Learning Sequences of Actions in Collectives of Autonomous Agents

NASA Technical Reports Server (NTRS)

Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)

2001-01-01

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Autonomous Agents and Intelligent Assistants for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2000-01-01

Human exploration of space will involve remote autonomous crew and systems in long missions. Data to earth will be delayed and limited. Earth control centers will not receive continuous real-time telemetry data, and there will be communication round trips of up to one hour. There will be reduced human monitoring on the planet and earth. When crews are present on the planet, they will be occupied with other activities, and system management will be a low priority task. Earth control centers will use multi-tasking "night shift" and on-call specialists. A new project at Johnson Space Center is developing software to support teamwork between distributed human and software agents in future interplanetary work environments. The Engineering and Mission Operations Directorates at Johnson Space Center (JSC) are combining laboratories and expertise to carry out this project, by establishing a testbed for hWl1an centered design, development and evaluation of intelligent autonomous and assistant systems. Intelligent autonomous systems for managing systems on planetary bases will commuicate their knowledge to support distributed multi-agent mixed-initiative operations. Intelligent assistant agents will respond to events by developing briefings and responses according to instructions from human agents on earth and in space.

An Application of Artificial Intelligence to the Implementation of Electronic Commerce

NASA Astrophysics Data System (ADS)

Srivastava, Anoop Kumar

In this paper, we present an application of Artificial Intelligence (AI) to the implementation of Electronic Commerce. We provide a multi autonomous agent based framework. Our agent based architecture leads to flexible design of a spectrum of multiagent system (MAS) by distributing computation and by providing a unified interface to data and programs. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, structure of Electronic Marketplace, an ontology, the agent model, and interaction pattern between agents is given. We have developed mechanisms for coordination between agents using a language, which is called Virtual Enterprise Modeling Language (VEML). VEML is a integration of Java and Knowledge Query and Manipulation Language (KQML). VEML provides application programmers with potential to globally develop different kinds of MAS based on their requirements and applications. We have implemented a multi autonomous agent based system called VE System. We demonstrate efficacy of our system by discussing experimental results and its salient features.

DualTrust: A Distributed Trust Model for Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.; Dionysiou, Ioanna; Frincke, Deborah A.

2011-02-01

For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, trust management is important for the acceptance of the mobile agent sensors and to protect the system from malicious behavior by insiders and entities that have penetrated network defenses. This paper examines the trust relationships, evidence, and decisions in a representative system and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. We then propose the DualTrust conceptual trust model. By addressing themore » autonomic manager’s bi-directional primary relationships in the ACS architecture, DualTrust is able to monitor the trustworthiness of the autonomic managers, protect the sensor swarm in a scalable manner, and provide global trust awareness for the orchestrating autonomic manager.« less

Situation Awareness of Onboard System Autonomy

NASA Technical Reports Server (NTRS)

Schreckenghost, Debra; Thronesbery, Carroll; Hudson, Mary Beth

2005-01-01

We have developed intelligent agent software for onboard system autonomy. Our approach is to provide control agents that automate crew and vehicle systems, and operations assistants that aid humans in working with these autonomous systems. We use the 3 Tier control architecture to develop the control agent software that automates system reconfiguration and routine fault management. We use the Distributed Collaboration and Interaction (DCI) System to develop the operations assistants that provide human services, including situation summarization, event notification, activity management, and support for manual commanding of autonomous system. In this paper we describe how the operations assistants aid situation awareness of the autonomous control agents. We also describe our evaluation of the DCI System to support control engineers during a ground test at Johnson Space Center (JSC) of the Post Processing System (PPS) for regenerative water recovery.

Directional Communication in Evolved Multiagent Teams

DTIC Science & Technology

2013-06-10

decentralized localization proposed by Franchi et al. [9]. Overall, the significant advantage of directional communication over non- directional...reception benefits the evolution of communicating autonomous agents because it simplifies the language required to express positional information, which...systems. This paper hypothesizes that such directional reception benefits the evolution of communicating autonomous agents because it simplifies the

Adjustable Autonomy Testbed

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schrenkenghost, Debra K.

2001-01-01

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Distance-Based Behaviors for Low-Complexity Control in Multiagent Robotics

NASA Astrophysics Data System (ADS)

Pierpaoli, Pietro

Several biological examples show that living organisms cooperate to collectively accomplish tasks impossible for single individuals. More importantly, this coordination is often achieved with a very limited set of information. Inspired by these observations, research on autonomous systems has focused on the development of distributed control techniques for control and guidance of groups of autonomous mobile agents, or robots. From an engineering perspective, when coordination and cooperation is sought in large ensembles of robotic vehicles, a reduction in hardware and algorithms' complexity becomes mandatory from the very early stages of the project design. The research for solutions capable of lowering power consumption, cost and increasing reliability are thus worth investigating. In this work, we studied low-complexity techniques to achieve cohesion and control on swarms of autonomous robots. Starting from an inspiring example with two-agents, we introduced effects of neighbors' relative positions on control of an autonomous agent. The extension of this intuition addressed the control of large ensembles of autonomous vehicles, and was applied in the form of a herding-like technique. To this end, a low-complexity distance-based aggregation protocol was defined. We first showed that our protocol produced a cohesion aggregation among the agent while avoiding inter-agent collisions. Then, a feedback leader-follower architecture was introduced for the control of the swarm. We also described how proximity measures and probability of collisions with neighbors can also be used as source of information in highly populated environments.

A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application.

PubMed

Mostafa, Salama A; Mustapha, Aida; Mohammed, Mazin Abed; Ahmad, Mohd Sharifuddin; Mahmoud, Moamin A

2018-04-01

Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments. This model aims to facilitate the autonomy management of agents and help them make competent autonomous decisions. The FLAA model employs fuzzy logic to quantitatively measure and distribute autonomy among several agents based on their performance. We implement and test this model in the Automated Elderly Movements Monitoring (AEMM-Care) system, which uses agents to monitor the daily movement activities of elderly users and perform fall detection and prevention tasks in a complex environment. The test results show that the FLAA model improves the accuracy and performance of these agents in detecting and preventing falls. Copyright © 2018 Elsevier B.V. All rights reserved.

Remote Agent Demonstration

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Kurien, James; Rajan, Kanna

1999-01-01

We describe the computer demonstration of the Remote Agent Experiment (RAX). The Remote Agent is a high-level, model-based, autonomous control agent being validated on the NASA Deep Space 1 spacecraft.

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

Self-organizing network services with evolutionary adaptation.

PubMed

Nakano, Tadashi; Suda, Tatsuya

2005-09-01

This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner.

Autonomous System Technologies for Resilient Airspace Operations

NASA Technical Reports Server (NTRS)

Houston, Vincent E.; Le Vie, Lisa R.

2017-01-01

Increasing autonomous systems within the aircraft cockpit begins with an effort to understand what autonomy is and developing the technology that encompasses it. Autonomy allows an agent, human or machine, to act independently within a circumscribed set of goals; delegating responsibility to the agent(s) to achieve overall system objective(s). Increasingly Autonomous Systems (IAS) are the highly sophisticated progression of current automated systems toward full autonomy. Working in concert with humans, these types of technologies are expected to improve the safety, reliability, costs, and operational efficiency of aviation. IAS implementation is imminent, which makes the development and the proper performance of such technologies, with respect to cockpit operation efficiency, the management of air traffic and data communication information, vital. A prototype IAS agent that attempts to optimize the identification and distribution of "relevant" air traffic data to be utilized by human crews during complex airspace operations has been developed.

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152 RTG

DTIC Science & Technology

2018-04-18

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG

DTIC Science & Technology

2018-04-01

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

The Use of an Autonomous Pedagogical Agent and Automatic Speech Recognition for Teaching Sight Words to Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Saadatzi, Mohammad Nasser; Pennington, Robert C.; Welch, Karla C.; Graham, James H.; Scott, Renee E.

2017-01-01

In the current study, we examined the effects of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and constant time delay during the instruction of reading sight words aloud to young adults with autism spectrum disorder. We used a concurrent multiple baseline across participants design to…

Computing architecture for autonomous microgrids

DOEpatents

Goldsmith, Steven Y.

2015-09-29

A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the .

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson's arms race model.

PubMed

Riaz, Faisal; Niazi, Muaz A

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson's arms race model has also been presented. The performance of the proposed social agent has been validated at two levels-firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme.

A Unified Approach to Model-Based Planning and Execution

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Norvig, Peter (Technical Monitor)

2000-01-01

Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson’s arms race model

PubMed Central

Niazi, Muaz A.

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson’s arms race model has also been presented. The performance of the proposed social agent has been validated at two levels–firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme. PMID:29040294

Needs, Pains, and Motivations in Autonomous Agents.

PubMed

Starzyk, Janusz A; Graham, James; Puzio, Leszek

This paper presents the development of a motivated learning (ML) agent with symbolic I/O. Our earlier work on the ML agent was enhanced, giving it autonomy for interaction with other agents. Specifically, we equipped the agent with drives and pains that establish its motivations to learn how to respond to desired and undesired events and create related abstract goals. The purpose of this paper is to explore the autonomous development of motivations and memory in agents within a simulated environment. The ML agent has been implemented in a virtual environment created within the NeoAxis game engine. Additionally, to illustrate the benefits of an ML-based agent, we compared the performance of our algorithm against various reinforcement learning (RL) algorithms in a dynamic test scenario, and demonstrated that our ML agent learns better than any of the tested RL agents.This paper presents the development of a motivated learning (ML) agent with symbolic I/O. Our earlier work on the ML agent was enhanced, giving it autonomy for interaction with other agents. Specifically, we equipped the agent with drives and pains that establish its motivations to learn how to respond to desired and undesired events and create related abstract goals. The purpose of this paper is to explore the autonomous development of motivations and memory in agents within a simulated environment. The ML agent has been implemented in a virtual environment created within the NeoAxis game engine. Additionally, to illustrate the benefits of an ML-based agent, we compared the performance of our algorithm against various reinforcement learning (RL) algorithms in a dynamic test scenario, and demonstrated that our ML agent learns better than any of the tested RL agents.

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

NASA Technical Reports Server (NTRS)

Muscettola, Nicola

2004-01-01

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Engineering Ultimate Self-Protection in Autonomic Agents for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future missions will be required to be self-managing as well as self-directed, in order to meet the challenges of human and robotic space exploration. We discuss security and self protection in autonomic agent based-systems, and propose the ultimate self-protection mechanism for such systems-self-destruction. Like other metaphors in Autonomic Computing, this is inspired by biological systems, and is the analog of biological apoptosis. Finally, we discus the role it might play in future NASA space exploration missions.

Organization-based Model-driven Development of High-assurance Multiagent Systems

DTIC Science & Technology

2009-02-27

based Model -driven Development of High-assurance Multiagent Systems " performed by Dr. Scott A . DeLoach and Dr Robby at Kansas State University... A Capabilities Based Model for Artificial Organizations. Journal of Autonomous Agents and Multiagent Systems . Volume 16, no. 1, February 2008, pp...Matson, E . T. (2007). A capabilities based theory of artificial organizations. Journal of Autonomous Agents and Multiagent Systems

An Approach to Model Based Testing of Multiagent Systems

PubMed Central

Nadeem, Aamer

2015-01-01

Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion. PMID:25874263

Autonomy: Life and Being

NASA Astrophysics Data System (ADS)

Williams, Mary-Anne

This paper uses robot experience to explore key concepts of autonomy, life and being. Unfortunately, there are no widely accepted definitions of autonomy, life or being. Using a new cognitive agent architecture we argue that autonomy is a key ingredient for both life and being, and set about exploring autonomy as a concept and a capability. Some schools of thought regard autonomy as the key characteristic that distinguishes a system from an agent; agents are systems with autonomy, but rarely is a definition of autonomy provided. Living entities are autonomous systems, and autonomy is vital to life. Intelligence presupposes autonomy too; what would it mean for a system to be intelligent but not exhibit any form of genuine autonomy. Our philosophical, scientific and legal understanding of autonomy and its implications is immature and as a result progress towards designing, building, managing, exploiting and regulating autonomous systems is retarded. In response we put forward a framework for exploring autonomy as a concept and capability based on a new cognitive architecture. Using this architecture tools and benchmarks can be developed to analyze and study autonomy in its own right as a means to further our understanding of autonomous systems, life and being. This endeavor would lead to important practical benefits for autonomous systems design and help determine the legal status of autonomous systems. It is only with a new enabling understanding of autonomy that the dream of Artificial Intelligence and Artificial Life can be realized. We argue that designing systems with genuine autonomy capabilities can be achieved by focusing on agent experiences of being rather than attempting to encode human experiences as symbolic knowledge and know-how in the artificial agents we build.

Multi-agent autonomous system

NASA Technical Reports Server (NTRS)

Fink, Wolfgang (Inventor); Dohm, James (Inventor); Tarbell, Mark A. (Inventor)

2010-01-01

A multi-agent autonomous system for exploration of hazardous or inaccessible locations. The multi-agent autonomous system includes simple surface-based agents or craft controlled by an airborne tracking and command system. The airborne tracking and command system includes an instrument suite used to image an operational area and any craft deployed within the operational area. The image data is used to identify the craft, targets for exploration, and obstacles in the operational area. The tracking and command system determines paths for the surface-based craft using the identified targets and obstacles and commands the craft using simple movement commands to move through the operational area to the targets while avoiding the obstacles. Each craft includes its own instrument suite to collect information about the operational area that is transmitted back to the tracking and command system. The tracking and command system may be further coupled to a satellite system to provide additional image information about the operational area and provide operational and location commands to the tracking and command system.

Self-emergence of Lexicon Consensus in a Population of Autonomous Agents by Means of Evolutionary Strategies

NASA Astrophysics Data System (ADS)

Maravall, Darío; de Lope, Javier; Domínguez, Raúl

In Multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of evolutionary strategies to the self-emergence of a common lexicon in a population of agents. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the agents or the states of the environment itself) into symbols or signals we check whether it is possible for the population to converge in an autonomous, decentralized way to a common lexicon, so that the communication efficiency of the entire population is optimal. We have conducted several experiments, from the simplest case of a 2×2 association matrix (i.e. two meanings and two symbols) to a 3×3 lexicon case and in both cases we have attained convergence to the optimal communication system by means of evolutionary strategies. To analyze the convergence of the population of agents we have defined the population's consensus when all the agents (i.e. the 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that evolutionary strategies are powerful enough optimizers to guarantee the convergence to lexicon consensus in a population of autonomous agents.

The Unified Behavior Framework for the Simulation of Autonomous Agents

DTIC Science & Technology

2015-03-01

1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed ...Identification Friend or Foe viii THE UNIFIED BEHAVIOR FRAMEWORK FOR THE SIMULATION OF AUTONOMOUS AGENTS I. Introduction The development of autonomy has...room for research by utilizing methods like simulation and modeling that consume less time and fewer monetary resources. A recently developed reactive

Methyl methacrylate as a healing agent for self-healing cementitious materials

NASA Astrophysics Data System (ADS)

Van Tittelboom, K.; Adesanya, K.; Dubruel, P.; Van Puyvelde, P.; De Belie, N.

2011-12-01

Different types of healing agents have already been tested on their efficiency for use in self-healing cementitious materials. Generally, commercial healing agents are used while their properties are adjusted for manual crack repair and not for autonomous crack healing. Consequently, the amount of regain in properties due to self-healing of cracks is limited. In this research, a methyl methacrylate (MMA)-based healing agent was developed specifically for use in self-healing cementitious materials. Various parameters were optimized including the viscosity, curing time, strength, etc. After the desired properties were obtained, the healing agent was encapsulated and screened for its self-healing efficiency. The decrease in water permeability due to autonomous crack healing using MMA as a healing agent was similar to the results obtained for manually healed cracks. First results seem promising: however, further research needs to be undertaken in order to obtain an optimal healing agent ready for use in practice.

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and stillmore » serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.« less

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Automated monitoring of medical protocols: a secure and distributed architecture.

PubMed

Alsinet, T; Ansótegui, C; Béjar, R; Fernández, C; Manyà, F

2003-03-01

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

Autonomous Decentralized Voltage Profile Control of Super Distributed Energy System using Multi-agent Technology

NASA Astrophysics Data System (ADS)

Tsuji, Takao; Hara, Ryoichi; Oyama, Tsutomu; Yasuda, Keiichiro

A super distributed energy system is a future energy system in which the large part of its demand is fed by a huge number of distributed generators. At one time some nodes in the super distributed energy system behave as load, however, at other times they behave as generator - the characteristic of each node depends on the customers' decision. In such situation, it is very difficult to regulate voltage profile over the system due to the complexity of power flows. This paper proposes a novel control method of distributed generators that can achieve the autonomous decentralized voltage profile regulation by using multi-agent technology. The proposed multi-agent system employs two types of agent; a control agent and a mobile agent. Control agents generate or consume reactive power to regulate the voltage profile of neighboring nodes and mobile agents transmit the information necessary for VQ-control among the control agents. The proposed control method is tested through numerical simulations.

A Diversified Investment Strategy Using Autonomous Agents

NASA Astrophysics Data System (ADS)

Barbosa, Rui Pedro; Belo, Orlando

In a previously published article, we presented an architecture for implementing agents with the ability to trade autonomously in the Forex market. At the core of this architecture is an ensemble of classification and regression models that is used to predict the direction of the price of a currency pair. In this paper, we will describe a diversified investment strategy consisting of five agents which were implemented using that architecture. By simulating trades with 18 months of out-of-sample data, we will demonstrate that data mining models can produce profitable predictions, and that the trading risk can be diminished through investment diversification.

Autonomous sensor manager agents (ASMA)

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.

2004-04-01

Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.

Contrasting actions of pressor agents in severe autonomic failure

NASA Technical Reports Server (NTRS)

Jordan, J.; Shannon, J. R.; Biaggioni, I.; Norman, R.; Black, B. K.; Robertson, D.

1998-01-01

BACKGROUND: Orthostatic hypotension is the most disabling symptom of autonomic failure. The choice of a pressor agent is largely empiric, and it would be of great value to define predictors of a response. PATIENTS AND METHODS: In 35 patients with severe orthostatic hypotension due to multiple system atrophy or pure autonomic failure, we determined the effect on seated systolic blood pressure (SBP) of placebo, phenylpropanolamine (12.5 mg and 25 mg), yohimbine (5.4 mg), indomethacin (50 mg), ibuprofen (600 mg), caffeine (250 mg), and methylphenidate (5 mg). In a subgroup of patients, we compared the pressor effect of midodrine (5 mg) with the effect of phenylpropanolamine (12.5 mg). RESULTS: There were no significant differences in the pressor responses between patients with multiple system atrophy or pure autonomic failure. When compared with placebo, the pressor response was significant for phenylpropanolamine, yohimbine, and indomethacin. In a subgroup of patients, we confirmed that this pressor effect of phenylpropanolamine, yohimbine, and indomethacin corresponded to a significant increase in standing SBP. The pressor responses to ibuprofen, caffeine, and methylphenidate were not significantly different from placebo. Phenylpropanolamine and midodrine elicited similar pressor responses. There were no significant associations between drug response and autonomic function testing, postprandial hypotension, or plasma catecholamine levels. CONCLUSIONS: We conclude that significant increases in systolic blood pressure can be obtained in patients with orthostatic hypotension due to primary autonomic failure with phenylpropanolamine in low doses or yohimbine or indomethacin in moderate doses. The response to a pressor agent cannot be predicted by autonomic function testing or plasma catecholamines. Therefore, empiric testing with a sequence of medications, based on the risk of side effects in the individual patient and the probability of a response, is a useful approach.

Proposed Methodology for Application of Human-like gradual Multi-Agent Q-Learning (HuMAQ) for Multi-robot Exploration

NASA Astrophysics Data System (ADS)

Narayan Ray, Dip; Majumder, Somajyoti

2014-07-01

Several attempts have been made by the researchers around the world to develop a number of autonomous exploration techniques for robots. But it has been always an important issue for developing the algorithm for unstructured and unknown environments. Human-like gradual Multi-agent Q-leaming (HuMAQ) is a technique developed for autonomous robotic exploration in unknown (and even unimaginable) environments. It has been successfully implemented in multi-agent single robotic system. HuMAQ uses the concept of Subsumption architecture, a well-known Behaviour-based architecture for prioritizing the agents of the multi-agent system and executes only the most common action out of all the different actions recommended by different agents. Instead of using new state-action table (Q-table) each time, HuMAQ uses the immediate past table for efficient and faster exploration. The proof of learning has also been established both theoretically and practically. HuMAQ has the potential to be used in different and difficult situations as well as applications. The same architecture has been modified to use for multi-robot exploration in an environment. Apart from all other existing agents used in the single robotic system, agents for inter-robot communication and coordination/ co-operation with the other similar robots have been introduced in the present research. Current work uses a series of indigenously developed identical autonomous robotic systems, communicating with each other through ZigBee protocol.

A Markov Chain Approach to Probabilistic Swarm Guidance

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Bayard, David S.

2012-01-01

This paper introduces a probabilistic guidance approach for the coordination of swarms of autonomous agents. The main idea is to drive the swarm to a prescribed density distribution in a prescribed region of the configuration space. In its simplest form, the probabilistic approach is completely decentralized and does not require communication or collabo- ration between agents. Agents make statistically independent probabilistic decisions based solely on their own state, that ultimately guides the swarm to the desired density distribution in the configuration space. In addition to being completely decentralized, the probabilistic guidance approach has a novel autonomous self-repair property: Once the desired swarm density distribution is attained, the agents automatically repair any damage to the distribution without collaborating and without any knowledge about the damage.

Extending the Trans-Contextual Model in Physical Education and Leisure-Time Contexts: Examining the Role of Basic Psychological Need Satisfaction

ERIC Educational Resources Information Center

Barkoukis, Vassilis; Hagger, Martin S.; Lambropoulos, George; Tsorbatzoudis, Haralambos

2010-01-01

Background: The trans-contextual model (TCM) is an integrated model of motivation that aims to explain the processes by which agentic support for autonomous motivation in physical education promotes autonomous motivation and physical activity in a leisure-time context. It is proposed that perceived support for autonomous motivation in physical…

Improving Human/Autonomous System Teaming Through Linguistic Analysis

NASA Technical Reports Server (NTRS)

Meszaros, Erica L.

2016-01-01

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such integration requires humans to work closely with autonomous systems, forming human and autonomous agent teams. The intention behind such teaming is that a team composed of both humans and autonomous agents will operate better than homogenous teams. Procedures exist for licensing pilots to operate in the national airspace system and current work is being done to define methods for validating the function of autonomous systems, however there is no method in place for assessing the interaction of these two disparate systems. Moreover, currently these systems are operated primarily by subject matter experts, limiting their use and the benefits of such teams. Providing additional information about the ongoing mission to the operator can lead to increased usability and allow for operation by non-experts. Linguistic analysis of the context of verbal communication provides insight into the intended meaning of commonly heard phrases such as "What's it doing now?" Analyzing the semantic sphere surrounding these common phrases enables the prediction of the operator's intent and allows the interface to supply the operator's desired information.

Online Deception Detection Using BDI Agents

ERIC Educational Resources Information Center

Merritts, Richard A.

2013-01-01

This research has two facets within separate research areas. The research area of Belief, Desire and Intention (BDI) agent capability development was extended. Deception detection research has been advanced with the development of automation using BDI agents. BDI agents performed tasks automatically and autonomously. This study used these…

Autonomous stimulus triggered self-healing in smart structural composites

NASA Astrophysics Data System (ADS)

Norris, C. J.; White, J. A. P.; McCombe, G.; Chatterjee, P.; Bond, I. P.; Trask, R. S.

2012-09-01

Inspired by the ability of biological systems to sense and autonomously heal damage, this research has successfully demonstrated the first autonomous, stimulus triggered, self-healing system in a structural composite material. Both the sensing and healing mechanisms are reliant on microvascular channels incorporated within a laminated composite material. For the triggering mechanism, a single air filled vessel was pressurized, sealed and monitored. Upon drop weight impact (10 J), delamination and microcrack connectivity between the pressurized vessel and those open to ambient led to a pressure loss which, with the use of a suitable sensor, triggered a pump to deliver a healing agent to the damage zone. Using this autonomous healing approach, near full recovery of post-impact compression strength was achieved (94% on average). A simplified alternative system with healing agent continuously flowing through the vessels, akin to blood flow, was found to offer 100% recovery of the material’s virgin strength. Optical microscopy and ultrasonic C-scanning provided further evidence of large-scale infusion of matrix damage with the healing agent. The successful implementation of this bioinspired technology could substantially enhance the integrity and reliability of aerospace structures, whilst offering benefits through improved performance/weight ratios and extended lifetimes.

Emergent Aerospace Designs Using Negotiating Autonomous Agents

NASA Technical Reports Server (NTRS)

Deshmukh, Abhijit; Middelkoop, Timothy; Krothapalli, Anjaneyulu; Smith, Charles

2000-01-01

This paper presents a distributed design methodology where designs emerge as a result of the negotiations between different stake holders in the process, such as cost, performance, reliability, etc. The proposed methodology uses autonomous agents to represent design decision makers. Each agent influences specific design parameters in order to maximize their utility. Since the design parameters depend on the aggregate demand of all the agents in the system, design agents need to negotiate with others in the market economy in order to reach an acceptable utility value. This paper addresses several interesting research issues related to distributed design architectures. First, we present a flexible framework which facilitates decomposition of the design problem. Second, we present overview of a market mechanism for generating acceptable design configurations. Finally, we integrate learning mechanisms in the design process to reduce the computational overhead.

The NASA/Army Autonomous Rotorcraft Project

NASA Technical Reports Server (NTRS)

Whalley, M.; Freed, M.; Takahashi, M.; Christian, D.; Patterson-Hine, A.; Schulein, G.; Harris, R.

2002-01-01

An overview of the NASA Ames Research Center Autonomous Rotorcraft Project (ARP) is presented. The project brings together several technologies to address NASA and US Army autonomous vehicle needs, including a reactive planner for mission planning and execution, control system design incorporating a detailed understanding of the platform dynamics, and health monitoring and diagnostics. A candidate reconnaissance and surveillance mission is described. The autonomous agent architecture and its application to the candidate mission are presented. Details of the vehicle hardware and software development are provided.

Learning Hierarchical Skills for Game Agents from Video of Human Behavior

DTIC Science & Technology

2009-01-01

intelligent agents for computer games is an im- portant aspect of game development . However, traditional methods are expensive, and the resulting agents...Constructing autonomous agents is an essential task in game development . In this paper, we outlined a system that an- alyzes preprocessed video footage of

A Real-Time Rover Executive based On Model-Based Reactive Planning

NASA Technical Reports Server (NTRS)

Bias, M. Bernardine; Lemai, Solange; Muscettola, Nicola; Korsmeyer, David (Technical Monitor)

2003-01-01

This paper reports on the experimental verification of the ability of IDEA (Intelligent Distributed Execution Architecture) effectively operate at multiple levels of abstraction in an autonomous control system. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting control agents, each organized around the same fundamental structure. Two IDEA agents, a system-level agent and a mission-level agent, are designed and implemented to autonomously control the K9 rover in real-time. The system is evaluated in the scenario where the rover must acquire images from a specified set of locations. The IDEA agents are responsible for enabling the rover to achieve its goals while monitoring the execution and safety of the rover and recovering from dangerous states when necessary. Experiments carried out both in simulation and on the physical rover, produced highly promising results.

Recent Developments on Microencapsulation for Autonomous Corrosion Protection

NASA Technical Reports Server (NTRS)

Calle, Luz M.; Li, Wenyan; Buhrow, Jerry W.; Fitzpatrick, Lilliana; Jolley, Scott T.; Surma, Jan M.; Pearman, Benjamin P.; Zhang, Xuejun

2014-01-01

This work concerns recent progress in the development of a multifunctional smart coating based on microencapsulation for the autonomous control of corrosion. Microencapsulation allows the incorporation of desired corrosion control functionalities, such as early corrosion detection and inhibition through corrosion controlled release of corrosion indicators and inhibitors, as well as self-healing agent release when mechanical damage occurs.While proof-of-concept results have been reported previously, more recent efforts have been concentrated in technical developments to improve coating compatibility, synthesis procedure scalability, as well as fine tuning the release property of encapsulated active agents.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Intelligent Autonomy for Unmanned Surface and Underwater Vehicles

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Woodward, Gail

2011-01-01

As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.

A Lego Mindstorms NXT based test bench for multiagent exploratory systems and distributed network partitioning

NASA Astrophysics Data System (ADS)

Patil, Riya Raghuvir

Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for selfpartitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the LegoRTM Mindstorms' NXT on a graphical programming platform using National Instruments' LabVIEW(TM) forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

Maintaining Limited-Range Connectivity Among Second-Order Agents

DTIC Science & Technology

2016-07-07

we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do...hoc networks of mobile autonomous agents. This loose ter- minology refers to groups of robotic agents with limited mobility and communica- tion...connectivity can be preserved. 3.1. Networks of robotic agents with second-order dynamics and the connectivity maintenance problem. We begin by

"Campus" - An Agent-Based Platform for Distance Education.

ERIC Educational Resources Information Center

Westhoff, Dirk; Unger, Claus

This paper presents "Campus," an environment that allows University of Hagen (Germany) students to connect briefly to the Internet but remain represented by personalized, autonomous agents that can fulfill a variety of information, communication, planning, and cooperation tasks. A brief survey is presented of existing mobile agent system…

Autonomous Learning from a Social Cognitive Perspective

ERIC Educational Resources Information Center

Ponton, Michael K.; Rhea, Nancy E.

2006-01-01

The current perspective of autonomous learning defines it as the agentive exhibition of resourcefulness, initiative, and persistence in self-directed learning. As a form of human agency, it has been argued in the literature that this perspective should be consistent with Bandura's (1986) Social Cognitive Theory (SCT). The purpose of this article…

Collaborating with Autonomous Agents

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Cross, Charles D.; Fan, Henry; Hempley, Lucas E.; Motter, Mark A.; Neilan, James H.; Qualls, Garry D.; Rothhaar, Paul M.; Tran, Loc D.; Allen, B. Danette

2015-01-01

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langley's Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicle's language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Naming games in two-dimensional and small-world-connected random geometric networks.

PubMed

Lu, Qiming; Korniss, G; Szymanski, B K

2008-01-01

We investigate a prototypical agent-based model, the naming game, on two-dimensional random geometric networks. The naming game [Baronchelli, J. Stat. Mech.: Theory Exp. (2006) P06014] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the naming games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case.

Autonomous mission management for UAVs using soar intelligent agents

NASA Astrophysics Data System (ADS)

Gunetti, Paolo; Thompson, Haydn; Dodd, Tony

2013-05-01

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Nicewarner, Keith

2006-01-01

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Agent-based human-robot interaction of a combat bulldozer

NASA Astrophysics Data System (ADS)

Granot, Reuven; Feldman, Maxim

2004-09-01

A small-scale supervised autonomous bulldozer in a remote site was developed to experience agent based human intervention. The model is based on Lego Mindstorms kit and represents combat equipment, whose job performance does not require high accuracy. The model enables evaluation of system response for different operator interventions, as well as for a small colony of semiautonomous dozers. The supervising human may better react than a fully autonomous system to unexpected contingent events, which are a major barrier to implement full autonomy. The automation is introduced as improved Man Machine Interface (MMI) by developing control agents as intelligent tools to negotiate between human requests and task level controllers as well as negotiate with other elements of the software environment. Current UGVs demand significant communication resources and constant human operation. Therefore they will be replaced by semi-autonomous human supervisory controlled systems (telerobotic). For human intervention at the low layers of the control hierarchy we suggest a task oriented control agent to take care of the fluent transition between the state in which the robot operates and the one imposed by the human. This transition should take care about the imperfections, which are responsible for the improper operation of the robot, by disconnecting or adapting them to the new situation. Preliminary conclusions from the small-scale experiments are presented.

Collaborative autonomous sensing with Bayesians in the loop

NASA Astrophysics Data System (ADS)

Ahmed, Nisar

2016-10-01

There is a strong push to develop intelligent unmanned autonomy that complements human reasoning for applications as diverse as wilderness search and rescue, military surveillance, and robotic space exploration. More than just replacing humans for `dull, dirty and dangerous' work, autonomous agents are expected to cope with a whole host of uncertainties while working closely together with humans in new situations. The robotics revolution firmly established the primacy of Bayesian algorithms for tackling challenging perception, learning and decision-making problems. Since the next frontier of autonomy demands the ability to gather information across stretches of time and space that are beyond the reach of a single autonomous agent, the next generation of Bayesian algorithms must capitalize on opportunities to draw upon the sensing and perception abilities of humans-in/on-the-loop. This work summarizes our recent research toward harnessing `human sensors' for information gathering tasks. The basic idea behind is to allow human end users (i.e. non-experts in robotics, statistics, machine learning, etc.) to directly `talk to' the information fusion engine and perceptual processes aboard any autonomous agent. Our approach is grounded in rigorous Bayesian modeling and fusion of flexible semantic information derived from user-friendly interfaces, such as natural language chat and locative hand-drawn sketches. This naturally enables `plug and play' human sensing with existing probabilistic algorithms for planning and perception, and has been successfully demonstrated with human-robot teams in target localization applications.

Stability of distributed MPC in an intersection scenario

NASA Astrophysics Data System (ADS)

Sprodowski, T.; Pannek, J.

2015-11-01

The research topic of autonomous cars and the communication among them has attained much attention in the last years and is developing quickly. Among others, this research area spans fields such as image recognition, mathematical control theory, communication networks, and sensor fusion. We consider an intersection scenario where we divide the shared road space in different cells. These cells form a grid. The cars are modelled as an autonomous multi-agent system based on the Distributed Model Predictive Control algorithm (DMPC). We prove that the overall system reaches stability using Optimal Control for each multi-agent and demonstrate that by numerical results.

Kinetic theory of situated agents applied to pedestrian flow in a corridor

NASA Astrophysics Data System (ADS)

Rangel-Huerta, A.; Muñoz-Meléndez, A.

2010-03-01

A situated agent-based model for simulation of pedestrian flow in a corridor is presented. In this model, pedestrians choose their paths freely and make decisions based on local criteria for solving collision conflicts. The crowd consists of multiple walking agents equipped with a function of perception as well as a competitive rule-based strategy that enables pedestrians to reach free access areas. Pedestrians in our model are autonomous entities capable of perceiving and making decisions. They apply socially accepted conventions, such as avoidance rules, as well as individual preferences such as the use of specific exit points, or the execution of eventual comfort turns resulting in spontaneous changes of walking speed. Periodic boundary conditions were considered in order to determine the density-average walking speed, and the density-average activity with respect to specific parameters: comfort angle turn and frequency of angle turn of walking agents. The main contribution of this work is an agent-based model where each pedestrian is represented as an autonomous agent. At the same time the pedestrian crowd dynamics is framed by the kinetic theory of biological systems.

Collective Bargaining and the Concept of Autonomy in the National Autonomous University of Mexico.

ERIC Educational Resources Information Center

Hartnett, Richard A.

Major issues concerning the negotiation of a collective bargaining contract on February 1, 1981, at the National Autonomous Associations of Academic Personnel of the University (AAPAUNAM), the first legally authorized bargaining agent of the faculty. The contract was negotiated under terms of the recently enacted amendments to the federal…

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

Agent-Based Scientific Workflow Composition

NASA Astrophysics Data System (ADS)

Barker, A.; Mann, B.

2006-07-01

Agents are active autonomous entities that interact with one another to achieve their objectives. This paper addresses how these active agents are a natural fit to consume the passive Service Oriented Architecture which is found in Internet and Grid Systems, in order to compose, coordinate and execute e-Science experiments. A framework is introduced which allows an e-Science experiment to be described as a MultiAgent System.

Minimal Representation and Decision Making for Networked Autonomous Agents

DTIC Science & Technology

2015-08-27

to a multi-vehicle version of the Travelling Salesman Problem (TSP). We further provided a direct formula for computing the number of robots...the sensor. As a first stab at this, the two-agent rendezvous problem is considered where one agent (the target) is equipped with no sensors and is...by the total distance traveled by all agents. For agents with limited sensing and communication capabilities, we give a formula that computes the

Development of Methodology for Programming Autonomous Agents

NASA Technical Reports Server (NTRS)

Erol, Kutluhan; Levy, Renato; Lang, Lun

2004-01-01

A brief report discusses the rationale for, and the development of, a methodology for generating computer code for autonomous-agent-based systems. The methodology is characterized as enabling an increase in the reusability of the generated code among and within such systems, thereby making it possible to reduce the time and cost of development of the systems. The methodology is also characterized as enabling reduction of the incidence of those software errors that are attributable to the human failure to anticipate distributed behaviors caused by the software. A major conceptual problem said to be addressed in the development of the methodology was that of how to efficiently describe the interfaces between several layers of agent composition by use of a language that is both familiar to engineers and descriptive enough to describe such interfaces unambivalently

Protection of autonomous microgrids using agent-based distributed communication

DOE PAGES

Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

2016-04-06

This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

Model-based Executive Control through Reactive Planning for Autonomous Rovers

NASA Technical Reports Server (NTRS)

Finzi, Alberto; Ingrand, Felix; Muscettola, Nicola

2004-01-01

This paper reports on the design and implementation of a real-time executive for a mobile rover that uses a model-based, declarative approach. The control system is based on the Intelligent Distributed Execution Architecture (IDEA), an approach to planning and execution that provides a unified representational and computational framework for an autonomous agent. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting agents, each with the same fundamental structure. We show that planning and real-time response are compatible if the executive minimizes the size of the planning problem. We detail the implementation of this approach on an exploration rover (Gromit an RWI ATRV Junior at NASA Ames) presenting different IDEA controllers of the same domain and comparing them with more classical approaches. We demonstrate that the approach is scalable to complex coordination of functional modules needed for autonomous navigation and exploration.

Protection of autonomous microgrids using agent-based distributed communication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

Flocking algorithm for autonomous flying robots.

PubMed

Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás

2014-06-01

Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.

Implementation of Autonomous Navigation and Mapping using a Laser Line Scanner on a Tactical Unmanned Aerial Vehicle

DTIC Science & Technology

2011-12-01

study new multi-agent algorithms to avoid collision and obstacles. Others, including Hanford et al. [2], have tried to build low-cost experimental...2007. [2] S. D. Hanford , L. N. Long, and J. F. Horn, “A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle ( UAV ),” 2003 AIAA Atmospheric

University Student and Teacher Perceptions of Teacher Roles in Promoting Autonomous Language Learning with Technology outside the Classroom

ERIC Educational Resources Information Center

Lai, Chun; Yeung, Yuk; Hu, Jingjing

2016-01-01

Helping students to become autonomous learners, who actively utilize technologies for learning outside the classroom, is important for successful language learning. Teachers, as significant social agents who shape students' intellectual and social experiences, have a critical role to play. This study examined students' and teachers' perceptions of…

Mobile agent location in distributed environments

NASA Astrophysics Data System (ADS)

Fountoukis, S. G.; Argyropoulos, I. P.

2012-12-01

An agent is a small program acting on behalf of a user or an application which plays the role of a user. Artificial intelligence can be encapsulated in agents so that they can be capable of both behaving autonomously and showing an elementary decision ability regarding movement and some specific actions. Therefore they are often called autonomous mobile agents. In a distributed system, they can move themselves from one processing node to another through the interconnecting network infrastructure. Their purpose is to collect useful information and to carry it back to their user. Also, agents are used to start, monitor and stop processes running on the individual interconnected processing nodes of computer cluster systems. An agent has a unique id to discriminate itself from other agents and a current position. The position can be expressed as the address of the processing node which currently hosts the agent. Very often, it is necessary for a user, a processing node or another agent to know the current position of an agent in a distributed system. Several procedures and algorithms have been proposed for the purpose of position location of mobile agents. The most basic of all employs a fixed computing node, which acts as agent position repository, receiving messages from all the moving agents and keeping records of their current positions. The fixed node, responds to position queries and informs users, other nodes and other agents about the position of an agent. Herein, a model is proposed that considers pairs and triples of agents instead of single ones. A location method, which is investigated in this paper, attempts to exploit this model.

Casuist BDI-Agent: A New Extended BDI Architecture with the Capability of Ethical Reasoning

NASA Astrophysics Data System (ADS)

Honarvar, Ali Reza; Ghasem-Aghaee, Nasser

Since the intelligent agent is developed to be cleverer, more complex, and yet uncontrollable, a number of problems have been recognized. The capability of agents to make moral decisions has become an important question, when intelligent agents have developed more autonomous and human-like. We propose Casuist BDI-Agent architecture which extends the power of BDI architecture. Casuist BDI-Agent architecture combines CBR method in AI and bottom up casuist approach in ethics in order to add capability of ethical reasoning to BDI-Agent.

Mission Operations with an Autonomous Agent

NASA Technical Reports Server (NTRS)

Pell, Barney; Sawyer, Scott R.; Muscettola, Nicola; Smith, Benjamin; Bernard, Douglas E.

1998-01-01

The Remote Agent (RA) is an Artificial Intelligence (AI) system which automates some of the tasks normally reserved for human mission operators and performs these tasks autonomously on-board the spacecraft. These tasks include activity generation, sequencing, spacecraft analysis, and failure recovery. The RA will be demonstrated as a flight experiment on Deep Space One (DSI), the first deep space mission of the NASA's New Millennium Program (NMP). As we moved from prototyping into actual flight code development and teamed with ground operators, we made several major extensions to the RA architecture to address the broader operational context in which PA would be used. These extensions support ground operators and the RA sharing a long-range mission profile with facilities for asynchronous ground updates; support ground operators monitoring and commanding the spacecraft at multiple levels of detail simultaneously; and enable ground operators to provide additional knowledge to the RA, such as parameter updates, model updates, and diagnostic information, without interfering with the activities of the RA or leaving the system in an inconsistent state. The resulting architecture supports incremental autonomy, in which a basic agent can be delivered early and then used in an increasingly autonomous manner over the lifetime of the mission. It also supports variable autonomy, as it enables ground operators to benefit from autonomy when L'@ey want it, but does not inhibit them from obtaining a detailed understanding and exercising tighter control when necessary. These issues are critical to the successful development and operation of autonomous spacecraft.

A Biologically Inspired Cooperative Multi-Robot Control Architecture

NASA Technical Reports Server (NTRS)

Howsman, Tom; Craft, Mike; ONeil, Daniel; Howell, Joe T. (Technical Monitor)

2002-01-01

A prototype cooperative multi-robot control architecture suitable for the eventual construction of large space structures has been developed. In nature, there are numerous examples of complex architectures constructed by relatively simple insects, such as termites and wasps, which cooperatively assemble their nests. The prototype control architecture emulates this biological model. Actions of each of the autonomous robotic construction agents are only indirectly coordinated, thus mimicking the distributed construction processes of various social insects. The robotic construction agents perform their primary duties stigmergically i.e., without direct inter-agent communication and without a preprogrammed global blueprint of the final design. Communication and coordination between individual agents occurs indirectly through the sensed modifications that each agent makes to the structure. The global stigmergic building algorithm prototyped during the initial research assumes that the robotic builders only perceive the current state of the structure under construction. Simulation studies have established that an idealized form of the proposed architecture was indeed capable of producing representative large space structures with autonomous robots. This paper will explore the construction simulations in order to illustrate the multi-robot control architecture.

A Stigmergic Cooperative Multi-Robot Control Architecture

NASA Technical Reports Server (NTRS)

Howsman, Thomas G.; O'Neil, Daniel; Craft, Michael A.

2004-01-01

In nature, there are numerous examples of complex architectures constructed by relatively simple insects, such as termites and wasps, which cooperatively assemble their nests. A prototype cooperative multi-robot control architecture which may be suitable for the eventual construction of large space structures has been developed which emulates this biological model. Actions of each of the autonomous robotic construction agents are only indirectly coordinated, thus mimicking the distributed construction processes of various social insects. The robotic construction agents perform their primary duties stigmergically, i.e., without direct inter-agent communication and without a preprogrammed global blueprint of the final design. Communication and coordination between individual agents occurs indirectly through the sensed modifications that each agent makes to the structure. The global stigmergic building algorithm prototyped during the initial research assumes that the robotic builders only perceive the current state of the structure under construction. Simulation studies have established that an idealized form of the proposed architecture was indeed capable of producing representative large space structures with autonomous robots. This paper will explore the construction simulations in order to illustrate the multi-robot control architecture.

Autonomous intelligent cars: proof that the EPSRC Principles are future-proof

NASA Astrophysics Data System (ADS)

de Cock Buning, Madeleine; de Bruin, Roeland

2017-07-01

Principle 2 of the EPSRC's principles of robotics (AISB workshop on Principles of Robotics, 2016) proves to be future proof when applied to the current state of the art of law and technology surrounding autonomous intelligent cars (AICs). Humans, not AICS, are responsible agents. AICs should be designed; operated as far as is practicable to comply with existing laws and fundamental rights and freedoms, including privacy by design. It will show that some legal questions arising from autonomous intelligent driving technology can be answered by the technology itself.

A Buyer Behaviour Framework for the Development and Design of Software Agents in E-Commerce.

ERIC Educational Resources Information Center

Sproule, Susan; Archer, Norm

2000-01-01

Software agents are computer programs that run in the background and perform tasks autonomously as delegated by the user. This paper blends models from marketing research and findings from the field of decision support systems to build a framework for the design of software agents to support in e-commerce buying applications. (Contains 35…

Next Generation Remote Agent Planner

NASA Technical Reports Server (NTRS)

Jonsson, Ari K.; Muscettola, Nicola; Morris, Paul H.; Rajan, Kanna

1999-01-01

In May 1999, as part of a unique technology validation experiment onboard the Deep Space One spacecraft, the Remote Agent became the first complete autonomous spacecraft control architecture to run as flight software onboard an active spacecraft. As one of the three components of the architecture, the Remote Agent Planner had the task of laying out the course of action to be taken, which included activities such as turning, thrusting, data gathering, and communicating. Building on the successful approach developed for the Remote Agent Planner, the Next Generation Remote Agent Planner is a completely redesigned and reimplemented version of the planner. The new system provides all the key capabilities of the original planner, while adding functionality, improving performance and providing a modular and extendible implementation. The goal of this ongoing project is to develop a system that provides both a basis for future applications and a framework for further research in the area of autonomous planning for spacecraft. In this article, we present an introductory overview of the Next Generation Remote Agent Planner. We present a new and simplified definition of the planning problem, describe the basics of the planning process, lay out the new system design and examine the functionality of the core reasoning module.

Fuzzy Cognitive and Social Negotiation Agent Strategy for Computational Collective Intelligence

NASA Astrophysics Data System (ADS)

Chohra, Amine; Madani, Kurosh; Kanzari, Dalel

Finding the adequate (win-win solutions for both parties) negotiation strategy with incomplete information for autonomous agents, even in one-to-one negotiation, is a complex problem. Elsewhere, negotiation behaviors, in which the characters such as conciliatory or aggressive define a 'psychological' aspect of the negotiator personality, play an important role. The aim of this paper is to develop a fuzzy cognitive and social negotiation strategy for autonomous agents with incomplete information, where the characters conciliatory, neutral, or aggressive, are suggested to be integrated in negotiation behaviors (inspired from research works aiming to analyze human behavior and those on social negotiation psychology). For this purpose, first, one-to-one bargaining process, in which a buyer agent and a seller agent negotiate over single issue (price), is developed for a time-dependent strategy (based on time-dependent behaviors of Faratin et al.) and for a fuzzy cognitive and social strategy. Second, experimental environments and measures, allowing a set of experiments, carried out for different negotiation deadlines of buyer and seller agents, are detailed. Third, experimental results for both time-dependent and fuzzy cognitive and social strategies are presented, analyzed, and compared for different deadlines of agents. The suggested fuzzy cognitive and social strategy allows agents to improve the negotiation process, with regard to the time-dependent one, in terms of agent utilities, round number to reach an agreement, and percentage of agreements.

Visualizing Decision-making Behaviours in Agent-based Autonomous Spacecraft

NASA Technical Reports Server (NTRS)

North, Steve; Hennessy, Joseph F. (Technical Monitor)

2003-01-01

The authors will report initial progress on the PIAudit project as a Research Resident Associate Program. The objective of this research is to prototype a tool for visualizing decision-making behaviours in autonomous spacecraft. This visualization will serve as an information source for human analysts. The current visualization prototype for PIAudit combines traditional Decision Trees with Weights of Evidence.

Agent Based Software for the Autonomous Control of Formation Flying Spacecraft

NASA Technical Reports Server (NTRS)

How, Jonathan P.; Campbell, Mark; Dennehy, Neil (Technical Monitor)

2003-01-01

Distributed satellite systems is an enabling technology for many future NASA/DoD earth and space science missions, such as MMS, MAXIM, Leonardo, and LISA [1, 2, 3]. While formation flying offers significant science benefits, to reduce the operating costs for these missions it will be essential that these multiple vehicles effectively act as a single spacecraft by performing coordinated observations. Autonomous guidance, navigation, and control as part of a coordinated fleet-autonomy is a key technology that will help accomplish this complex goal. This is no small task, as most current space missions require significant input from the ground for even relatively simple decisions such as thruster burns. Work for the NMP DS1 mission focused on the development of the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. NMRA integrates traditional real-time monitoring and control with components for constraint-based planning, robust multi-threaded execution, and model-based diagnosis and reconfiguration. The complexity of using an autonomous approach for space flight software was evident when most of its capabilities were stripped off prior to launch (although more capability was uplinked subsequently, and the resulting demonstration was very successful).

Operator Informational Needs for Multiple Autonomous Small Vehicles

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Fan, Henry; Cross, Charles D.; Hempley, Lucas E.; Cichella, Venanzio; Puig-Navarro, Javier; Mehdi, Syed Bilal

2015-01-01

With the anticipated explosion of small unmanned aerial vehicles, it is highly likely that operators will be controlling fleets of autonomous vehicles. To fulfill the promise of autonomy, vehicle operators will not be concerned with manual control of the vehicle; instead, they will deal with the overall mission. Furthermore, the one operator to many vehicles is becoming a constant meme with various industries including package delivery, search and rescue, and utility companies. In order for an operator to concurrently control several vehicles, his station must look and behave very differently than the current ground control station instantiations. Furthermore, the vehicle will have to be much more autonomous, especially during non-normal operations, in order to accommodate the knowledge deficit or the information overload of the operator in charge of several vehicles. The expected usage increase of small drones requires presenting the operational information generated by a fleet of heterogeneous autonomous agents to an operator. NASA Langley Research Center's Autonomy Incubator has brought together researchers in various disciplines including controls, trajectory planning, systems engineering, and human factors to develop an integrated system to study autonomy issues. The initial human factors effort is focusing on mission displays that would give an operator the overall status of all autonomous agents involved in the current mission. This paper will discuss the specifics of the mission displays for operators controlling several vehicles.

A Multifunctional Coating for Autonomous Corrosion Control

NASA Technical Reports Server (NTRS)

Calle, Luz M.; Li, Wenyan; Buhrow, Jerry W.; Jolley, Scott t.

2011-01-01

Nearly all metals and their alloys are subject to corrosion that causes them to lose their structural integrity or other critical functionality. Protective coatings are the most commonly used method of corrosion control. However, progressively stricter environmental regulations have resulted in the ban of many commercially available corrosion protective coatings due to the harmful effects of their solvents or corrosion inhibitors. This work concerns the development of a multifunctional smart coating for the autonomous control of corrosion. This coating is being developed to have the inherent ability to detect the chemical changes associated with the onset of corrosion and respond autonomously to indicate it and control it. The multi-functionality of the coating is based on microencapsulation technology specifically designed for corrosion control applications. This design has, in addition to all the advantages of existing microcapsulation designs, the corrosion controlled release function that triggers the delivery of corrosion indicators and inhibitors on demand, only when and where needed. Microencapsulation of self-healing agents for autonomous repair of mechanical damage to the coating is also being pursued. Corrosion indicators, corrosion inhibitors, as well as self-healing agents, have been encapsulated and dispersed into several paint systems to test the corrosion detection, inhibition, and self-healing properties of the coating. Key words: Corrosion, coating, autonomous corrosion control, corrosion indication, corrosion inhibition, self-healing coating, smart coating, multifunctional coating, microencapsulation.

Autonomic Healing of Low-Velocity Impact Damage in Fiber-Reinforced Composites

DTIC Science & Technology

2010-01-01

formaldehyde) microencapsulation using the method described by Brown et al. [37]. Two different size ranges of microcapsules were employed to promote even...agent. The components for self-healing, urea–formaldehyde microcapsules containing dicyclopentadiene (DCPD) liquid healing agent and paraffin wax...impact damage is the employment of self-healing materials. In particular, the strat- egy using microencapsulated healing agent, demonstrated by White

Influence of government controls over the currency exchange rate in the evolution of Hurst's exponent: An autonomous agent-based model

NASA Astrophysics Data System (ADS)

Chávez Muñoz, Pablo; Fernandes da Silva, Marcus; Vivas Miranda, José; Claro, Francisco; Gomez Diniz, Raimundo

2007-12-01

We have studied the performance of the Hurst's index associated with the currency exchange rate in Brazil and Chile. It is shown that this index maps the degree of government control in the exchange rate. A model of supply and demand based in an autonomous agent is proposed, that simulates a virtual market of sale and purchase, where buyer or seller are forced to negotiate through an intermediary. According to this model, the average of the price of daily transactions correspond to the theoretical balance proposed by the law of supply and demand. The influence of an added tendency factor is also analyzed.

Expressing Intervals in Automated Service Negotiation

NASA Astrophysics Data System (ADS)

Clark, Kassidy P.; Warnier, Martijn; van Splunter, Sander; Brazier, Frances M. T.

During automated negotiation of services between autonomous agents, utility functions are used to evaluate the terms of negotiation. These terms often include intervals of values which are prone to misinterpretation. It is often unclear if an interval embodies a continuum of real numbers or a subset of natural numbers. Furthermore, it is often unclear if an agent is expected to choose only one value, multiple values, a sub-interval or even multiple sub-intervals. Additional semantics are needed to clarify these issues. Normally, these semantics are stored in a domain ontology. However, ontologies are typically domain specific and static in nature. For dynamic environments, in which autonomous agents negotiate resources whose attributes and relationships change rapidly, semantics should be made explicit in the service negotiation. This paper identifies issues that are prone to misinterpretation and proposes a notation for expressing intervals. This notation is illustrated using an example in WS-Agreement.

Constructing Game Agents from Video of Human Behavior

DTIC Science & Technology

2009-01-01

Future Work Constructing autonomous agents is an important task in video game development. Games such as Quake, Warcraft III, and Halo 2 (Damian 2005...Vision. Rio de Janeiro, Brazil: IEEE Press. Kelley, J. P.; Botea, A.; and Koenig, S. 2008. Offline planning with hierarchical task networks in video ...

Application of Grazing-Inspired Guidance Laws to Autonomous Information Gathering

DTIC Science & Technology

2014-09-01

paths by expressing it as the Selective Traveling Salesman Problem subject to dynamic constraints. Tisdale et al. [11] utilized a receding horizon ap...vehicle failures by halving the initial fuel level on selected agents. Note that simulations start with agents 50s travel time away from where they

Autonomous Agents on Expedition: Humans and Progenitor Ants and Planetary Exploration

NASA Astrophysics Data System (ADS)

Rilee, M. L.; Clark, P. E.; Curtis, S. A.; Truszkowski, W. F.

2002-01-01

The Autonomous Nano-Technology Swarm (ANTS) is an advanced mission architecture based on a social insect analog of many specialized spacecraft working together to achieve mission goals. The principal mission concept driving the ANTS architecture is a Main Belt Asteroid Survey in the 2020s that will involve a thousand or more nano-technology enabled, artificially intelligent, autonomous pico-spacecraft (< 1 kg). The objective of this survey is to construct a compendium of composition, shape, and other physical parameter observations of a significant fraction of asteroid belt objects. Such an atlas will be of primary scientific importance for the understanding of Solar System origins and evolution and will lay the foundation for future exploration and capitalization of space. As the capabilities enabling ANTS are developed over the next two decades, these capabilities will need to be proven. Natural milestones for this process include the deployment of progenitors to ANTS on human expeditions to space and remote missions with interfaces for human interaction and control. These progenitors can show up in a variety of forms ranging from spacecraft subsystems and advanced handheld sensors, through complete prototypical ANTS spacecraft. A critical capability to be demonstrated is reliable, long-term autonomous operations across the ANTS architecture. High level, mission-oriented behaviors are to be managed by a control / communications layer of the swarm, whereas common low level functions required of all spacecraft, e.g. attitude control and guidance and navigation, are handled autonomically on each spacecraft. At the higher levels of mission planning and social interaction deliberative techniques are to be used. For the asteroid survey, ANTS acts as a large community of cooperative agents while for precursor missions there arises the intriguing possibility of Progenitor ANTS and humans acting together as agents. For optimal efficiency and responsiveness for individual spacecraft at the lowest levels of control we have been studying control methods based on nonlinear dynamical systems. We describe the critically important autonomous control architecture of the ANTS mission concept and a sequence of partial implementations that feature increasingly autonomous behaviors. The scientific and engineering roles that these Progenitor ANTS could play in human missions or remote missions with near real time human interactions, particularly to the Moon and Mars, will be discussed.

Increasing Mission Science Return Through Use of Spacecraft Autonomy and Sensor Webs: A Volcanology Example

NASA Astrophysics Data System (ADS)

Davies, A. G.; Chien, S. A.; Castano, R.; Tran, D. Q.; Scharenbroich, L. J.

2006-12-01

Mission science return is increased through use of onboard autonomy, and using disparate assets integrated into an autonomously-operating sensor web that can re-task these assets to rapidly obtain additional data. Software on spacecraft has been used to analyse data to detect dynamic events of high interest, such as on- going volcanic activity. This capability has been successfully demonstrated by the NASA New Millennium Program Autonomous Sciencecraft Experiment (ASE), on the Earth Observing 1 spacecraft in Earth-orbit [1-2]. The potential now exists for eruption parameters to be quantified onboard a spacecraft, using models that relate thermal emission to volumetric eruption rate. This promises a notification not only of on-going activity, but also the magnitude of the event, within a few hours of the original observation, a process that normally takes weeks. ASE/EO-1 is part of the JPL Volcano Sensor Web [3]. This autonomous system collates information of volcanic activity from numerous assets and retasks EO-1 to obtain observations as soon as practicable. The use of a ground-based planner allows rapid insertion or replacement of new observations, with no human intervention. Endusers are notified automatically by email. Spacecraft autonomy, involving automatic fault detection and mitigation, onboard processing of data, and replanning of observations, allows mission operations to break free from pre-ordained operations sequencing, necessary for studying dynamic volcanic processes on other bodies in the Solar System (e.g., Io and Enceladus). Onboard processing allows quantification of dynamic processes, improving both science content per returned byte and optimization of subsequent resource use. This work was carried out at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA. [1] Chien, S. et al. (2004) The EO-1 Autonomous Science Agent, Proceedings of the 2004 Conferences on Autonomous Agents and Multi-agent Systems (AAMAS), New York City, USA, July 2004. [2] Davies, A. G. et al. (2006) Monitoring active volcanism with the Autonomous Sciencecraft Experiment (ASE) on EO-1, RSE, 101, 427-446. [3] Davies, A. G. et al., (2006) Sensor Web enables rapid response to volcanic activity, Eos, 87, 1, 1&5.

Autonomous microfluidic sample preparation system for protein profile-based detection of aerosolized bacterial cells and spores.

PubMed

Stachowiak, Jeanne C; Shugard, Erin E; Mosier, Bruce P; Renzi, Ronald F; Caton, Pamela F; Ferko, Scott M; Van de Vreugde, James L; Yee, Daniel D; Haroldsen, Brent L; VanderNoot, Victoria A

2007-08-01

For domestic and military security, an autonomous system capable of continuously monitoring for airborne biothreat agents is necessary. At present, no system meets the requirements for size, speed, sensitivity, and selectivity to warn against and lead to the prevention of infection in field settings. We present a fully automated system for the detection of aerosolized bacterial biothreat agents such as Bacillus subtilis (surrogate for Bacillus anthracis) based on protein profiling by chip gel electrophoresis coupled with a microfluidic sample preparation system. Protein profiling has previously been demonstrated to differentiate between bacterial organisms. With the goal of reducing response time, multiple microfluidic component modules, including aerosol collection via a commercially available collector, concentration, thermochemical lysis, size exclusion chromatography, fluorescent labeling, and chip gel electrophoresis were integrated together to create an autonomous collection/sample preparation/analysis system. The cycle time for sample preparation was approximately 5 min, while total cycle time, including chip gel electrophoresis, was approximately 10 min. Sensitivity of the coupled system for the detection of B. subtilis spores was 16 agent-containing particles per liter of air, based on samples that were prepared to simulate those collected by wetted cyclone aerosol collector of approximately 80% efficiency operating for 7 min.

Resource allocation and supervisory control architecture for intelligent behavior generation

NASA Astrophysics Data System (ADS)

Shah, Hitesh K.; Bahl, Vikas; Moore, Kevin L.; Flann, Nicholas S.; Martin, Jason

2003-09-01

In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) was funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). As part of our research, we presented the use of a grammar-based approach to enabling intelligent behaviors in autonomous robotic vehicles. With the growth of the number of available resources on the robot, the variety of the generated behaviors and the need for parallel execution of multiple behaviors to achieve reaction also grew. As continuation of our past efforts, in this paper, we discuss the parallel execution of behaviors and the management of utilized resources. In our approach, available resources are wrapped with a layer (termed services) that synchronizes and serializes access to the underlying resources. The controlling agents (called behavior generating agents) generate behaviors to be executed via these services. The agents are prioritized and then, based on their priority and the availability of requested services, the Control Supervisor decides on a winner for the grant of access to services. Though the architecture is applicable to a variety of autonomous vehicles, we discuss its application on T4, a mid-sized autonomous vehicle developed for security applications.

Autonomous and Autonomic Systems: A Paradigm for Future Space Exploration Missions

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Hinchey, Michael G.; Rash, James L.; Rouff, Christopher A.

2004-01-01

NASA increasingly will rely on autonomous systems concepts, not only in the mission control centers on the ground, but also on spacecraft and on rovers and other assets on extraterrestrial bodies. Automomy enables not only reduced operations costs, But also adaptable goal-driven functionality of mission systems. Space missions lacking autonomy will be unable to achieve the full range of advanced mission objectives, given that human control under dynamic environmental conditions will not be feasible due, in part, to the unavoidably high signal propagation latency and constrained data rates of mission communications links. While autonomy cost-effectively supports accomplishment of mission goals, autonomicity supports survivability of remote mission assets, especially when human tending is not feasible. Autonomic system properties (which ensure self-configuring, self-optimizing self-healing, and self-protecting behavior) conceptually may enable space missions of a higher order into any previously flown. Analysis of two NASA agent-based systems previously prototyped, and of a proposed future mission involving numerous cooperating spacecraft, illustrates how autonomous and autonomic system concepts may be brought to bear on future space missions.

Engineering Sensorial Delay to Control Phototaxis and Emergent Collective Behaviors

NASA Astrophysics Data System (ADS)

Mijalkov, Mite; McDaniel, Austin; Wehr, Jan; Volpe, Giovanni

2016-01-01

Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors from simple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.

Multirobot autonomous landmine detection using distributed multisensor information aggregation

NASA Astrophysics Data System (ADS)

Jumadinova, Janyl; Dasgupta, Prithviraj

2012-06-01

We consider the problem of distributed sensor information fusion by multiple autonomous robots within the context of landmine detection. We assume that different landmines can be composed of different types of material and robots are equipped with different types of sensors, while each robot has only one type of landmine detection sensor on it. We introduce a novel technique that uses a market-based information aggregation mechanism called a prediction market. Each robot is provided with a software agent that uses sensory input of the robot and performs calculations of the prediction market technique. The result of the agent's calculations is a 'belief' representing the confidence of the agent in identifying the object as a landmine. The beliefs from different robots are aggregated by the market mechanism and passed on to a decision maker agent. The decision maker agent uses this aggregate belief information about a potential landmine and makes decisions about which other robots should be deployed to its location, so that the landmine can be confirmed rapidly and accurately. Our experimental results show that, for identical data distributions and settings, using our prediction market-based information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques.

Software for Automation of Real-Time Agents, Version 2

NASA Technical Reports Server (NTRS)

Fisher, Forest; Estlin, Tara; Gaines, Daniel; Schaffer, Steve; Chouinard, Caroline; Engelhardt, Barbara; Wilklow, Colette; Mutz, Darren; Knight, Russell; Rabideau, Gregg;

Situation awareness-based agent transparency for human-autonomy teaming effectiveness

NASA Astrophysics Data System (ADS)

Chen, Jessie Y. C.; Barnes, Michael J.; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan G.

2017-05-01

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators' situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators' task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

Nonuniform Deployment of Autonomous Agents in Harbor-Like Environments

DTIC Science & Technology

2014-11-12

ith agent than to all other agents. Interested readers are referred to [55] for the comprehensive study on Voronoi partitioning and its applications...robots: An rfid approach, PhD dissertation, School of Electrical Engi- neering and Computer Science, University of Ottawa (October 2012). [55] A. Okabe, B...Gueaieb, A stochastic approach of mobile robot navigation using customized rfid sys- tems, International Conference on Signals, Circuits and Systems

Modeling Interactive Intelligences

DTIC Science & Technology

2002-08-01

given a task in an uncertain environment? How can we design it with that type of intelligence? How do we gauge the ludic capabilities of an agent? The...for play, unless they are playgrounds or have been designated as toys. Our non-artistic creations come with built-in purposes. Deviations from expected...uses are usually not welcomed. How could play enter into autonomous agent design ? What enhancement of the agent could it bring about? To think

Autonomy and the akratic patient.

PubMed Central

McKnight, C J

1993-01-01

I argue that the distinction which is current in much writing on medical ethics between autonomous and non-autonomous patients cannot cope comfortably with weak-willed (incontinent) patients. I describe a case involving a patient who refuses a blood transfusion even though he or she agrees that it would be in his or her best interests. The case is discussed in the light of the treatment of autonomy by B Brody and R Gillon. These writers appear to force us to treat an incontinent patient either as autonomous, just like a rational agent whose decisions are in accordance with his beliefs or as non-autonomous, like comatose patients or children. Though neither is entirely satisfactory I opt for describing such patients as autonomous but point out that in cases like this the principle of respect for autonomy does not give a determinate answer about how the patient ought to be treated. PMID:8308874

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Human-Centered Design for the Personal Satellite Assistant

NASA Technical Reports Server (NTRS)

Bradshaw, Jeffrey M.; Sierhuis, Maarten; Gawdiak, Yuri; Thomas, Hans; Greaves, Mark; Clancey, William J.; Swanson, Keith (Technical Monitor)

2000-01-01

The Personal Satellite Assistant (PSA) is a softball-sized flying robot designed to operate autonomously onboard manned spacecraft in pressurized micro-gravity environments. We describe how the Brahms multi-agent modeling and simulation environment in conjunction with a KAoS agent teamwork approach can be used to support human-centered design for the PSA.

Self-organizing team formation for target observation

NASA Astrophysics Data System (ADS)

Bowyer, Richard S.; Bogner, Robert E.

2001-08-01

Target observation is a problem where the application of multiple sensors can improve the probability of detection and observation of the target. Team formation is one method by which seemingly unsophisticated heterogeneous sensors may be organized to achieve a coordinated observation system. The sensors, which we shall refer to as agents, are situated in an area of interest with the goal of observing a moving target. We apply a team approach to this problem, which combines the strengths of individual agents into a cohesive entity - the team. In autonomous systems, the mechanisms that underlie the formation of a team are of interest. Teams may be formed by various mechanisms, which include an externally imposed grouping of agents, or an internally, self-organized (SO) grouping of agents. Internally motivated mechanisms are particularly challenging, but offer the benefit of being unsupervised, an important quality for groups of autonomous cooperating machines. This is the focus of our research. By studying natural systems such as colonies of ants, we obtain insight into these mechanisms of self organization. We propose that the team is an expression of a distributed agent-self, and that a particular realization of the agent-self exists, whilst the environmental conditions are conducive to that existence. We describe an algorithms for agent team formation that is inspired by the self-organizing behavior of ants, and describe simulation results for team formation amongst a lattice of networked sensors.

Autonomic and Coevolutionary Sensor Networking

NASA Astrophysics Data System (ADS)

Boonma, Pruet; Suzuki, Junichi

(WSNs) applications are often required to balance the tradeoffs among conflicting operational objectives (e.g., latency and power consumption) and operate at an optimal tradeoff. This chapter proposes and evaluates a architecture, called BiSNET/e, which allows WSN applications to overcome this issue. BiSNET/e is designed to support three major types of WSN applications: , and hybrid applications. Each application is implemented as a decentralized group of, which is analogous to a bee colony (application) consisting of bees (agents). Agents collect sensor data or detect an event (a significant change in sensor reading) on individual nodes, and carry sensor data to base stations. They perform these data collection and event detection functionalities by sensing their surrounding network conditions and adaptively invoking behaviors such as pheromone emission, reproduction, migration, swarming and death. Each agent has its own behavior policy, as a set of genes, which defines how to invoke its behaviors. BiSNET/e allows agents to evolve their behavior policies (genes) across generations and autonomously adapt their performance to given objectives. Simulation results demonstrate that, in all three types of applications, agents evolve to find optimal tradeoffs among conflicting objectives and adapt to dynamic network conditions such as traffic fluctuations and node failures/additions. Simulation results also illustrate that, in hybrid applications, data collection agents and event detection agents coevolve to augment their adaptability and performance.

Agent Architectures for Compliance

NASA Astrophysics Data System (ADS)

Burgemeestre, Brigitte; Hulstijn, Joris; Tan, Yao-Hua

A Normative Multi-Agent System consists of autonomous agents who must comply with social norms. Different kinds of norms make different assumptions about the cognitive architecture of the agents. For example, a principle-based norm assumes that agents can reflect upon the consequences of their actions; a rule-based formulation only assumes that agents can avoid violations. In this paper we present several cognitive agent architectures for self-monitoring and compliance. We show how different assumptions about the cognitive architecture lead to different information needs when assessing compliance. The approach is validated with a case study of horizontal monitoring, an approach to corporate tax auditing recently introduced by the Dutch Customs and Tax Authority.

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

Reusable Autonomy

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Obenschain, Arthur F. (Technical Monitor)

2002-01-01

Currently, spacecraft ground systems have a well defined and somewhat standard architecture and operations concept. Based on domain analysis studies of various control centers conducted over the years it is clear that ground systems have core capabilities and functionality that are common across all ground systems. This observation alone supports the realization of reuse. Additionally, spacecraft ground systems are increasing in their ability to do things autonomously. They are being engineered using advanced expert systems technology to provide automated support for operators. A clearer understanding of the possible roles of agent technology is advancing the prospects of greater autonomy for these systems. Many of their functional and management tasks are or could be supported by applied agent technology, the dynamics of the ground system's infrastructure could be monitored by agents, there are intelligent agent-based approaches to user-interfaces, etc. The premise of this paper is that the concepts associated with software reuse, applicable in consideration of classically-engineered ground systems, can be updated to address their application in highly agent-based realizations of future ground systems. As a somewhat simplified example consider the following situation, involving human agents in a ground system context. Let Group A of controllers be working on Mission X. They are responsible for the command, control and health and safety of the Mission X spacecraft. Let us suppose that mission X successfully completes it mission and is turned off. Group A could be dispersed or perhaps move to another Mission Y. In this case there would be reuse of the human agents from Mission X to Mission Y. The Group A agents perform their well-understood functions in a somewhat but related context. There will be a learning or familiarization process that the group A agents go through to make the new context, determined by the new Mission Y, understood. This simplified scenario highlights some of the major issues that need to be addressed when considering the situation where Group A is composed of software-based agents (not their human counterparts) and they migrate from one mission support system to another. This paper will address: - definition of an agent architecture appropriate to support reuse; - identification of non-mission-specific agent capabilities required; - appropriate knowledge representation schemes for mission-specific knowledge; - agent interface with mission-specific knowledge (a type of Learning); development of a fully-operational group of cooperative software agents for ground system support; architecture and operation of a repository of reusable agents that could be the source of intelligent components for realizing an autonomous (or nearly autonomous) agent-based ground system, and an agent-based approach to repository management and operation (an intelligent interface for human use of the repository in a ground-system development activity).

The autonomous sciencecraft constellations

NASA Technical Reports Server (NTRS)

Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

2003-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

We Care about You: Incorporating Pet Characteristics with Educational Agents through Reciprocal Caring Approach

ERIC Educational Resources Information Center

Chen, Zhi-Hong

2012-01-01

Although different educational agents have been proposed to facilitate student learning, most of them operate from a "smart" (i.e., intelligent and autonomous) perspective. Recently, a so-called "non-smart" perspective is also attracting increasing interest, and is now regarded as a topic worthwhile of researching. To this end,…

An Autonomous Mobile Agent-Based Distributed Learning Architecture: A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

Current distance learning systems are increasingly packing highly data-intensive contents on servers, resulting in the congestion of network and server resources at peak service times. A distributed learning system based on faded information field (FIF) architecture that employs mobile agents (MAs) has been proposed and simulated in this work. The…

Solving Autonomy Technology Gaps through Wireless Technology and Orion Avionics Architectural Principles

NASA Astrophysics Data System (ADS)

Black, Randy; Bai, Haowei; Michalicek, Andrew; Shelton, Blaine; Villela, Mark

2008-01-01

Currently, autonomy in space applications is limited by a variety of technology gaps. Innovative application of wireless technology and avionics architectural principles drawn from the Orion crew exploration vehicle provide solutions for several of these gaps. The Vision for Space Exploration envisions extensive use of autonomous systems. Economic realities preclude continuing the level of operator support currently required of autonomous systems in space. In order to decrease the number of operators, more autonomy must be afforded to automated systems. However, certification authorities have been notoriously reluctant to certify autonomous software in the presence of humans or when costly missions may be jeopardized. The Orion avionics architecture, drawn from advanced commercial aircraft avionics, is based upon several architectural principles including partitioning in software. Robust software partitioning provides "brick wall" separation between software applications executing on a single processor, along with controlled data movement between applications. Taking advantage of these attributes, non-deterministic applications can be placed in one partition and a "Safety" application created in a separate partition. This "Safety" partition can track the position of astronauts or critical equipment and prevent any unsafe command from executing. Only the Safety partition need be certified to a human rated level. As a proof-of-concept demonstration, Honeywell has teamed with the Ultra WideBand (UWB) Working Group at NASA Johnson Space Center to provide tracking of humans, autonomous systems, and critical equipment. Using UWB the NASA team can determine positioning to within less than one inch resolution, allowing a Safety partition to halt operation of autonomous systems in the event that an unplanned collision is imminent. Another challenge facing autonomous systems is the coordination of multiple autonomous agents. Current approaches address the issue as one of networking and coordination of multiple independent units, each with its own mission. As a proof-of-concept Honeywell is developing and testing various algorithms that lead to a deterministic, fault tolerant, reliable wireless backplane. Just as advanced avionics systems control several subsystems, actuators, sensors, displays, etc.; a single "master" autonomous agent (or base station computer) could control multiple autonomous systems. The problem is simplified to controlling a flexible body consisting of several sensors and actuators, rather than one of coordinating multiple independent units. By filling technology gaps associated with space based autonomous system, wireless technology and Orion architectural principles provide the means for decreasing operational costs and simplifying problems associated with collaboration of multiple autonomous systems.

Goal striving within agentic and communal roles: separate but functionally similar pathways to enhanced well-being.

PubMed

Sheldon, Kennon M; Cooper, M Lynne

2008-06-01

Do agency and communion strivings provide functionally similar but predictively independent pathways to enhanced well-being? We tested this idea via a year-long study of 493 diverse community adults. Our process model, based on self-determination and motive disposition theories, fit the data well. First, the need for achievement predicted initial autonomous motivation for agentic (work and school) role-goals and the need for intimacy predicted felt autonomy for communal (relationship and parenting) goals. For both agentic and communal goals, autonomous motivation predicted corresponding initial expectancies that predicted later goal attainment. Finally, each type of attainment predicted improved adjustment or role-satisfaction over the year. Besides being similar across agency and communion, the model was also similar across race and gender, except that the beneficial effects of communal goal attainment were stronger for high need for intimacy women and Blacks. Implications for agency/communion theories, motivation theories, and theories of well-being are discussed.

Promoting motivation with virtual agents and avatars: role of visual presence and appearance.

PubMed

Baylor, Amy L

2009-12-12

Anthropomorphic virtual agents can serve as powerful technological mediators to impact motivational outcomes such as self-efficacy and attitude change. Such anthropomorphic agents can be designed as simulated social models in the Bandurian sense, providing social influence as virtual 'role models'. Of particular value is the capacity for designing such agents as optimized social models for a target audience and context. Importantly, the visual presence and appearance of such agents can have a major impact on motivation and affect regardless of the underlying technical sophistication. Empirical results of different instantiations of agent presence and appearance are reviewed for both autonomous virtual agents and avatars that represent a user.

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

NASA Technical Reports Server (NTRS)

Tran, Loc; Cross, Charles; Montague, Gilbert; Motter, Mark; Neilan, James; Qualls, Garry; Rothhaar, Paul; Trujillo, Anna; Allen, B. Danette

2015-01-01

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Agent Based Intelligence in a Tetrahedral Rover

NASA Technical Reports Server (NTRS)

Phelps, Peter; Truszkowski, Walt

2007-01-01

A tetrahedron is a 4-node 6-strut pyramid structure which is being used by the NASA - Goddard Space Flight Center as the basic building block for a new approach to robotic motion. The struts are extendable; it is by the sequence of activities: strut-extension, changing the center of gravity and falling that the tetrahedron "moves". Currently, strut-extension is handled by human remote control. There is an effort underway to make the movement of the tetrahedron autonomous, driven by an attempt to achieve a goal. The approach being taken is to associate an intelligent agent with each node. Thus, the autonomous tetrahedron is realized as a constrained multi-agent system, where the constraints arise from the fact that between any two agents there is an extendible strut. The hypothesis of this work is that, by proper composition of such automated tetrahedra, robotic structures of various levels of complexity can be developed which will support more complex dynamic motions. This is the basis of the new approach to robotic motion which is under investigation. A Java-based simulator for the single tetrahedron, realized as a constrained multi-agent system, has been developed and evaluated. This paper reports on this project and presents a discussion of the structure and dynamics of the simulator.

Model-Unified Planning and Execution for Distributed Autonomous System Control

NASA Technical Reports Server (NTRS)

Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

2006-01-01

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Ribbon networks for modeling navigable paths of autonomous agents in virtual environments.

PubMed

Willemsen, Peter; Kearney, Joseph K; Wang, Hongling

2006-01-01

This paper presents the Environment Description Framework (EDF) for modeling complex networks of intersecting roads and pathways in virtual environments. EDF represents information about the layout of streets and sidewalks, the rules that govern behavior on roads and walkways, and the locations of agents with respect to navigable structures. The framework serves as the substrate on which behavior programs for autonomous vehicles and pedestrians are built. Pathways are modeled as ribbons in space. The ribbon structure provides a natural coordinate frame for defining the local geometry of navigable surfaces. EDF includes a powerful runtime interface supported by robust and efficient code for locating objects on the ribbon network, for mapping between Cartesian and ribbon coordinates, and for determining behavioral constraints imposed by the environment.

Intelligent Agent Appropriation in the Tracking Phase of an Environmental Scanning Process: A Case Study of a French Trade Union

ERIC Educational Resources Information Center

Lafaye, Christophe

2009-01-01

Introduction: The rapid growth of the Internet has modified the boundaries of information acquisition (tracking) in environmental scanning. Despite the numerous advantages of this new medium, information overload is an enormous problem for Internet scanners. In order to help them, intelligent agents (i.e., autonomous, automated software agents…

Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication

DTIC Science & Technology

2005-01-01

system (PMFserv) that implements human behavior models from a range of ability, stress, emotion , decision theoretic and motivation sources. An...autonomous agents, human behavior models, culture and emotions 1. Introduction There are many applications of computer animation and simulation where...We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors

An agent-based peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises

NASA Astrophysics Data System (ADS)

Zhang, Wenyu; Zhang, Shuai; Cai, Ming; Jian, Wu

2015-04-01

With the development of virtual enterprise (VE) paradigm, the usage of serviceoriented architecture (SOA) is increasingly being considered for facilitating the integration and utilisation of distributed manufacturing resources. However, due to the heterogeneous nature among VEs, the dynamic nature of a VE and the autonomous nature of each VE member, the lack of both sophisticated coordination mechanism in the popular centralised infrastructure and semantic expressivity in the existing SOA standards make the current centralised, syntactic service discovery method undesirable. This motivates the proposed agent-based peer-to-peer (P2P) architecture for semantic discovery of manufacturing services across VEs. Multi-agent technology provides autonomous and flexible problemsolving capabilities in dynamic and adaptive VE environments. Peer-to-peer overlay provides highly scalable coupling across decentralised VEs, each of which exhibiting as a peer composed of multiple agents dealing with manufacturing services. The proposed architecture utilises a novel, efficient, two-stage search strategy - semantic peer discovery and semantic service discovery - to handle the complex searches of manufacturing services across VEs through fast peer filtering. The operation and experimental evaluation of the prototype system are presented to validate the implementation of the proposed approach.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Agent-based approach for generation of a money-centered star network

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

2008-09-01

The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

Multi-agent systems design for aerospace applications

NASA Astrophysics Data System (ADS)

Waslander, Steven L.

2007-12-01

Engineering systems with independent decision makers are becoming increasingly prevalent and present many challenges in coordinating actions to achieve systems goals. In particular, this work investigates the applications of air traffic flow control and autonomous vehicles as motivation to define algorithms that allow agents to agree to safe, efficient and equitable solutions in a distributed manner. To ensure system requirements will be satisfied in practice, each method is evaluated for a specific model of agent behavior, be it cooperative or non-cooperative. The air traffic flow control problem is investigated from the point of view of the airlines, whose costs are directly affected by resource allocation decisions made by the Federal Aviation Administration in order to mitigate traffic disruptions caused by weather. Airlines are first modeled as cooperative, and a distributed algorithm is presented with various global cost metrics which balance efficient and equitable use of resources differently. Next, a competitive airline model is assumed and two market mechanisms are developed for allocating contested airspace resources. The resource market mechanism provides a solution for which convergence to an efficient solution can be guaranteed, and each airline will improve on the solution that would occur without its inclusion in the decision process. A lump-sum market is then introduced as an alternative mechanism, for which efficiency loss bounds exist if airlines attempt to manipulate prices. Initial convergence results for lump-sum markets are presented for simplified problems with a single resource. To validate these algorithms, two air traffic flow models are developed which extend previous techniques, the first a convenient convex model made possible by assuming constant velocity flow, and the second a more complex flow model with full inflow, velocity and rerouting control. Autonomous vehicle teams are envisaged for many applications including mobile sensing and search and rescue. To enable these high-level applications, multi-vehicle collision avoidance is solved using a cooperative, decentralized algorithm. For the development of coordination algorithms for autonomous vehicles, the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) is presented. This testbed provides significant advantages over other aerial testbeds due to its small size and low maintenance requirements.

Delay-dependent coupling for a multi-agent LTI consensus system with inter-agent delays

NASA Astrophysics Data System (ADS)

Qiao, Wei; Sipahi, Rifat

2014-01-01

Delay-dependent coupling (DDC) is considered in this paper in a broadly studied linear time-invariant multi-agent consensus system in which agents communicate with each other under homogeneous delays, while attempting to reach consensus. The coupling among the agents is designed here as an explicit parameter of this delay, allowing couplings to autonomously adapt based on the delay value, and in order to guarantee stability and a certain degree of robustness in the network despite the destabilizing effect of delay. Design procedures, analysis of convergence speed of consensus, comprehensive numerical studies for the case of time-varying delay, and limitations are presented.

Control Architecture for Robotic Agent Command and Sensing

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand; Estlin, Tara; Gaines, Daniel

2008-01-01

Control Architecture for Robotic Agent Command and Sensing (CARACaS) is a recent product of a continuing effort to develop architectures for controlling either a single autonomous robotic vehicle or multiple cooperating but otherwise autonomous robotic vehicles. CARACaS is potentially applicable to diverse robotic systems that could include aircraft, spacecraft, ground vehicles, surface water vessels, and/or underwater vessels. CARACaS incudes an integral combination of three coupled agents: a dynamic planning engine, a behavior engine, and a perception engine. The perception and dynamic planning en - gines are also coupled with a memory in the form of a world model. CARACaS is intended to satisfy the need for two major capabilities essential for proper functioning of an autonomous robotic system: a capability for deterministic reaction to unanticipated occurrences and a capability for re-planning in the face of changing goals, conditions, or resources. The behavior engine incorporates the multi-agent control architecture, called CAMPOUT, described in An Architecture for Controlling Multiple Robots (NPO-30345), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 65. CAMPOUT is used to develop behavior-composition and -coordination mechanisms. Real-time process algebra operators are used to compose a behavior network for any given mission scenario. These operators afford a capability for producing a formally correct kernel of behaviors that guarantee predictable performance. By use of a method based on multi-objective decision theory (MODT), recommendations from multiple behaviors are combined to form a set of control actions that represents their consensus. In this approach, all behaviors contribute simultaneously to the control of the robotic system in a cooperative rather than a competitive manner. This approach guarantees a solution that is good enough with respect to resolution of complex, possibly conflicting goals within the constraints of the mission to be accomplished by the vehicle(s).

Modeling of a production system using the multi-agent approach

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Sękala, A.; Banaś, W.

2017-08-01

The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the other type of agent that are utilized in the described simulation. The article presents the idea of an integrated program approach and shows the resulting production layout as a virtual model. This model was developed in the NetLogo multi-agent program environment.

Virtual agents in a simulated virtual training environment

NASA Technical Reports Server (NTRS)

Achorn, Brett; Badler, Norman L.

1993-01-01

A drawback to live-action training simulations is the need to gather a large group of participants in order to train a few individuals. One solution to this difficulty is the use of computer-controlled agents in a virtual training environment. This allows a human participant to be replaced by a virtual, or simulated, agent when only limited responses are needed. Each agent possesses a specified set of behaviors and is capable of limited autonomous action in response to its environment or the direction of a human trainee. The paper describes these agents in the context of a simulated hostage rescue training session, involving two human rescuers assisted by three virtual (computer-controlled) agents and opposed by three other virtual agents.

Issues Regarding the Future Application of Autonomous Systems to Command and Control (C2)

DTIC Science & Technology

2015-06-01

working with Lockheed Martin to build a fleet of land and air drones to deliver cars and even containers of soldiers[OG13]. 5.3.4 Space Deep Space 1...Orlando Belo. Autonomous forex trading agents. In Petra Perner, editor, Advances in Data Mining. Medical Applications, E- Commerce, Marketing, and...http://pando.com/2013/04/02/ want-to-take-on-wall-street-quantopians-algorithmic-trading- platform-now-accepts-outside-data-sets/. CC05. Martin

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms Project

NASA Technical Reports Server (NTRS)

Falker, John; Zeitlin, Nancy; Leucht, Kurt; Stolleis, Karl

2015-01-01

Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots, called Swarmies, to be used as a ground-based research platform for in-situ resource utilization missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in an unknown environment and return those resources to a central site.

A multi-agent architecture for geosimulation of moving agents

NASA Astrophysics Data System (ADS)

Vahidnia, Mohammad H.; Alesheikh, Ali A.; Alavipanah, Seyed Kazem

2015-10-01

In this paper, a novel architecture is proposed in which an axiomatic derivation system in the form of first-order logic facilitates declarative explanation and spatial reasoning. Simulation of environmental perception and interaction between autonomous agents is designed with a geographic belief-desire-intention and a request-inform-query model. The architecture has a complementary quantitative component that supports collaborative planning based on the concept of equilibrium and game theory. This new architecture presents a departure from current best practices geographic agent-based modelling. Implementation tasks are discussed in some detail, as well as scenarios for fleet management and disaster management.

Where neuroscience and dynamic system theory meet autonomous robotics: a contracting basal ganglia model for action selection.

PubMed

Girard, B; Tabareau, N; Pham, Q C; Berthoz, A; Slotine, J-J

2008-05-01

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.

Human-Vehicle Interface for Semi-Autonomous Operation of Uninhabited Aero Vehicles

NASA Technical Reports Server (NTRS)

Jones, Henry L.; Frew, Eric W.; Woodley, Bruce R.; Rock, Stephen M.

2001-01-01

The robustness of autonomous robotic systems to unanticipated circumstances is typically insufficient for use in the field. The many skills of human user often fill this gap in robotic capability. To incorporate the human into the system, a useful interaction between man and machine must exist. This interaction should enable useful communication to be exchanged in a natural way between human and robot on a variety of levels. This report describes the current human-robot interaction for the Stanford HUMMINGBIRD autonomous helicopter. In particular, the report discusses the elements of the system that enable multiple levels of communication. An intelligent system agent manages the different inputs given to the helicopter. An advanced user interface gives the user and helicopter a method for exchanging useful information. Using this human-robot interaction, the HUMMINGBIRD has carried out various autonomous search, tracking, and retrieval missions.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources.

PubMed

Liu, Yu-Ting; Pal, Nikhil R; Marathe, Amar R; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources

PubMed Central

Liu, Yu-Ting; Pal, Nikhil R.; Marathe, Amar R.; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems. PMID:28676734

Capturing Safety Requirements to Enable Effective Task Allocation Between Humans and Automaton in Increasingly Autonomous Systems

NASA Technical Reports Server (NTRS)

Neogi, Natasha A.

2016-01-01

There is a current drive towards enabling the deployment of increasingly autonomous systems in the National Airspace System (NAS). However, shifting the traditional roles and responsibilities between humans and automation for safety critical tasks must be managed carefully, otherwise the current emergent safety properties of the NAS may be disrupted. In this paper, a verification activity to assess the emergent safety properties of a clearly defined, safety critical, operational scenario that possesses tasks that can be fluidly allocated between human and automated agents is conducted. Task allocation role sets were proposed for a human-automation team performing a contingency maneuver in a reduced crew context. A safety critical contingency procedure (engine out on takeoff) was modeled in the Soar cognitive architecture, then translated into the Hybrid Input Output formalism. Verification activities were then performed to determine whether or not the safety properties held over the increasingly autonomous system. The verification activities lead to the development of several key insights regarding the implicit assumptions on agent capability. It subsequently illustrated the usefulness of task annotations associated with specialized requirements (e.g., communication, timing etc.), and demonstrated the feasibility of this approach.

Miniaturized spectrometer for stand-off chemical detection

NASA Astrophysics Data System (ADS)

Henning, Patrick F.; Chadha, Suneet; Damren, Richard; Rowe, Rebecca C.; Stevenson, Chuck; Curtiss, Lawrence E.; DiGiuseppe, Thomas G.

2002-02-01

Advanced autonomous detection of both chemical warfare agents and toxic industrial chemicals has long been of major military concern and is becoming an increasingly realistic need. Foster-Miller has successfully designed and demonstrated a high spectral throughput monolithic wedge spectrometer capable of providing early, stand-off detection of chemical threats. Recent breakthrough innovations in IR source technologies, high D* multispectral array detectors, and IR waveguide materials has allowed for the development of a robust, miniature, monolithic infrared spectrometer. Foster-Miller recently demonstrated a high resolution spectrometer operating in the 8 to 12 micron region for chemical agent detection. Results will be presented demonstrating the feasibility of adapting the wedge spectrometer to operate as an upward looking ground sensor for stand-off chemical detection. Our miniaturized spectrometer forms the basis for deploying low cost, lightweight sensors which may be used for reconnaissance missions or delivered to remote locations for unattended operation. The ability of perform passive stand-off infrared chemical agent and chemical emissions detection with a low cost, compact device that can operate autonomously in remote environments has broad applications in both the military and commercial marketplace.

Self-healing in single and multiple fiber(s) reinforced polymer composites

NASA Astrophysics Data System (ADS)

Woldesenbet, E.

2010-06-01

You Polymer composites have been attractive medium to introduce the autonomic healing concept into modern day engineering materials. To date, there has been significant research in self-healing polymeric materials including several studies specifically in fiber reinforced polymers. Even though several methods have been suggested in autonomic healing materials, the concept of repair by bleeding of enclosed functional agents has garnered wide attention by the scientific community. A self-healing fiber reinforced polymer composite has been developed. Tensile tests are carried out on specimens that are fabricated by using the following components: hollow and solid glass fibers, healing agent, catalysts, multi-walled carbon nanotubes, and a polymer resin matrix. The test results have demonstrated that single fiber polymer composites and multiple fiber reinforced polymer matrix composites with healing agents and catalysts have provided 90.7% and 76.55% restoration of the original tensile strength, respectively. Incorporation of functionalized multi-walled carbon nanotubes in the healing medium of the single fiber polymer composite has provided additional efficiency. Healing is found to be localized, allowing multiple healing in the presence of several cracks.

Water-driven micromotors for rapid photocatalytic degradation of biological and chemical warfare agents.

PubMed

Li, Jinxing; Singh, Virendra V; Sattayasamitsathit, Sirilak; Orozco, Jahir; Kaufmann, Kevin; Dong, Renfeng; Gao, Wei; Jurado-Sanchez, Beatriz; Fedorak, Yuri; Wang, Joseph

2014-11-25

Threats of chemical and biological warfare agents (CBWA) represent a serious global concern and require rapid and efficient neutralization methods. We present a highly effective micromotor strategy for photocatalytic degradation of CBWA based on light-activated TiO2/Au/Mg microspheres that propel autonomously in natural water and obviate the need for external fuel, decontaminating reagent, or mechanical agitation. The activated TiO2/Au/Mg micromotors generate highly reactive oxygen species responsible for the efficient destruction of the cell membranes of the anthrax simulant Bacillus globigii spore, as well as rapid and complete in situ mineralization of the highly persistent organophosphate nerve agents into nonharmful products. The water-driven propulsion of the TiO2/Au/Mg micromotors facilitates efficient fluid transport and dispersion of the photogenerated reactive oxidative species and their interaction with the CBWA. Coupling of the photocatalytic surface of the micromotors and their autonomous water-driven propulsion thus leads to a reagent-free operation which holds a considerable promise for diverse "green" defense and environmental applications.

Environmentally Friendly Coating Technology for Autonomous Corrosion Control

NASA Technical Reports Server (NTRS)

Calle, Luz M.; Li, Wenyan; Buhrow, Jerry W.; Johnsey, Marissa N.; Jolley, Scott T.; Pearman, Benjamin P.; Zhang, Xuejun; Fitzpatrick, Lilliana; Gillis, Mathew; Blanton, Michael;

Launch Commit Criteria Monitoring Agent

NASA Technical Reports Server (NTRS)

Semmel, Glenn S.; Davis, Steven R.; Leucht, Kurt W.; Rowe, Dan A.; Kelly, Andrew O.; Boeloeni, Ladislau

2005-01-01

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has developed and deployed a software agent to monitor the Space Shuttle's ground processing telemetry stream. The application, the Launch Commit Criteria Monitoring Agent, increases situational awareness for system and hardware engineers during Shuttle launch countdown. The agent provides autonomous monitoring of the telemetry stream, automatically alerts system engineers when predefined criteria have been met, identifies limit warnings and violations of launch commit criteria, aids Shuttle engineers through troubleshooting procedures, and provides additional insight to verify appropriate troubleshooting of problems by contractors. The agent has successfully detected launch commit criteria warnings and violations on a simulated playback data stream. Efficiency and safety are improved through increased automation.

Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; Brooks, Alexander J.-W.; Tarbell, Mark A.; Dohm, James M.

2017-05-01

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C4ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

Effects of Agent Transparency on Multi-Robot Management Effectiveness

DTIC Science & Technology

2015-09-01

capacity was found to be a significant predictor of participants’ trust in the agent. Individual differences in spatial ability accounted for...Another concern regarding autonomous systems is operator workload, which is the cost of performing a task that reduces an individual’s ability to complete...more elaborate and costly strategy that cost additional time (Clark et al. 2011). We hypothesize, therefore, that action GE will be associated with

Emergence of a snake-like structure in mobile distributed agents: an exploratory agent-based modeling approach.

PubMed

Niazi, Muaz A

2014-01-01

The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems.

Emergence of a Snake-Like Structure in Mobile Distributed Agents: An Exploratory Agent-Based Modeling Approach

PubMed Central

Niazi, Muaz A.

2014-01-01

The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems. PMID:24701135

Neutron Radiography Based Visualization and Profiling of Water Uptake in (Un)cracked and Autonomously Healed Cementitious Materials

PubMed Central

Van den Heede, Philip; Van Belleghem, Bjorn; Alderete, Natalia; Van Tittelboom, Kim; De Belie, Nele

2016-01-01

Given their low tensile strength, cement-based materials are very susceptible to cracking. These cracks serve as preferential pathways for corrosion inducing substances. For large concrete infrastructure works, currently available time-consuming manual repair techniques are not always an option. Often, one simply cannot reach the damaged areas and when making those areas accessible anyway (e.g., by redirecting traffic), the economic impacts involved would be enormous. Under those circumstances, it might be useful to have concrete with an embedded autonomous healing mechanism. In this paper, the effectiveness of incorporating encapsulated high and low viscosity polyurethane-based healing agents to ensure (multiple) crack healing has been investigated by means of capillary absorption tests on mortar while monitoring the time-dependent water ingress with neutron radiography. Overall visual interpretation and water front/sample cross-section area ratios as well as water profiles representing the area around the crack and their integrals do not show a preference for the high or low viscosity healing agent. Another observation is that in presence of two cracks, only one is properly healed, especially when using the latter healing agent. Exposure to water immediately after release of the healing agent stimulates the foaming reaction of the polyurethane and ensures a better crack closure. PMID:28773436

Algorithms of walking and stability for an anthropomorphic robot

NASA Astrophysics Data System (ADS)

Sirazetdinov, R. T.; Devaev, V. M.; Nikitina, D. V.; Fadeev, A. Y.; Kamalov, A. R.

2017-09-01

Autonomous movement of an anthropomorphic robot is considered as a superposition of a set of typical elements of movement - so-called patterns, each of which can be considered as an agent of some multi-agent system [ 1 ]. To control the AP-601 robot, an information and communication infrastructure has been created that represents some multi-agent system that allows the development of algorithms for individual patterns of moving and run them in the system as a set of independently executed and interacting agents. The algorithms of lateral movement of the anthropomorphic robot AP-601 series with active stability due to the stability pattern are presented.

Animation of Traffic through Roundabouts

DOT National Transportation Integrated Search

1998-01-14

This report describes work done on a roundabout animation program during 1997. The roundabout animation program began as an undergraduate class project and has evolved to its current state. The program is based on the principle of an autonomous agent...

Coordinating teams of autonomous vehicles: an architectural perspective

NASA Astrophysics Data System (ADS)

Czichon, Cary; Peterson, Robert W.; Mettala, Erik G.; Vondrak, Ivo

2005-05-01

In defense-related robotics research, a mission level integration gap exists between mission tasks (tactical) performed by ground, sea, or air applications and elementary behaviors enacted by processing, communications, sensors, and weaponry resources (platform specific). The gap spans ensemble (heterogeneous team) behaviors, automatic MOE/MOP tracking, and tactical task modeling/simulation for virtual and mixed teams comprised of robotic and human combatants. This study surveys robotic system architectures, compares approaches for navigating problem/state spaces by autonomous systems, describes an architecture for an integrated, repository-based modeling, simulation, and execution environment, and outlines a multi-tiered scheme for robotic behavior components that is agent-based, platform-independent, and extendable via plug-ins. Tools for this integrated environment, along with a distributed agent framework for collaborative task performance are being developed by a U.S. Army funded SBIR project (RDECOM Contract N61339-04-C-0005).

A Face Attention Technique for a Robot Able to Interpret Facial Expressions

NASA Astrophysics Data System (ADS)

Simplício, Carlos; Prado, José; Dias, Jorge

Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.

Muscarine- and carbachol-induced aggressions: fear and irritable kinds of aggressions.

PubMed

Beleslin, D B; Samardzić, R

1977-12-28

In unaneasthetized and unrestrained cats, muscarine and carbachol were injected into the cerebral ventricles. The kind of aggressive behaviour depended on the cholinomimetic drug and was classified as fear and an irritable kind of aggression. Muscarine induced the fear kind of aggression. The aggressive behaviour was usually preceded by attempts to escape and the attack was relevant to the situation. For the attack the presence of some threatening agent was needed. The aggression was accompanied by intense motor but less autonomic activation. On the other hand, carbachol induced an irritable kind of aggression and had the following characteristics: for the attack the presence of some threatening agent was not needed; the attack was not relevant to the situation; the aggression was not preceded by attempts to escape; and the aggressive behaviour was accompanied by intense motor and autonomic activation. It is concluded that cholinoceptive mechanisms are involved in the control of aggressive behaviour.

Advanced Autonomous Systems for Space Operations

NASA Astrophysics Data System (ADS)

Gross, A. R.; Smith, B. D.; Muscettola, N.; Barrett, A.; Mjolssness, E.; Clancy, D. J.

2002-01-01

New missions of exploration and space operations will require unprecedented levels of autonomy to successfully accomplish their objectives. Inherently high levels of complexity, cost, and communication distances will preclude the degree of human involvement common to current and previous space flight missions. With exponentially increasing capabilities of computer hardware and software, including networks and communication systems, a new balance of work is being developed between humans and machines. This new balance holds the promise of not only meeting the greatly increased space exploration requirements, but simultaneously dramatically reducing the design, development, test, and operating costs. New information technologies, which take advantage of knowledge-based software, model-based reasoning, and high performance computer systems, will enable the development of a new generation of design and development tools, schedulers, and vehicle and system health management capabilities. Such tools will provide a degree of machine intelligence and associated autonomy that has previously been unavailable. These capabilities are critical to the future of advanced space operations, since the science and operational requirements specified by such missions, as well as the budgetary constraints will limit the current practice of monitoring and controlling missions by a standing army of ground-based controllers. System autonomy capabilities have made great strides in recent years, for both ground and space flight applications. Autonomous systems have flown on advanced spacecraft, providing new levels of spacecraft capability and mission safety. Such on-board systems operate by utilizing model-based reasoning that provides the capability to work from high-level mission goals, while deriving the detailed system commands internally, rather than having to have such commands transmitted from Earth. This enables missions of such complexity and communication` distances as are not otherwise possible, as well as many more efficient and low cost applications. In addition, utilizing component and system modeling and reasoning capabilities, autonomous systems will play an increasing role in ground operations for space missions, where they will both reduce the human workload as well as provide greater levels of monitoring and system safety. This paper will focus specifically on new and innovative software for remote, autonomous, space systems flight operations. Topics to be presented will include a brief description of key autonomous control concepts, the Remote Agent program that commanded the Deep Space 1 spacecraft to new levels of system autonomy, recent advances in distributed autonomous system capabilities, and concepts for autonomous vehicle health management systems. A brief description of teaming spacecraft and rovers for complex exploration missions will also be provided. New on-board software for autonomous science data acquisition for planetary exploration will be described, as well as advanced systems for safe planetary landings. A new multi-agent architecture that addresses some of the challenges of autonomous systems will be presented. Autonomous operation of ground systems will also be considered, including software for autonomous in-situ propellant production and management, and closed- loop ecological life support systems (CELSS). Finally, plans and directions for the future will be discussed.

Itinerancy of money

NASA Astrophysics Data System (ADS)

Yasutomi, Ayumu

2003-09-01

Previously, I studied [Physica D 82, 180-194 (1995)] the emergence and collapse of money in a computer simulation model. In this paper I will revisit the same topic, building a model in the same line. I discuss this problem from the viewpoint of chaotic itinerancy. Money is the most popular system for evading the difficulty of exchange under division of labor. It emerges autonomously from exchanges among selfish agents which behave as automata. And such emergent money collapses autonomously. I describe money as a structure in economic space, explaining its autonomous emergence and collapse as two phases of the same phenomenon. The key element in this phenomenon is the switch of the meaning of strategies. This is caused by the drastic change of environment caused by the emergence of a structure. This dynamics shares some aspects with chaotic itinerancy.

Research on Production Scheduling System with Bottleneck Based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Weiye, Wang; Peng, Wang; Pan, Quanke

Aimed at the imbalance problem of resource capacity in Production Scheduling System, this paper uses Production Scheduling System based on multi-agent which has been constructed, and combines the dynamic and autonomous of Agent; the bottleneck problem in the scheduling is solved dynamically. Firstly, this paper uses Bottleneck Resource Agent to find out the bottleneck resource in the production line, analyses the inherent mechanism of bottleneck, and describes the production scheduling process based on bottleneck resource. Bottleneck Decomposition Agent harmonizes the relationship of job's arrival time and transfer time in Bottleneck Resource Agent and Non-Bottleneck Resource Agents, therefore, the dynamic scheduling problem is simplified as the single machine scheduling of each resource which takes part in the scheduling. Finally, the dynamic real-time scheduling problem is effectively solved in Production Scheduling System.

Engineering resistance against viroid

USDA-ARS?s Scientific Manuscript database

Viroids, the smallest infectious agents endowed with autonomous replication, are tiny single-stranded circular RNAs (~250-400 nt) without protein-coding ability that, despite their simplicity, infect and often cause disease in herbaceous and woody plants of economic relevance. To mitigate the result...

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

A Concept of Operations for the Use of Emergent Open Internet Technologies as the Basis for a Network-Centric Environment

DTIC Science & Technology

2006-09-01

automated agents , such as chatbots to acts as a relay between chatrooms and blogs or other systems. In particular, chatbots could be used to monitor...bandwidth connections and legacy systems. Chatbot Integration The use of connected autonomous agents that monitor chatrooms to allow users access...of Cell Phone GPS Tracking. .............84 Figure 35. Example of a Chatbot Creating a Blog Entry

Trust Management in Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.; Haack, Jereme N.; Fink, Glenn A.

2009-07-07

Reputation-based trust management techniques can address issues such as insider threat as well as quality of service issues that may be malicious in nature. However, trust management techniques must be adapted to the unique needs of the architectures and problem domains to which they are applied. Certain characteristics of swarms such as their lightweight ephemeral nature and indirect communication make this adaptation especially challenging. In this paper we look at the trust issues and opportunities in mobile agent swarm-based autonomic systems and find that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust managementmore » problem becomes much more scalable and still serves to protect the swarms. We also analyze the applicability of trust management research as it has been applied to architectures with similar characteristics. Finally, we specify required characteristics for trust management mechanisms to be used to monitor the trustworthiness of the entities in a swarm-based autonomic computing system.« less

Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Decentralized Bayesian search using approximate dynamic programming methods.

PubMed

Zhao, Yijia; Patek, Stephen D; Beling, Peter A

2008-08-01

We consider decentralized Bayesian search problems that involve a team of multiple autonomous agents searching for targets on a network of search points operating under the following constraints: 1) interagent communication is limited; 2) the agents do not have the opportunity to agree in advance on how to resolve equivalent but incompatible strategies; and 3) each agent lacks the ability to control or predict with certainty the actions of the other agents. We formulate the multiagent search-path-planning problem as a decentralized optimal control problem and introduce approximate dynamic heuristics that can be implemented in a decentralized fashion. After establishing some analytical properties of the heuristics, we present computational results for a search problem involving two agents on a 5 x 5 grid.

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

Intermediate Levels of Autonomy within the SSM/PMAD Breadboard

NASA Technical Reports Server (NTRS)

Dugal-Whitehead, Norma R.; Walls, Bryan

1995-01-01

The Space Station Module Power Management and Distribution (SSM/PMAD) bread-board is a test bed for the development of advanced power system control and automation. Software control in the SSM/PMAD breadboard is through co-operating systems, called Autonomous Agents. Agents can be a mixture of algorithmic software and expert systems. The early SSM/PMAD system was envisioned as being completely autonomous. It soon became apparent, though, that there would always be a need for human intervention, at least as long as a human interacts with the system in any way. In a system designed only for autonomous operation, manual intervention meant taking full control of the whole system, and loosing whatever expertise was in the system. Several methods for allowing humans to interact at an appropriate level of control were developed. This paper examines some of these intermediate modes of autonomy. The least humanly intrusive mode is simple monitoring. The ability to modify future behavior by altering a schedule involves high-level interaction. Modification of operating activities comes next. The coarsest mode of control is individual, unplanned operation of individual Power System components. Each of these levels is integrated into the SSM/PMAD breadboard, with support for the user (such as warnings of the consequences of control decisions) at every level.

Multiple-Agent Air/Ground Autonomous Exploration Systems

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Chao, Tien-Hsin; Tarbell, Mark; Dohm, James M.

2007-01-01

Autonomous systems of multiple-agent air/ground robotic units for exploration of the surfaces of remote planets are undergoing development. Modified versions of these systems could be used on Earth to perform tasks in environments dangerous or inaccessible to humans: examples of tasks could include scientific exploration of remote regions of Antarctica, removal of land mines, cleanup of hazardous chemicals, and military reconnaissance. A basic system according to this concept (see figure) would include a unit, suspended by a balloon or a blimp, that would be in radio communication with multiple robotic ground vehicles (rovers) equipped with video cameras and possibly other sensors for scientific exploration. The airborne unit would be free-floating, controlled by thrusters, or tethered either to one of the rovers or to a stationary object in or on the ground. Each rover would contain a semi-autonomous control system for maneuvering and would function under the supervision of a control system in the airborne unit. The rover maneuvering control system would utilize imagery from the onboard camera to navigate around obstacles. Avoidance of obstacles would also be aided by readout from an onboard (e.g., ultrasonic) sensor. Together, the rover and airborne control systems would constitute an overarching closed-loop control system to coordinate scientific exploration by the rovers.

Coordination of heterogeneous nonlinear multi-agent systems with prescribed behaviours

NASA Astrophysics Data System (ADS)

Tang, Yutao

2017-10-01

In this paper, we consider a coordination problem for a class of heterogeneous nonlinear multi-agent systems with a prescribed input-output behaviour which was represented by another input-driven system. In contrast to most existing multi-agent coordination results with an autonomous (virtual) leader, this formulation takes possible control inputs of the leader into consideration. First, the coordination was achieved by utilising a group of distributed observers based on conventional assumptions of model matching problem. Then, a fully distributed adaptive extension was proposed without using the input of this input-output behaviour. An example was given to verify their effectiveness.

Dynamic Task Assignment of Autonomous Distributed AGV in an Intelligent FMS Environment

NASA Astrophysics Data System (ADS)

Fauadi, Muhammad Hafidz Fazli Bin Md; Lin, Hao Wen; Murata, Tomohiro

The need of implementing distributed system is growing significantly as it is proven to be effective for organization to be flexible against a highly demanding market. Nevertheless, there are still large technical gaps need to be addressed to gain significant achievement. We propose a distributed architecture to control Automated Guided Vehicle (AGV) operation based on multi-agent architecture. System architectures and agents' functions have been designed to support distributed control of AGV. Furthermore, enhanced agent communication protocol has been configured to accommodate dynamic attributes of AGV task assignment procedure. Result proved that the technique successfully provides a better solution.

The Reactive-Causal Architecture: Introducing an Emotion Model along with Theories of Needs

NASA Astrophysics Data System (ADS)

Aydin, Ali Orhan; Orgun, Mehmet Ali

In the entertainment application area, one of the major aims is to develop believable agents. To achieve this aim, agents should be highly autonomous, situated, flexible, and display affect. The Reactive-Causal Architecture (ReCau) is proposed to simulate these core attributes. In its current form, ReCau cannot explain the effects of emotions on intelligent behaviour. This study aims is to further improve the emotion model of ReCau to explain the effects of emotions on intelligent behaviour. This improvement allows ReCau to be emotional to support the development of believable agents.

A standard protocol for describing individual-based and agent-based models

USGS Publications Warehouse

Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

2006-01-01

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

Multilevel Coordination Mechanisms for Real-Time Autonomous Agents

DTIC Science & Technology

2004-02-01

for example, (Paolucci, 2000) or www.sun.com/ jini ) can allow agents to find each other by describing the kinds of services that they need or provide...In this regard, an important output from DARPA’s CoABS program is the CoABS Grid — a middleware layer based on Java / Jini technology that provides...Figure 1. Map of Binni showing firestorm deception. Misinformation from Gao is intended to displace the firestorm to the west, allowing Gao and

Quantum-enhanced deliberation of learning agents using trapped ions

NASA Astrophysics Data System (ADS)

Dunjko, V.; Friis, N.; Briegel, H. J.

2015-02-01

A scheme that successfully employs quantum mechanics in the design of autonomous learning agents has recently been reported in the context of the projective simulation (PS) model for artificial intelligence. In that approach, the key feature of a PS agent, a specific type of memory which is explored via random walks, was shown to be amenable to quantization, allowing for a speed-up. In this work we propose an implementation of such classical and quantum agents in systems of trapped ions. We employ a generic construction by which the classical agents are ‘upgraded’ to their quantum counterparts by a nested process of adding coherent control, and we outline how this construction can be realized in ion traps. Our results provide a flexible modular architecture for the design of PS agents. Furthermore, we present numerical simulations of simple PS agents which analyze the robustness of our proposal under certain noise models.

Integrating CLIPS applications into heterogeneous distributed systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1991-01-01

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center.

Memoryless cooperative graph search based on the simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Hou, Jian; Yan, Gang-Feng; Fan, Zhen

2011-04-01

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter—radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.

Information Foraging and Change Detection for Automated Science Exploration

NASA Technical Reports Server (NTRS)

Furlong, P. Michael; Dille, Michael

2016-01-01

This paper presents a new algorithm for autonomous on-line exploration in unknown environments. The objective is to free remote scientists from possibly-infeasible extensive preliminary site investigation prior to sending robotic agents. We simulate a common exploration task for an autonomous robot sampling the environment at various locations and compare performance against simpler control strategies. An extension is proposed and evaluated that further permits operation in the presence of environmental variability in which the robot encounters a change in the distribution underlying sampling targets. Experimental results indicate a strong improvement in performance across varied parameter choices for the scenario.

Reinforcement learning: Solving two case studies

NASA Astrophysics Data System (ADS)

Duarte, Ana Filipa; Silva, Pedro; dos Santos, Cristina Peixoto

2012-09-01

Reinforcement Learning algorithms offer interesting features for the control of autonomous systems, such as the ability to learn from direct interaction with the environment, and the use of a simple reward signalas opposed to the input-outputs pairsused in classic supervised learning. The reward signal indicates the success of failure of the actions executed by the agent in the environment. In this work, are described RL algorithmsapplied to two case studies: the Crawler robot and the widely known inverted pendulum. We explore RL capabilities to autonomously learn a basic locomotion pattern in the Crawler, andapproach the balancing problem of biped locomotion using the inverted pendulum.

Emergence of trend trading and its effects in minority game

NASA Astrophysics Data System (ADS)

Liu, Xing-Hua; Liang, Xiao-Bei; Wang, Nai-Jing

2006-09-01

In this paper, we extended Minority Game (MG) by equipping agents with both value and trend strategies. In the new model, agents (we call them strong-adaptation agents) can autonomically select to act as trend trader or value trader when they game and learn in system. So the new model not only can reproduce stylized factors but also has the potential to investigate into the process of some problems of securities market. We investigated the dynamics of trend trading and its impacts on securities market based on the new model. Our research found that trend trading is inevitable when strong-adaptation agents make decisions by inductive reasoning. Trend trading (of strong-adaptation agents) is not irrational behavior but shows agent's strong-adaptation intelligence, because strong-adaptation agents can take advantage of the pure value agents when they game together in hybrid system. We also found that strong-adaptation agents do better in real environment. The results of our research are different with those of behavior finance researches.

The Discourses of Corporate Spiritualism and Evangelical Capitalism.

ERIC Educational Resources Information Center

Nadesan, Majia Holmer

1999-01-01

Explores the growth of literature proposing corporate spirituality as a means of motivating employees. Suggests that critical analysis articulates and advocates two entrepreneurial views of subjecthood that obscure contemporary corporate power by centering the individual as an autonomous agent. Concludes that these discourses reinforce social…

Trust Management and Accountability for Internet Security

ERIC Educational Resources Information Center

Liu, Wayne W.

2011-01-01

Adversarial yet interacting interdependent relationships in information sharing and service provisioning have been a pressing issue of the Internet. Such relationships exist among autonomous software agents, in networking system peers, as well as between "service users and providers." Traditional "ad hoc" security approaches effective in…

Adapting an Agent-Based Model of Socio-Technical Systems to Analyze System and Security Failures

DTIC Science & Technology

2016-05-09

statistically significant amount, which it did with a p-valueɘ.0003 on a simulation of 3125 iterations; the data is shown in the Delegation 1 column of...Blackout metric to a statistically significant amount, with a p-valueɘ.0003 on a simulation of 3125 iterations; the data is shown in the Delegation 2...Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1-Volume 1, pp. 1007- 1014 . International Foundation

Consensus-Based Formation Control of a Class of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Joshi, Suresh; Gonzalez, Oscar R.

2014-01-01

This paper presents a consensus-based formation control scheme for autonomous multi-agent systems represented by double integrator dynamics. Assuming that the information graph topology consists of an undirected connected graph, a leader-based consensus-type control law is presented and shown to provide asymptotic formation stability when subjected to piecewise constant formation velocity commands. It is also shown that global asymptotic stability is preserved in the presence of (0, infinity)- sector monotonic non-decreasing actuator nonlinearities.

Extending the trans-contextual model in physical education and leisure-time contexts: examining the role of basic psychological need satisfaction.

PubMed

Barkoukis, Vassilis; Hagger, Martin S; Lambropoulos, George; Tsorbatzoudis, Haralambos

2010-12-01

The trans-contextual model (TCM) is an integrated model of motivation that aims to explain the processes by which agentic support for autonomous motivation in physical education promotes autonomous motivation and physical activity in a leisure-time context. It is proposed that perceived support for autonomous motivation in physical education is related to autonomous motivation in physical education and leisure-time contexts. Furthermore, relations between autonomous motivation and the immediate antecedents of intentions to engage in physical activity behaviour and actual behaviour are hypothesized. The purpose of the present study was to incorporate the constructs of basic psychological need satisfaction in the TCM to provide a more comprehensive explanation of motivation and demonstrate the robustness of the findings of previous tests of the model that have not incorporated these constructs. Students (N=274) from Greek secondary schools. Participants completed self-report measures of perceived autonomy support, autonomous motivation, and basic psychological need satisfaction in physical education. Follow-up measures of these variables were taken in a leisure-time context along with measures of attitudes, subjective norms, perceived behavioural control (PBC), and intentions from the theory of planned behaviour 1 week later. Self-reported physical activity behaviour was measured 4 weeks later. Results supported TCM hypotheses. Basic psychological need satisfaction variables uniquely predicted autonomous motivation in physical education and leisure time as well as the antecedents of intention, namely, attitudes, and PBC. The basic psychological need satisfaction variables also mediated the effects of perceived autonomy support on autonomous motivation in physical education. Findings support the TCM and provide further information of the mechanisms in the model and integrated theories of motivation in physical education and leisure time.

Toward Agent Programs with Circuit Semantics

NASA Technical Reports Server (NTRS)

Nilsson, Nils J.

1992-01-01

New ideas are presented for computing and organizing actions for autonomous agents in dynamic environments-environments in which the agent's current situation cannot always be accurately discerned and in which the effects of actions cannot always be reliably predicted. The notion of 'circuit semantics' for programs based on 'teleo-reactive trees' is introduced. Program execution builds a combinational circuit which receives sensory inputs and controls actions. These formalisms embody a high degree of inherent conditionality and thus yield programs that are suitably reactive to their environments. At the same time, the actions computed by the programs are guided by the overall goals of the agent. The paper also speculates about how programs using these ideas could be automatically generated by artificial intelligence planning systems and adapted by learning methods.

Material quality assessment of silk nanofibers based on swarm intelligence

NASA Astrophysics Data System (ADS)

Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

2013-02-01

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

Explanation Capabilities for Behavior-Based Robot Control

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.

2012-01-01

A recent study that evaluated issues associated with remote interaction with an autonomous vehicle within the framework of grounding found that missing contextual information led to uncertainty in the interpretation of collected data, and so introduced errors into the command logic of the vehicle. As the vehicles became more autonomous through the activation of additional capabilities, more errors were made. This is an inefficient use of the platform, since the behavior of remotely located autonomous vehicles didn't coincide with the "mental models" of human operators. One of the conclusions of the study was that there should be a way for the autonomous vehicles to describe what action they choose and why. Robotic agents with enough self-awareness to dynamically adjust the information conveyed back to the Operations Center based on a detail level component analysis of requests could provide this description capability. One way to accomplish this is to map the behavior base of the robot into a formal mathematical framework called a cost-calculus. A cost-calculus uses composition operators to build up sequences of behaviors that can then be compared to what is observed using well-known inference mechanisms.

Simulation and Control Lab Development for Power and Energy Management for NASA Manned Deep Space Missions

NASA Technical Reports Server (NTRS)

McNelis, Anne M.; Beach, Raymond F.; Soeder, James F.; McNelis, Nancy B.; May, Ryan; Dever, Timothy P.; Trase, Larry

2014-01-01

The development of distributed hierarchical and agent-based control systems will allow for reliable autonomous energy management and power distribution for on-orbit missions. Power is one of the most critical systems on board a space vehicle, requiring quick response time when a fault or emergency is identified. As NASAs missions with human presence extend beyond low earth orbit autonomous control of vehicle power systems will be necessary and will need to reliably function for long periods of time. In the design of autonomous electrical power control systems there is a need to dynamically simulate and verify the EPS controller functionality prior to use on-orbit. This paper presents the work at NASA Glenn Research Center in Cleveland, Ohio where the development of a controls laboratory is being completed that will be utilized to demonstrate advanced prototype EPS controllers for space, aeronautical and terrestrial applications. The control laboratory hardware, software and application of an autonomous controller for demonstration with the ISS electrical power system is the subject of this paper.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Mount, Frances; Carreon, Patricia; Torney, Susan E.

2001-01-01

The Engineering and Mission Operations Directorates at NASA Johnson Space Center are combining laboratories and expertise to establish the Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations. This is a testbed for human centered design, development and evaluation of intelligent autonomous and assistant systems that will be needed for human exploration and development of space. This project will improve human-centered analysis, design and evaluation methods for developing intelligent software. This software will support human-machine cognitive and collaborative activities in future interplanetary work environments where distributed computer and human agents cooperate. We are developing and evaluating prototype intelligent systems for distributed multi-agent mixed-initiative operations. The primary target domain is control of life support systems in a planetary base. Technical approaches will be evaluated for use during extended manned tests in the target domain, the Bioregenerative Advanced Life Support Systems Test Complex (BIO-Plex). A spinoff target domain is the International Space Station (ISS) Mission Control Center (MCC). Prodl}cts of this project include human-centered intelligent software technology, innovative human interface designs, and human-centered software development processes, methods and products. The testbed uses adjustable autonomy software and life support systems simulation models from the Adjustable Autonomy Testbed, to represent operations on the remote planet. Ground operations prototypes and concepts will be evaluated in the Exploration Planning and Operations Center (ExPOC) and Jupiter Facility.

Multi-agent robotic systems and applications for satellite missions

NASA Astrophysics Data System (ADS)

Nunes, Miguel A.

A revolution in the space sector is happening. It is expected that in the next decade there will be more satellites launched than in the previous sixty years of space exploration. Major challenges are associated with this growth of space assets such as the autonomy and management of large groups of satellites, in particular with small satellites. There are two main objectives for this work. First, a flexible and distributed software architecture is presented to expand the possibilities of spacecraft autonomy and in particular autonomous motion in attitude and position. The approach taken is based on the concept of distributed software agents, also referred to as multi-agent robotic system. Agents are defined as software programs that are social, reactive and proactive to autonomously maximize the chances of achieving the set goals. Part of the work is to demonstrate that a multi-agent robotic system is a feasible approach for different problems of autonomy such as satellite attitude determination and control and autonomous rendezvous and docking. The second main objective is to develop a method to optimize multi-satellite configurations in space, also known as satellite constellations. This automated method generates new optimal mega-constellations designs for Earth observations and fast revisit times on large ground areas. The optimal satellite constellation can be used by researchers as the baseline for new missions. The first contribution of this work is the development of a new multi-agent robotic system for distributing the attitude determination and control subsystem for HiakaSat. The multi-agent robotic system is implemented and tested on the satellite hardware-in-the-loop testbed that simulates a representative space environment. The results show that the newly proposed system for this particular case achieves an equivalent control performance when compared to the monolithic implementation. In terms on computational efficiency it is found that the multi-agent robotic system has a consistent lower CPU load of 0.29 +/- 0.03 compared to 0.35 +/- 0.04 for the monolithic implementation, a 17.1 % reduction. The second contribution of this work is the development of a multi-agent robotic system for the autonomous rendezvous and docking of multiple spacecraft. To compute the maneuvers guidance, navigation and control algorithms are implemented as part of the multi-agent robotic system. The navigation and control functions are implemented using existing algorithms, but one important contribution of this section is the introduction of a new six degrees of freedom guidance method which is part of the guidance, navigation and control architecture. This new method is an explicit solution to the guidance problem, and is particularly useful for real time guidance for attitude and position, as opposed to typical guidance methods which are based on numerical solutions, and therefore are computationally intensive. A simulation scenario is run for docking four CubeSats deployed radially from a launch vehicle. Considering fully actuated CubeSats, the simulations show docking maneuvers that are successfully completed within 25 minutes which is approximately 30% of a full orbital period in low earth orbit. The final section investigates the problem of optimization of satellite constellations for fast revisit time, and introduces a new method to generate different constellation configurations that are evaluated with a genetic algorithm. Two case studies are presented. The first is the optimization of a constellation for rapid coverage of the oceans of the globe in 24 hours or less. Results show that for an 80 km sensor swath width 50 satellites are required to cover the oceans with a 24 hour revisit time. The second constellation configuration study focuses on the optimization for the rapid coverage of the North Atlantic Tracks for air traffic monitoring in 3 hours or less. The results show that for a fixed swath width of 160 km and for a 3 hour revisit time 52 satellites are required.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Anesthesia and concussion.

PubMed

Tasker, Robert C

2017-06-01

As clinicians preparing patients for general anesthesia, should we consider the possibility of concussion in our elective operative patients? If so, why is this necessary? Is it possible that exposure to an anesthetic is detrimental to recovery from concussion? If so, what should we do about the imperative/urgency for surgery? No answers are promised in this review. Rather, the focus is on the questions and approaches taken in the recent literature, as well as highlighting a need for more research. Surgery, pain and general anesthesia all influence autonomic nervous system responses. Intravenous and inhalational anesthetic agents are also known to have variable effects on the cerebrovascular reactivity (CVR) to carbon dioxide (CO2). This review adds to this general information the recent, specific physiologic alterations seen after concussion in autonomic system function and the CVR to CO2. This review provides a perspective about autonomic nervous system function and cerebrovascular effects of concussion, and some relevant clinical issues that warrant further clinical study.

The Role of Trust in Information Science and Technology.

ERIC Educational Resources Information Center

Marsh, Stephen; Dibben, Mark R.

2003-01-01

Discusses the notion of trust as it relates to information science and technology, specifically user interfaces, autonomous agents, and information systems. Highlights include theoretical meaning of trust; trust and levels of analysis, including organizational trust; electronic commerce, user interfaces, and static trust; dynamic trust; and trust…

Adapting Autonomous Behavior Using an Inverse Trust Estimation

DTIC Science & Technology

2014-07-01

be undertrusting the agent so trust should be increased. It does not take into ac- count situations where overtrust may be occurring. To account for...Bisantz, A.M., Drury , C.G.: Foundations for an empirically determined scale of trust in automated systems. International Journal of Cognitive

Developmental Liberalism

ERIC Educational Resources Information Center

Curren, Randall

2006-01-01

In this essay, Randall Curren identifies a type of liberalism that incorporates empirical claims about the development of agency and rationality, and responds to the criticism that liberalism rests on an incoherent conception of "autonomous agency." He argues that moral agents did indeed "become ghosts" somewhere en route from Aristotle to Kant,…

Pharmacotherapy of Cardiovascular Autonomic Dysfunction in Parkinson Disease.

PubMed

Shibao, Cyndya A; Kaufmann, Horacio

2017-11-01

Cardiovascular autonomic dysfunctions, including neurogenic orthostatic hypotension, supine hypertension and post-prandial hypotension, are relatively common in patients with Parkinson disease. Recent evidence suggests that early autonomic impairment such as cardiac autonomic denervation and even neurogenic orthostatic hypotension occur prior to the appearance of the typical motor deficits associated with the disease. When neurogenic orthostatic hypotension develops, patients with Parkinson disease have an increased risk of mortality, falls, and trauma-related to falls. Neurogenic orthostatic hypotension reduces quality of life and contributes to cognitive decline and physical deconditioning. The co-existence of supine hypertension complicates the treatment of neurogenic orthostatic hypotension because it involves the use of drugs with opposing effects. Furthermore, treatment of neurogenic orthostatic hypotension is challenging because of few therapeutic options; in the past 20 years, the US Food and Drug Administration approved only two drugs for the treatment of this condition. Small, open-label or randomized studies using acute doses of different pharmacologic probes suggest benefit of other drugs as well, which could be used in individual patients under close monitoring. This review describes the pathophysiology of neurogenic orthostatic hypotension and supine hypertension in Parkinson disease. We discuss the mode of action and therapeutic efficacy of different pharmacologic agents used in the treatment of patients with cardiovascular autonomic failure.

An Algorithm for Autonomous Formation Obstacle Avoidance

NASA Astrophysics Data System (ADS)

Cruz, Yunior I.

The level of human interaction with Unmanned Aerial Systems varies greatly from remotely piloted aircraft to fully autonomous systems. In the latter end of the spectrum, the challenge lies in designing effective algorithms to dictate the behavior of the autonomous agents. A swarm of autonomous Unmanned Aerial Vehicles requires collision avoidance and formation flight algorithms to negotiate environmental challenges it may encounter during the execution of its mission, which may include obstacles and chokepoints. In this work, a simple algorithm is developed to allow a formation of autonomous vehicles to perform point to point navigation while avoiding obstacles and navigating through chokepoints. Emphasis is placed on maintaining formation structures. Rather than breaking formation and individually navigating around the obstacle or through the chokepoint, vehicles are required to assemble into appropriately sized/shaped sub-formations, bifurcate around the obstacle or negotiate the chokepoint, and reassemble into the original formation at the far side of the obstruction. The algorithm receives vehicle and environmental properties as inputs and outputs trajectories for each vehicle from start to the desired ending location. Simulation results show that the algorithm safely routes all vehicles past the obstruction while adhering to the aforementioned requirements. The formation adapts and successfully negotiates the obstacles and chokepoints in its path while maintaining proper vehicle separation.

Emergence of Leadership in Communication.

PubMed

Allahverdyan, Armen E; Galstyan, Aram

2016-01-01

We study a neuro-inspired model that mimics a discussion (or information dissemination) process in a network of agents. During their interaction, agents redistribute activity and network weights, resulting in emergence of leader(s). The model is able to reproduce the basic scenarios of leadership known in nature and society: laissez-faire (irregular activity, weak leadership, sizable inter-follower interaction, autonomous sub-leaders); participative or democratic (strong leadership, but with feedback from followers); and autocratic (no feedback, one-way influence). Several pertinent aspects of these scenarios are found as well-e.g., hidden leadership (a hidden clique of agents driving the official autocratic leader), and successive leadership (two leaders influence followers by turns). We study how these scenarios emerge from inter-agent dynamics and how they depend on behavior rules of agents-in particular, on their inertia against state changes.

A Mechanism to Avoid Collusion Attacks Based on Code Passing in Mobile Agent Systems

NASA Astrophysics Data System (ADS)

Jaimez, Marc; Esparza, Oscar; Muñoz, Jose L.; Alins-Delgado, Juan J.; Mata-Díaz, Jorge

Mobile agents are software entities consisting of code, data, state and itinerary that can migrate autonomously from host to host executing their code. Despite its benefits, security issues strongly restrict the use of code mobility. The protection of mobile agents against the attacks of malicious hosts is considered the most difficult security problem to solve in mobile agent systems. In particular, collusion attacks have been barely studied in the literature. This paper presents a mechanism that avoids collusion attacks based on code passing. Our proposal is based on a Multi-Code agent, which contains a different variant of the code for each host. A Trusted Third Party is responsible for providing the information to extract its own variant to the hosts, and for taking trusted timestamps that will be used to verify time coherence.

Agent Models for Self-Motivated Home-Assistant Bots

NASA Astrophysics Data System (ADS)

Merrick, Kathryn; Shafi, Kamran

2010-01-01

Modern society increasingly relies on technology to support everyday activities. In the past, this technology has focused on automation, using computer technology embedded in physical objects. More recently, there is an expectation that this technology will not just embed reactive automation, but also embed intelligent, proactive automation in the environment. That is, there is an emerging desire for novel technologies that can monitor, assist, inform or entertain when required, and not just when requested. This paper presents three self-motivated, home-assistant bot applications using different self-motivated agent models. Self-motivated agents use a computational model of motivation to generate goals proactively. Technologies based on self-motivated agents can thus respond autonomously and proactively to stimuli from their environment. Three prototypes of different self-motivated agent models, using different computational models of motivation, are described to demonstrate these concepts.

Design and Control of Large Collections of Learning Agents

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2001-01-01

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

Materials and methods for autonomous restoration of electrical conductivity

DOEpatents

Blaiszik, Benjamin J; Odom, Susan A; Caruso, Mary M; Jackson, Aaron C; Baginska, Marta B; Ritchey, Joshua A; Finke, Aaron D; White, Scott R; Moore, Jeffrey S; Sottos, Nancy R; Braun, Paul V; Amine, Khalil

2014-03-25

An autonomic conductivity restoration system includes a solid conductor and a plurality of particles. The particles include a conductive fluid, a plurality of conductive microparticles, and/or a conductive material forming agent. The solid conductor has a first end, a second end, and a first conductivity between the first and second ends. When a crack forms between the first and second ends of the conductor, the contents of at least a portion of the particles are released into the crack. The cracked conductor and the released contents of the particles form a restored conductor having a second conductivity, which may be at least 90% of the first conductivity.

Metrics of a Paradigm for Intelligent Control

NASA Technical Reports Server (NTRS)

Hexmoor, Henry

1999-01-01

We present metrics for quantifying organizational structures of complex control systems intended for controlling long-lived robotic or other autonomous applications commonly found in space applications. Such advanced control systems are often called integration platforms or agent architectures. Reported metrics span concerns about time, resources, software engineering, and complexities in the world.

Test oracle automation for V&V of an autonomous spacecraft's planner

NASA Technical Reports Server (NTRS)

Feather, M. S.; Smith, B.

2001-01-01

We built automation to assist the software testing efforts associated with the Remote Agent experiment. In particular, our focus was upon introducing test oracles into the testing of the planning and scheduling system component. This summary is intended to provide an overview of the work.

Help Seeking: Agentic Learners Initiating Feedback

ERIC Educational Resources Information Center

Fletcher, Anna Katarina

2018-01-01

Effective feedback is an essential tool for making learning explicit and an essential feature of classroom practice that promotes learner autonomy. Yet, it remains a pressing challenge for teachers to scaffold the active involvement of students as critical, reflective and autonomous learners who use feedback constructively. This paper seeks to…

Discovery Learning in Autonomous Agents Using Genetic Algorithms

DTIC Science & Technology

1993-12-01

Meyer and Wilson (47). 65. Roitblat , H. L., et al. "Biomimetic Sonar Processing: Prom Dolphin Echoloc-Ation to Artificial Neural Networks." In Meyer and...34 In Meyer and Wilson (47). 65. Roitblat , H. L., et al. "Biomimetic Sonar Processing: From Dolphin Echolocation to Artificial Neural Networks." In

Frequency ranges of heart rate variability related to autonomic nerve activity in the mouse.

PubMed

Tsai, Meng-Li; Chen, Chien-Chang; Yeh, Chang-Jyi; Chou, Li-Ming; Cheng, Chiung-Hsiang

2012-01-01

Mice have gained more and more attention in recent years and been widely used in transgenic experiments. Although the number of researches on the heart rate variability (HRV) of mice has been gradually increasing, a consensus on the frequency ranges of autonomic modulation has not been established. Therefore, the main purpose of this study was to find a HRV "prototype" for conscious mice in the state of being motionless and breathing regularly (called "genuinely resting"), and to determine the frequency ranges corresponding to the autonomic modulation. Further, whether these frequencies will change when the mice move freely was studied to evaluate the feasibility of the HRV spectrum as an index of the autonomic modulation of mice. The recording sites were specially arranged to simultaneously obtain the electrocardiography and electromyography data to be provided for the use of HRV analysis and motion monitoring, respectively. The states of being motionless and breathing regularly as judged from the electromyography results were selected as a genuine resting state of a conscious mouse. The frequencies related to autonomic modulation of HRV were determined by comparing the spectrum changes before and after blockades of the autonomic tone by different pharmaceutical agents in both the genuine resting state and freely moving states. Our results showed that the HRV of mice is not suitable for indexing sympathetic modulation; however, it is possible to use the spectral power in the frequency range between 0.1 and 1 Hz as an index of parasympathetic modulation.

Interacting with an artificial partner: modeling the role of emotional aspects.

PubMed

Cattinelli, Isabella; Goldwurm, Massimiliano; Borghese, N Alberto

2008-12-01

In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated agents. Based on the agent's personality, attitude, and nature, and on the emotional inputs it receives, the model will determine the next emotional state displayed by the agent itself. The probabilistic and time-varying nature of the model yields rich and dynamic interactions, and an autonomous adaptation to the interlocutor. In addition, a reinforcement learning technique is applied to have one agent drive its partner's behavior toward desired states. The model may also be used as a tool for behavior analysis, by extracting high probability patterns of interaction and by resorting to the ergodic properties of Markov chains.

Effect of reinforcement learning on coordination of multiangent systems

NASA Astrophysics Data System (ADS)

Bukkapatnam, Satish T. S.; Gao, Greg

2000-12-01

For effective coordination of distributed environments involving multiagent systems, learning ability of each agent in the environment plays a crucial role. In this paper, we develop a simple group learning method based on reinforcement, and study its effect on coordination through application to a supply chain procurement scenario involving a computer manufacturer. Here, all parties are represented by self-interested, autonomous agents, each capable of performing specific simple tasks. They negotiate with each other to perform complex tasks and thus coordinate supply chain procurement. Reinforcement learning is intended to enable each agent to reach a best negotiable price within a shortest possible time. Our simulations of the application scenario under different learning strategies reveals the positive effects of reinforcement learning on an agent's as well as the system's performance.

Pattern Analysis in Social Networks with Dynamic Connections

NASA Astrophysics Data System (ADS)

Wu, Yu; Zhang, Yu

In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Most existing work in this area models social network in which agent relations are fixed; instead, we focus on dynamic social networks where agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation rule called the Highest Weighted Reward (HWR) rule, with which agents dynamically choose their neighbors in order to maximize their own utilities based on the rewards from previous interactions. Our experiments show that in the 2-action pure coordination game, our system will stabilize to a clustering state where all relationships in the network are rewarded with the optimal payoff. Our experiments also reveal additional interesting patterns in the network.

Synthetic consciousness: the distributed adaptive control perspective

PubMed Central

2016-01-01

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431526

Synthetic consciousness: the distributed adaptive control perspective.

PubMed

Verschure, Paul F M J

2016-08-19

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Acquisition of Autonomous Behaviors by Robotic Assistants

NASA Technical Reports Server (NTRS)

Peters, R. A., II; Sarkar, N.; Bodenheimer, R. E.; Brown, E.; Campbell, C.; Hambuchen, K.; Johnson, C.; Koku, A. B.; Nilas, P.; Peng, J.

2005-01-01

Our research achievements under the NASA-JSC grant contributed significantly in the following areas. Multi-agent based robot control architecture called the Intelligent Machine Architecture (IMA) : The Vanderbilt team received a Space Act Award for this research from NASA JSC in October 2004. Cognitive Control and the Self Agent : Cognitive control in human is the ability to consciously manipulate thoughts and behaviors using attention to deal with conflicting goals and demands. We have been updating the IMA Self Agent towards this goal. If opportunity arises, we would like to work with NASA to empower Robonaut to do cognitive control. Applications 1. SES for Robonaut, 2. Robonaut Fault Diagnostic System, 3. ISAC Behavior Generation and Learning, 4. Segway Research.

Source Update Capture in Information Agents

NASA Technical Reports Server (NTRS)

Ashish, Naveen; Kulkarni, Deepak; Wang, Yao

2003-01-01

In this paper we present strategies for successfully capturing updates at Web sources. Web-based information agents provide integrated access to autonomous Web sources that can get updated. For many information agent applications we are interested in knowing when a Web source to which the application provides access, has been updated. We may also be interested in capturing all the updates at a Web source over a period of time i.e., detecting the updates and, for each update retrieving and storing the new version of data. Previous work on update and change detection by polling does not adequately address this problem. We present strategies for intelligently polling a Web source for efficiently capturing changes at the source.

Advances in Autonomous Systems for Missions of Space Exploration

NASA Astrophysics Data System (ADS)

Gross, A. R.; Smith, B. D.; Briggs, G. A.; Hieronymus, J.; Clancy, D. J.

New missions of space exploration will require unprecedented levels of autonomy to successfully accomplish their objectives. Both inherent complexity and communication distances will preclude levels of human involvement common to current and previous space flight missions. With exponentially increasing capabilities of computer hardware and software, including networks and communication systems, a new balance of work is being developed between humans and machines. This new balance holds the promise of meeting the greatly increased space exploration requirements, along with dramatically reduced design, development, test, and operating costs. New information technologies, which take advantage of knowledge-based software, model-based reasoning, and high performance computer systems, will enable the development of a new generation of design and development tools, schedulers, and vehicle and system health monitoring and maintenance capabilities. Such tools will provide a degree of machine intelligence and associated autonomy that has previously been unavailable. These capabilities are critical to the future of space exploration, since the science and operational requirements specified by such missions, as well as the budgetary constraints that limit the ability to monitor and control these missions by a standing army of ground- based controllers. System autonomy capabilities have made great strides in recent years, for both ground and space flight applications. Autonomous systems have flown on advanced spacecraft, providing new levels of spacecraft capability and mission safety. Such systems operate by utilizing model-based reasoning that provides the capability to work from high-level mission goals, while deriving the detailed system commands internally, rather than having to have such commands transmitted from Earth. This enables missions of such complexity and communications distance as are not otherwise possible, as well as many more efficient and low cost applications. One notable example of such missions are those to explore for the existence of water on planets such as Mars and the moons of Jupiter. It is clear that water does not exist on the surfaces of such bodies, but may well be located at some considerable depth below the surface, thus requiring a subsurface drilling capability. Subsurface drilling on planetary surfaces will require a robust autonomous control and analysis system, currently a major challenge, but within conceivable reach of planned technology developments. This paper will focus on new and innovative software for remote, autonomous, space systems flight operations, including flight test results, lessons learned, and implications for the future. An additional focus will be on technologies for planetary exploration using autonomous systems and astronaut-assistance systems that employ new spoken language technology. Topics to be presented will include a description of key autonomous control concepts, illustrated by the Remote Agent program that commanded the Deep Space 1 spacecraft to new levels of system autonomy, recent advances in distributed autonomous system capabilities, and concepts for autonomous vehicle health management systems. A brief description of teaming spacecraft and rovers for complex exploration missions will also be provided. New software for autonomous science data acquisition for planetary exploration will also be described, as well as advanced systems for safe planetary landings. Current results of autonomous planetary drilling system research will be presented. A key thrust within NASA is to develop technologies that will leverage the capabilities of human astronauts during planetary surface explorations. One such technology is spoken dialogue interfaces, which would allow collaboration with semi-autonomous agents that are engaged in activities that are normally accomplished using language, e.g., astronauts in space suits interacting with groups of semi-autonomous rovers and other astronauts. This technology will be described and discussed in the context of future exploration missions and the major new capabilities enabled by such systems. Finally, plans and directions for the future of autonomous systems will be presented.

The ground vehicle manager's associate

NASA Technical Reports Server (NTRS)

Edwards, Gary R.; Burnard, Robert H.; Bewley, William L.; Bullock, Bruce L.

1994-01-01

An overview of MAX, a software framework for manager's associate systems, is presented. MAX is used to develop and execute a problem-solving strategy for the task planning of semi-autonomous agents with the assistance of human performance. This paper describes the use of MAX in the supervisory management of robotic vehicles as they explore a planetary surface.

Investigating Estonian Teachers' Expectations for the General Education Curriculum

ERIC Educational Resources Information Center

Viirpalu, Piret; Krull, Edgar; Mikser, Rain

2014-01-01

Finding a balance between a centralised and decentralised curricular policy for general education and seeing teachers as autonomous agents of curriculum development is a recurrent issue in many countries. Radical reforms bring about the need to investigate whether and to what extent different parties - and first of all, teachers - are ready to…

3D Inhabited Virtual Worlds: Interactivity and Interaction between Avatars, Autonomous Agents, and Users.

ERIC Educational Resources Information Center

Jensen, Jens F.

This paper addresses some of the central questions currently related to 3-Dimensional Inhabited Virtual Worlds (3D-IVWs), their virtual interactions, and communication, drawing from the theory and methodology of sociology, interaction analysis, interpersonal communication, semiotics, cultural studies, and media studies. First, 3D-IVWs--seen as a…

Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Hunsberger, Luke; Tsamardinos, Ioannis

2005-01-01

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.

A Software Product Line Process to Develop Agents for the IoT.

PubMed

Ayala, Inmaculada; Amor, Mercedes; Fuentes, Lidia; Troya, José M

2015-07-01

One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

Agents That Negotiate Proficiently with People

NASA Astrophysics Data System (ADS)

Kraus, Sarit

Negotiation is a process by which interested parties confer with the aim of reaching agreements. The dissemination of technologies such as the Internet has created opportunities for computer agents to negotiate with people, despite being distributed geographically and in time. The inclusion of people presents novel problems for the design of autonomous agent negotiation strategies. People do not adhere to the optimal, monolithic strategies that can be derived analytically, as is the case in settings comprising computer agents alone. Their negotiation behavior is affected by a multitude of social and psychological factors, such as social attributes that influence negotiation deals (e.g., social welfare, inequity aversion) and traits of individual negotiators (e.g., altruism, trustworthiness, helpfulness). Furthermore, culture plays an important role in their decision making and people of varying cultures differ in the way they make offers and fulfill their commitments in negotiation.

NBC detection in air and water

NASA Technical Reports Server (NTRS)

Hartley, Frank T.; Smith, Steven J.; McMurtry, Gary M.

2003-01-01

Participating in a Navy STTR project to develop a system capable of the 'real-time' detection and quanitification of nuclear, biological and chemical (NBC) warfare agents, and of related industrial chemicals including NBC agent synthesis by-products in water and in air immediately above the water's surface. This project uses JPL's Soft Ionization Membrane (SIM) technology which totally ionizes molecules without fragmentation (a process that can markedly improve the sensitivity and specificity of molecule compostition identification), and JPL's Rotating Field Mass Spectrometer (RFMS) technology which has large enough dynamic mass range to enable detection of nuclear materials as well as biological and chemical agents. This Navy project integrates these JPL Environmental Monitoring UnitS (REMUS) an autonomous underwater vehicle (AUV). It is anticipated that the REMUS AUV will be capable of 'real-time' detection and quantification of NBC warefare agents.

Emergence of Leadership in Communication

PubMed Central

Allahverdyan, Armen E.; Galstyan, Aram

2016-01-01

We study a neuro-inspired model that mimics a discussion (or information dissemination) process in a network of agents. During their interaction, agents redistribute activity and network weights, resulting in emergence of leader(s). The model is able to reproduce the basic scenarios of leadership known in nature and society: laissez-faire (irregular activity, weak leadership, sizable inter-follower interaction, autonomous sub-leaders); participative or democratic (strong leadership, but with feedback from followers); and autocratic (no feedback, one-way influence). Several pertinent aspects of these scenarios are found as well—e.g., hidden leadership (a hidden clique of agents driving the official autocratic leader), and successive leadership (two leaders influence followers by turns). We study how these scenarios emerge from inter-agent dynamics and how they depend on behavior rules of agents—in particular, on their inertia against state changes. PMID:27532484

Learning Agents for Autonomous Space Asset Management (LAASAM)

NASA Astrophysics Data System (ADS)

Scally, L.; Bonato, M.; Crowder, J.

2011-09-01

Current and future space systems will continue to grow in complexity and capabilities, creating a formidable challenge to monitor, maintain, and utilize these systems and manage their growing network of space and related ground-based assets. Integrated System Health Management (ISHM), and in particular, Condition-Based System Health Management (CBHM), is the ability to manage and maintain a system using dynamic real-time data to prioritize, optimize, maintain, and allocate resources. CBHM entails the maintenance of systems and equipment based on an assessment of current and projected conditions (situational and health related conditions). A complete, modern CBHM system comprises a number of functional capabilities: sensing and data acquisition; signal processing; conditioning and health assessment; diagnostics and prognostics; and decision reasoning. In addition, an intelligent Human System Interface (HSI) is required to provide the user/analyst with relevant context-sensitive information, the system condition, and its effect on overall situational awareness of space (and related) assets. Colorado Engineering, Inc. (CEI) and Raytheon are investigating and designing an Intelligent Information Agent Architecture that will provide a complete range of CBHM and HSI functionality from data collection through recommendations for specific actions. The research leverages CEI’s expertise with provisioning management network architectures and Raytheon’s extensive experience with learning agents to define a system to autonomously manage a complex network of current and future space-based assets to optimize their utilization.

Smart materials on the way to theranostic nanorobots: Molecular machines and nanomotors, advanced biosensors, and intelligent vehicles for drug delivery.

PubMed

Sokolov, Ilya L; Cherkasov, Vladimir R; Tregubov, Andrey A; Buiucli, Sveatoslav R; Nikitin, Maxim P

2017-06-01

Theranostics, a fusion of two key parts of modern medicine - diagnostics and therapy of the organism's disorders, promises to bring the efficacy of medical treatment to a fundamentally new level and to become the basis of personalized medicine. Extrapolating today's progress in the field of smart materials to the long-run prospect, we can imagine future intelligent agents capable of performing complex analysis of different physiological factors inside the living organism and implementing a built-in program thereby triggering a series of therapeutic actions. These agents, by analogy with their macroscopic counterparts, can be called nanorobots. It is quite obscure what these devices are going to look like but they will be more or less based on today's achievements in nanobiotechnology. The present Review is an attempt to systematize highly diverse nanomaterials, which may potentially serve as modules for theranostic nanorobotics, e.g., nanomotors, sensing units, and payload carriers. Biocomputing-based sensing, externally actuated or chemically "fueled" autonomous movement, swarm inter-agent communication behavior are just a few inspiring examples that nanobiotechnology can offer today for construction of truly intelligent drug delivery systems. The progress of smart nanomaterials toward fully autonomous drug delivery nanorobots is an exciting prospect for disease treatment. Synergistic combination of the available approaches and their further development may produce intelligent drugs of unmatched functionality. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of antipsychotic agents on heart rate variability in male WKY rats: implications for cardiovascular safety.

PubMed

Wang, Ying-Chieh; Chen, Chun-Yu; Kuo, Terry B J; Lai, Ching-Jung; Yang, Cheryl C H

2012-06-01

Sudden cardiac death is higher among schizophrenic patients and is associated with parasympathetic hypoactivity. Antipsychotic agents are highly suspected to be a precipitating factor. Thus, we aimed to test if the antipsychotics haloperidol, risperidone and clozapine affect cardiac autonomic function, excluding the confounding effect of altered sleep structure by the drugs. In this study, haloperidol, risperidone and clozapine were given separately by intraperitoneal injection to male Wistar-Kyoto rats for 5 days. Electroencephalogram (EEG), electromyogram (EMG) and electrocardiographic signals were recorded at baseline and 5 days after drug treatments. Sleep scoring was based on EEG and EMG signals. Cardiac autonomic function was assessed using heart rate variability analysis. Clozapine increased heart rate and suppressed cardiac sympathetic and parasympathetic activity. Cardiac acceleration was more severe during sleep. Haloperidol tended to decrease heart rate while risperidone mildly increased heart rate; however, their effects were less obvious than those of clozapine. There was a significant drug-by-stage interaction on several heart rate variability measures. Taking this evidence as a whole, we conclude that haloperidol has a better level of cardiovascular safety than either risperidone or clozapine. Application of this approach to other psychotropic agents in the future will be a useful and helpful way to evaluate the cardiovascular safety of the various psychotropic medications that are in clinical use. Copyright © 2012 S. Karger AG, Basel.

[Using autonomous electrostimulation device Erektron in treating female overactive bladder].

PubMed

Yarin, G Yu; Shelyakina, O V; Fedorenko, V N; Alekseeva, A V; Vilgelmi, I A

2016-11-01

Overactive bladder (OAB) is one of the most common syndromes of lower urinary tract dysfunction. Besides standard therapy using anticholinergic medications, comprehensive management of overactive bladder includes physiotherapy. To test the clinical effectiveness and safety of autonomous electrostimulation device "Erektron" in treating OAB in women. The study was conducted at the Urology and Gynecology Clinic of the Innovative Medical Technology Center between 25.04.2014 and 30.01.2015. It included 20 women with newly diagnosed OAB both with and without urinary urgency incontinence or urinary stress incontinence. The patients were divided into 2 groups. All patients were treated with the first line anticholinergic agent solifenacin 5 mg daily. In patients of group 1, anticholinergic therapy was administered concurrently with intravaginal electrostimulation using "Erektron" device. In both groups, the treatment resulted in positive results, but a more pronounced improvement was found in group 1 patients with mixed incontinence. Autonomous electrostimulation device MT-RV "Erektron" can be used in comprehensive management of patients with OAB, including those with stress urinary incontinence.

Software Agents Applications Using Real-Time CORBA

NASA Astrophysics Data System (ADS)

Fowell, S.; Ward, R.; Nielsen, M.

This paper describes current projects being performed by SciSys in the area of the use of software agents, built using CORBA middleware, to improve operations within autonomous satellite/ground systems. These concepts have been developed and demonstrated in a series of experiments variously funded by ESA's Technology Flight Opportunity Initiative (TFO) and Leading Edge Technology for SMEs (LET-SME), and the British National Space Centre's (BNSC) National Technology Programme. Some of this earlier work has already been reported in [1]. This paper will address the trends, issues and solutions associated with this software agent architecture concept, together with its implementation using CORBA within an on-board environment, that is to say taking account of its real- time and resource constrained nature.

Reinforcement learning agents providing advice in complex video games

NASA Astrophysics Data System (ADS)

Taylor, Matthew E.; Carboni, Nicholas; Fachantidis, Anestis; Vlahavas, Ioannis; Torrey, Lisa

2014-01-01

This article introduces a teacher-student framework for reinforcement learning, synthesising and extending material that appeared in conference proceedings [Torrey, L., & Taylor, M. E. (2013)]. Teaching on a budget: Agents advising agents in reinforcement learning. {Proceedings of the international conference on autonomous agents and multiagent systems}] and in a non-archival workshop paper [Carboni, N., &Taylor, M. E. (2013, May)]. Preliminary results for 1 vs. 1 tactics in StarCraft. {Proceedings of the adaptive and learning agents workshop (at AAMAS-13)}]. In this framework, a teacher agent instructs a student agent by suggesting actions the student should take as it learns. However, the teacher may only give such advice a limited number of times. We present several novel algorithms that teachers can use to budget their advice effectively, and we evaluate them in two complex video games: StarCraft and Pac-Man. Our results show that the same amount of advice, given at different moments, can have different effects on student learning, and that teachers can significantly affect student learning even when students use different learning methods and state representations.

An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Sadiig, I. Ahmed M. J.

2005-01-01

The traditional learning paradigm involving face-to-face interaction with students is shifting to highly data-intensive electronic learning with the advances in Information and Communication Technology. An important component of the e-learning process is the delivery of the learning contents to their intended audience over a network. A distributed…

Do Intelligent Robots Need Emotion?

PubMed

Pessoa, Luiz

2017-11-01

What is the place of emotion in intelligent robots? Researchers have advocated the inclusion of some emotion-related components in the information-processing architecture of autonomous agents. It is argued here that emotion needs to be merged with all aspects of the architecture: cognitive-emotional integration should be a key design principle. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Development of Mirror Self-Recognition in Different Sociocultural Contexts

ERIC Educational Resources Information Center

Kartner, Joscha; Keller, Heidi; Chaudhary, Nandita; Yovsi, Relindis D.

2012-01-01

The overarching goal of the present study was to trace the development of mirror self-recognition (MSR), as an index of toddlers' sense of themselves and others as autonomous intentional agents, in different sociocultural environments. A total of 276 toddlers participated in the present study. Toddlers were either 16, 17, 18, 19, 20, or 21 months…

Questioning the Idea of the Individual as an Autonomous Moral Agent

ERIC Educational Resources Information Center

Bowers, C. A.

2012-01-01

This paper examines ways in which current moral values are influenced by earlier patterns of thinking carried forward in root metaphors whose meanings were often framed by the analogues settled upon in the past by thinkers who were influenced by the silences and prejudices of their culture. It is argued that such tacitly inherited metaphors…

Agents of Possibility: Examining the Intersections of Art, Education, and Activism in Communities

ERIC Educational Resources Information Center

Campana, Alina

2011-01-01

Some art educators working in communities exemplify an alternative to the more common and stereotypical notion of the artist as autonomous, self-focused, and neutral. They view artmaking and education as vehicles for social justice and, in some cases, for social and political activism. In these broader social functions, the boundaries between art,…

Decentralized Planning for Autonomous Agents Cooperating in Complex Missions

DTIC Science & Technology

2010-09-01

Consensus - based decentralized auctions for robust task allocation ," IEEE Transactions on Robotics...Robotics, vol. 24, pp. 209-222, 2006. [44] H.-L. Choi, L. Brunet, and J. P. How, " Consensus - based decentralized auctions for robust task allocation ...2003. 123 [31] L. Brunet, " Consensus - Based Auctions for Decentralized Task Assignment," Master’s thesis, Dept.

Perturbed Communication in a Virtual Environment to Train Medical Team Leaders.

PubMed

Huguet, Lauriane; Lourdeaux, Domitile; Sabouret, Nicolas; Ferrer, Marie-Hélène

2016-01-01

The VICTEAMS project aims at designing a virtual environment for training medical team leaders to non-technical skills. The virtual environment is populated with autonomous virtual agents who are able to make mistakes (in action or communication) in order to train rescue team leaders and to make them adaptive with all kinds of situations or teams.

Global analysis of tomato gene expression during potato spindle tuber viroid infection reveals a complex array of changes affecting hormone signaling

USDA-ARS?s Scientific Manuscript database

Viroids are the smallest known agents of infectious disease – small, single-stranded, highly structured, circular RNAs that lack detectable messenger RNA activity yet are able to replicate autonomously in susceptible plant species. Potato spindle tuber viroid (PSTVd) infection in tomato is accompan...

Remote Control and Children's Understanding of Robots

ERIC Educational Resources Information Center

Somanader, Mark C.; Saylor, Megan M.; Levin, Daniel T.

2011-01-01

Children use goal-directed motion to classify agents as living things from early in infancy. In the current study, we asked whether preschoolers are flexible in their application of this criterion by introducing them to robots that engaged in goal-directed motion. In one case the robot appeared to move fully autonomously, and in the other case it…

Multiagent pursuit-evasion games: Algorithms and experiments

NASA Astrophysics Data System (ADS)

Kim, Hyounjin

Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such as high level pursuit policy computation, inter-agent communication, navigation, sensing, and regulation. We present both simulation and experimental results on real pursuit-evasion games between our fleet of UAVs and UGVs and evaluate the pursuit policies, relating expected capture times to the speed and intelligence of the evaders and the sensing capabilities of the pursuers. The architecture and algorithmsis described in this dissertation are general enough to be applied to many real-world applications.

Further Structural Intelligence for Sensors Cluster Technology in Manufacturing

PubMed Central

Mekid, Samir

2006-01-01

With the ever increasing complex sensing and actuating tasks in manufacturing plants, intelligent sensors cluster in hybrid networks becomes a rapidly expanding area. They play a dominant role in many fields from macro and micro scale. Global object control and the ability to self organize into fault-tolerant and scalable systems are expected for high level applications. In this paper, new structural concepts of intelligent sensors and networks with new intelligent agents are presented. Embedding new functionalities to dynamically manage cooperative agents for autonomous machines are interesting key enabling technologies most required in manufacturing for zero defects production.

A programmable palm-size gas analyzer for use in micro-autonomous systems

NASA Astrophysics Data System (ADS)

Gordenker, Robert J. M.; Wise, Kensall D.

2012-06-01

Gas analysis systems having small size, low power, and high selectivity are badly needed for defense (detection of explosives and chemical warfare agents), homeland security, health care, and environmental applications. This paper presents a palm-size gas chromatography system having analysis times of 5-50sec, detection limits less than 1ppb, and an average power dissipation less than one watt. It uses no consumables. The three-chip fluidic system consists of a preconcentrator, a 25cm-3m separation column, and a chemi-resistive detector and is supported by a microcomputer and circuitry for programmable temperature control. The entire system, including the mini-pump and battery, occupies less than 200cc and is configured for use on autonomous robotic vehicles.

Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.

PubMed

Cowlagi, Raghvendra V; Tsiotras, Panagiotis

2012-10-01

We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.

ANTS: Applying A New Paradigm for Lunar and Planetary Exploration

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.

2002-01-01

ANTS (Autonomous Nano- Technology Swarm), a mission architecture consisting of a large (1000 member) swarm of picoclass (1 kg) totally autonomous spacecraft with both adaptable and evolvable heuristic systems, is being developed as a NASA advanced mission concept, and is here examined as a paradigm for lunar surface exploration. As the capacity and complexity of hardware and software, demands for bandwidth, and the sophistication of goals for lunar and planetary exploration have increased, greater cost constraints have led to fewer resources and thus, the need to operate spacecraft with less frequent human contact. At present, autonomous operation of spacecraft systems allows great capability of spacecraft to 'safe' themselves and survive when conditions threaten spacecraft safety. To further develop spacecraft capability, NASA is at the forefront of development of new mission architectures which involve the use of Intelligent Software Agents (ISAs), performing experiments in space and on the ground to advance deliberative and collaborative autonomous control techniques. Selected missions in current planning stages require small groups of spacecraft weighing tens, instead of hundreds, of kilograms to cooperate at a tactical level to select and schedule measurements to be made by appropriate instruments onboard. Such missions will be characterizing rapidly unfolding real-time events on a routine basis. The next level of development, which we are considering here, is in the use of autonomous systems at the strategic level, to explore the remote terranes, potentially involving large surveys or detailed reconnaissance.

Diagnosing and treating neurogenic orthostatic hypotension in primary care.

PubMed

Kuritzky, Louis; Espay, Alberto J; Gelblum, Jeffrey; Payne, Richard; Dietrich, Eric

2015-01-01

In response to a change in posture from supine or sitting to standing, autonomic reflexes normally maintain blood pressure (BP) by selective increases in arteriovenous resistance and by increased cardiac output, ensuring continued perfusion of the central nervous system. In neurogenic orthostatic hypotension (NOH), inadequate vasoconstriction and cardiac output cause BP to drop excessively, resulting in inadequate perfusion, with predictable symptoms such as dizziness, lightheadedness and falls. The condition may represent a central failure of baroreceptor signals to modulate cardiovascular function, a peripheral failure of norepinephrine release from cardiovascular sympathetic nerve endings, or both. Symptomatic patients may benefit from both non-pharmacologic and pharmacologic interventions. Among the latter, two pressor agents have been approved by the US Food and Drug Administration: the sympathomimetic prodrug midodrine, approved in 1996 for symptomatic orthostatic hypotension, and the norepinephrine prodrug droxidopa, approved in 2014, which is indicated for the treatment of symptomatic neurogenic orthostatic hypotension caused by primary autonomic failure (Parkinson's disease, multiple system atrophy and pure autonomic failure). A wide variety of off-label options also have been described (e.g. the synthetic mineralocorticoid fludrocortisone). Because pressor agents may promote supine hypertension, NOH management requires monitoring of supine BP and also lifestyle measures to minimize supine BP increases (e.g. head-of-bed elevation). However, NOH has been associated with cognitive impairment and increases a patient's risk of syncope and falls, with the potential for serious consequences. Hence, concerns about supine hypertension - for which the long-term prognosis in patients with NOH is yet to be established - must sometimes be balanced by the need to address a patient's immediate risks.

Long-term neurological and neuropsychological complications of sulfur mustard and Lewisite mixture poisoning in Chinese victims exposed to chemical warfare agents abandoned at the end of WWII.

PubMed

Isono, O; Kituda, A; Fujii, M; Yoshinaka, T; Nakagawa, G; Suzuki, Y

2018-09-01

In August 2003, 44 victims were poisoned by chemical warfare agents (CWAs) leaked from five drums that were excavated at a construction site in Qiqihar, Northeast China. The drums were abandoned by the former Japanese imperial army during World War II and contained a mixture of Sulfur mustard (SM) and Lewisite. We carried out a total of six regular check-ups between 2006 and 2014, and from 2008 we added neurological evaluations including neuropsychological test and autonomic nervous function test in parallel with medical follow-up as much as was possible. Severe autonomic failure, such as hyperhidrosis, pollakiuria, diarrhoea, diminished libido, and asthenia appeared in almost all victims. Polyneuropathy occurred in 35% of the victims and constricted vision occurred in 20% of them. The rates of abnormal response on cold pressor test (CPT), active standing test (AST), Heart rate variability (CV R-R ), performed in 2014, were 63.1%, 31.6%, and 15.9%, respectively. On neuropsychological testing evaluated in 2010, a generalized cognitive decline was observed in 42% of the victims. Memories and visuospatial abilities were affected in the remaining victims. Finally, a 17-item PTSD questionnaire and the Beck Depression Inventory evaluated in 2014 revealed long-lasting severe PTSD symptoms and depression of the victims. Our findings suggest that an SM/Lewisite compound have significant adverse consequences directly in cognitive and emotional network and autonomic nervous systems in the brain. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiagent cooperation and competition with deep reinforcement learning.

PubMed

Tampuu, Ardi; Matiisen, Tambet; Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments.

Phenomenological modelling of self-healing polymers based on integrated healing agents

NASA Astrophysics Data System (ADS)

Mergheim, Julia; Steinmann, Paul

2013-09-01

The present contribution introduces a phenomenological model for self-healing polymers. Self-healing polymers are a promising class of materials which mimic nature by their capability to autonomously heal micro-cracks. This self-healing is accomplished by the integration of microcapsules containing a healing agent and a dispersed catalyst into the matrix material. Propagating microcracks may then break the capsules which releases the healing agent into the microcracks where it polymerizes with the catalyst, closes the crack and 'heals' the material. The present modelling approach treats these processes at the macroscopic scale, the microscopic details of crack propagation and healing are thus described by means of continuous damage and healing variables. The formulation of the healing model accounts for the fact that healing is directly associated with the curing process of healing agent and catalyst. The model is implemented and its capabilities are studied by means of numerical examples.

Towards a mathematical theory of meaningful communication

NASA Astrophysics Data System (ADS)

Corominas-Murtra, Bernat; Fortuny, Jordi; Solé, Ricard V.

2014-04-01

Meaning has been left outside most theoretical approaches to information in biology. Functional responses based on an appropriate interpretation of signals have been replaced by a probabilistic description of correlations between emitted and received symbols. This assumption leads to potential paradoxes, such as the presence of a maximum information associated to a channel that creates completely wrong interpretations of the signals. Game-theoretic models of language evolution and other studies considering embodied communicating agents show that the correct (meaningful) match resulting from agent-agent exchanges is always achieved and natural systems obviously solve the problem correctly. Inspired by the concept of duality of the communicative sign stated by the swiss linguist Ferdinand de Saussure, here we present a complete description of the minimal system necessary to measure the amount of information that is consistently decoded. Several consequences of our developments are investigated, such as the uselessness of a certain amount of information properly transmitted for communication among autonomous agents.

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

Multiagent cooperation and competition with deep reinforcement learning

PubMed Central

Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments. PMID:28380078

L-dihydroxyphenylserine (Droxidopa) in the treatment of orthostatic hypotension: the European experience.

PubMed

Mathias, Christopher J

2008-03-01

Neurogenic orthostatic hypotension is a cardinal feature of generalised autonomic failure and commonly is the presenting sign in patients with primary autonomic failure. Orthostatic hypotension can result in considerable morbidity and even mortality and is a major management problem in disorders such as pure autonomic failure, multiple system atrophy and also in Parkinson's disease. Treatment is ideally two pronged, using non-pharmacological and pharmacological measures. Drug treatment ideally is aimed at restoring adequate amounts of the neurotransmitter noradrenaline. This often is not achievable because of damage to sympathetic nerve terminals, to autonomic ganglia or to central autonomic networks. An alternative is the use of sympathomimetics (that mimic the effects of noradrenaline, but are not identical to noradrenaline), in addition to other agents that target physiological mechanisms that contribute to blood pressure control.L-threo-dihydroxyphenyslerine (Droxidopa) is a pro-drug which has a structure similar to noradrenaline, but with a carboxyl group. It has no pressor effects in this form. It can be administered orally, unlike noradrenaline, and after absorption is converted by the enzyme dopa decarboxylase into noradrenaline thus increasing levels of the neurotransmitter which is identical to endogenous noradrenaline. Experience in Caucasians and in Europe is limited mainly to patients with dopamine beta hydroxylase deficiency. This review focuses on two studies performed in Europe, and provides information on its efficacy, tolerability and safety in patients with pure autonomic failure, multiple system atrophy and Parkinson's disease. It also addresses the issue of whether addition of dopa decarboxylase inhibitors, when combined with l-dopa in the treatment of the motor deficit in Parkinson's disease, impairs the pressor efficacy of Droxidopa.

Collective motion patterns of swarms with delay coupling: Theory and experiment.

PubMed

Szwaykowska, Klementyna; Schwartz, Ira B; Mier-Y-Teran Romero, Luis; Heckman, Christoffer R; Mox, Dan; Hsieh, M Ani

2016-03-01

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Breitman, Karin Koogan; Filho, Aluizio Haendchen; Haeusler, Edward Hermann

2004-01-01

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

Collective motion patterns of swarms with delay coupling: Theory and experiment

NASA Astrophysics Data System (ADS)

Szwaykowska, Klementyna; Schwartz, Ira B.; Mier-y-Teran Romero, Luis; Heckman, Christoffer R.; Mox, Dan; Hsieh, M. Ani

2016-03-01

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

Multi-Agent Diagnosis and Control of an Air Revitalization System for Life Support in Space

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Kowing, Jeffrey; Nieten, Joseph; Graham, Jeffrey s.; Schreckenghost, Debra; Bonasso, Pete; Fleming, Land D.; MacMahon, Matt; Thronesbery, Carroll

2000-01-01

An architecture of interoperating agents has been developed to provide control and fault management for advanced life support systems in space. In this adjustable autonomy architecture, software agents coordinate with human agents and provide support in novel fault management situations. This architecture combines the Livingstone model-based mode identification and reconfiguration (MIR) system with the 3T architecture for autonomous flexible command and control. The MIR software agent performs model-based state identification and diagnosis. MIR identifies novel recovery configurations and the set of commands required for the recovery. The AZT procedural executive and the human operator use the diagnoses and recovery recommendations, and provide command sequencing. User interface extensions have been developed to support human monitoring of both AZT and MIR data and activities. This architecture has been demonstrated performing control and fault management for an oxygen production system for air revitalization in space. The software operates in a dynamic simulation testbed.

Scheduling lessons learned from the Autonomous Power System

NASA Technical Reports Server (NTRS)

Ringer, Mark J.

1992-01-01

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

Monitoring Agents for Assisting NASA Engineers with Shuttle Ground Processing

NASA Technical Reports Server (NTRS)

Semmel, Glenn S.; Davis, Steven R.; Leucht, Kurt W.; Rowe, Danil A.; Smith, Kevin E.; Boeloeni, Ladislau

2005-01-01

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has designed, developed, and deployed a rule-based agent to monitor the Space Shuttle's ground processing telemetry stream. The NASA Engineering Shuttle Telemetry Agent increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when user defined conditions are satisfied. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the agent's rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules within this domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This chapter discusses the rule-based telemetry agent used for Space Shuttle ground processing. We present the problem domain along with design and development considerations such as information modeling, knowledge capture, and the deployment of the product. We also present ongoing work with other condition monitoring agents.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar.

PubMed

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K U; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar , which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar

PubMed Central

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K. U.; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar, which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs. PMID:27853431

Time-Extended Payoffs for Collectives of Autonomous Agents

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2002-01-01

A collective is a set of self-interested agents which try to maximize their own utilities, along with a a well-defined, time-extended world utility function which rates the performance of the entire system. In this paper, we use theory of collectives to design time-extended payoff utilities for agents that are both aligned with the world utility, and are "learnable", i.e., the agents can readily see how their behavior affects their utility. We show that in systems where each agent aims to optimize such payoff functions, coordination arises as a byproduct of the agents selfishly pursuing their own goals. A game theoretic analysis shows that such payoff functions have the net effect of aligning the Nash equilibrium, Pareto optimal solution and world utility optimum, thus eliminating undesirable behavior such as agents working at cross-purposes. We then apply collective-based payoff functions to the token collection in a gridworld problem where agents need to optimize the aggregate value of tokens collected across an episode of finite duration (i.e., an abstracted version of rovers on Mars collecting scientifically interesting rock samples, subject to power limitations). We show that, regardless of the initial token distribution, reinforcement learning agents using collective-based payoff functions significantly outperform both natural extensions of single agent algorithms and global reinforcement learning solutions based on "team games".

FY08 Chemical Synthesis for the Self-Decontaminating Coatings Project

DTIC Science & Technology

2013-08-01

These synthesized materials consist of Boltorn hyperbranched polymers that are functionalized with hydantoin, alkyl, and perfluorinated groups. 15...envisioned that completely prevents sorption of chemical agents, enables autonomous decontamination, reduces the volume of cleaning solution...modified with perfluorinated octanoic acid (PFOA), lauric acid, and a hydantoin moiety. HO OH CH3 HO O 3 Figure 2. Synthetic targets 1–3

Machine Learning Control For Highly Reconfigurable High-Order Systems

DTIC Science & Technology

2015-01-02

develop and flight test a Reinforcement Learning based approach for autonomous tracking of ground targets using a fixed wing Unmanned...Reinforcement Learning - based algorithms are developed for learning agents’ time dependent dynamics while also learning to control them. Three algorithms...to a wide range of engineering- based problems . Implementation of these solutions, however, is often complicated by the hysteretic, non-linear,

Mobile Agents for Battlespace Information Exchange

DTIC Science & Technology

2013-05-01

autonomously gather information and coordinate activities (e.g. meetings, e - commerce transactions) on behalf of their owners. Sometime in the...operations where consumer -level infrastructure is not available. The report provides an overview of MA characteristics and follows with a description of...detection for security, telecommunications and the military. With the advent of broadband communication (fixed and wireless) a typical consumer is now

A method for integrating multiple components in a decision support system

Treesearch

Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2005-01-01

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...

Integrating planning, execution, and learning

NASA Technical Reports Server (NTRS)

Kuokka, Daniel R.

1989-01-01

To achieve the goal of building an autonomous agent, the usually disjoint capabilities of planning, execution, and learning must be used together. An architecture, called MAX, within which cognitive capabilities can be purposefully and intelligently integrated is described. The architecture supports the codification of capabilities as explicit knowledge that can be reasoned about. In addition, specific problem solving, learning, and integration knowledge is developed.

Modeling the Chagas’ disease after stem cell transplantation

NASA Astrophysics Data System (ADS)

Galvão, Viviane; Miranda, José Garcia Vivas

2009-04-01

A recent model for Chagas’ disease after stem cell transplantation is extended for a three-dimensional multi-agent-based model. The computational model includes six different types of autonomous agents: inflammatory cell, fibrosis, cardiomyocyte, proinflammatory cytokine tumor necrosis factor- α, Trypanosoma cruzi, and bone marrow stem cell. Only fibrosis is fixed and the other types of agents can move randomly through the empty spaces using the three-dimensional Moore neighborhood. Bone marrow stem cells can promote apoptosis in inflammatory cells, fibrosis regression and can differentiate in cardiomyocyte. T. cruzi can increase the number of inflammatory cells. Inflammatory cells and tumor necrosis factor- α can increase the quantity of fibrosis. Our results were compared with experimental data giving a fairly fit and they suggest that the inflammatory cells are important for the development of fibrosis.

Cell theory, specificity, and reproduction, 1837-1870.

PubMed

Müller-Wille, Staffan

2010-09-01

The cell is not only the structural, physiological, and developmental unit of life, but also the reproductive one. So far, however, this aspect of the cell has received little attention from historians and philosophers of biology. I will argue that cell theory had far-reaching consequences for how biologists conceptualized the reproductive relationships between germs and adult organisms. Cell theory, as formulated by Theodor Schwann in 1839, implied that this relationship was a specific and lawful one, that is, that germs of a certain kind, all else being equal, would produce adult organisms of the same kind, and vice versa. Questions of preformation and epigenesis took on a new meaning under this presupposition. The question then became one of whether cells could be considered as autonomous agents producing adult organisms of a given species, or whether they were the product of external, organizing forces and thus only a stage in the development of the whole organism. This question became an important issue for nineteenth-century biology. As I will demonstrate, it was the view of cells as autonomous agents which helped both Charles Darwin and Gregor Mendel to think of inheritance as a lawful process. Copyright © 2010 Elsevier Ltd. All rights reserved.

Detecting the activation of a self-healing mechanism in concrete by acoustic emission and digital image correlation.

PubMed

Tsangouri, E; Aggelis, D G; Van Tittelboom, K; De Belie, N; Van Hemelrijck, D

2013-01-01

Autonomous crack healing in concrete is obtained when encapsulated healing agent is embedded into the material. Cracking damage in concrete elements ruptures the capsules and activates the healing process by healing agent release. Previously, the strength and stiffness recovery as well as the sealing efficiency after autonomous crack repair was well established. However, the mechanisms that trigger capsule breakage remain unknown. In parallel, the conditions under which the crack interacts with embedded capsules stay black-box. In this research, an experimental approach implementing an advanced optical and acoustic method sets up scopes to monitor and justify the crack formation and capsule breakage of concrete samples tested under three-point bending. Digital Image Correlation was used to visualize the crack opening. The optical information was the basis for an extensive and analytical study of the damage by Acoustic Emission analysis. The influence of embedding capsules on the concrete fracture process, the location of capsule damage, and the differentiation between emissions due to capsule rupture and crack formation are presented in this research. A profound observation of the capsules performance provides a clear view of the healing activation process.

Detecting the Activation of a Self-Healing Mechanism in Concrete by Acoustic Emission and Digital Image Correlation

PubMed Central

Tsangouri, E.; Aggelis, D. G.; Van Tittelboom, K.; De Belie, N.; Van Hemelrijck, D.

2013-01-01

Autonomous crack healing in concrete is obtained when encapsulated healing agent is embedded into the material. Cracking damage in concrete elements ruptures the capsules and activates the healing process by healing agent release. Previously, the strength and stiffness recovery as well as the sealing efficiency after autonomous crack repair was well established. However, the mechanisms that trigger capsule breakage remain unknown. In parallel, the conditions under which the crack interacts with embedded capsules stay black-box. In this research, an experimental approach implementing an advanced optical and acoustic method sets up scopes to monitor and justify the crack formation and capsule breakage of concrete samples tested under three-point bending. Digital Image Correlation was used to visualize the crack opening. The optical information was the basis for an extensive and analytical study of the damage by Acoustic Emission analysis. The influence of embedding capsules on the concrete fracture process, the location of capsule damage, and the differentiation between emissions due to capsule rupture and crack formation are presented in this research. A profound observation of the capsules performance provides a clear view of the healing activation process. PMID:24381518

A Software Product Line Process to Develop Agents for the IoT

PubMed Central

Ayala, Inmaculada; Amor, Mercedes; Fuentes, Lidia; Troya, José M.

2015-01-01

One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes. PMID:26140350

Sensor supervision and multiagent commanding by means of projective virtual reality

NASA Astrophysics Data System (ADS)

Rossmann, Juergen

1998-10-01

When autonomous systems with multiple agents are considered, conventional control- and supervision technologies are often inadequate because the amount of information available is often presented in a way that the user is effectively overwhelmed by the displayed data. New virtual reality (VR) techniques can help to cope with this problem, because VR offers the chance to convey information in an intuitive manner and can combine supervision capabilities and new, intuitive approaches to the control of autonomous systems. In the approach taken, control and supervision issues were equally stressed and finally led to the new ideas and the general framework for Projective Virtual Reality. The key idea of this new approach for an intuitively operable man machine interface for decentrally controlled multi-agent systems is to let the user act in the virtual world, detect the changes and have an action planning component automatically generate task descriptions for the agents involved to project actions that have been carried out by users in the virtual world into the physical world, e.g. with the help of robots. Thus the Projective Virtual Reality approach is to split the job between the task deduction in the VR and the task `projection' onto the physical automation components by the automatic action planning component. Besides describing the realized projective virtual reality system, the paper will also describe in detail the metaphors and visualization aids used to present different types of (e.g. sensor-) information in an intuitively comprehensible manner.

Mario Becomes Cognitive.

PubMed

Schrodt, Fabian; Kneissler, Jan; Ehrenfeld, Stephan; Butz, Martin V

2017-04-01

In line with Allen Newell's challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents' behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences. Copyright © 2017 Cognitive Science Society, Inc.

Multiagent data warehousing and multiagent data mining for cerebrum/cerebellum modeling

NASA Astrophysics Data System (ADS)

Zhang, Wen-Ran

2002-03-01

An algorithm named Neighbor-Miner is outlined for multiagent data warehousing and multiagent data mining. The algorithm is defined in an evolving dynamic environment with autonomous or semiautonomous agents. Instead of mining frequent itemsets from customer transactions, the new algorithm discovers new agents and mining agent associations in first-order logic from agent attributes and actions. While the Apriori algorithm uses frequency as a priory threshold, the new algorithm uses agent similarity as priory knowledge. The concept of agent similarity leads to the notions of agent cuboid, orthogonal multiagent data warehousing (MADWH), and multiagent data mining (MADM). Based on agent similarities and action similarities, Neighbor-Miner is proposed and illustrated in a MADWH/MADM approach to cerebrum/cerebellum modeling. It is shown that (1) semiautonomous neurofuzzy agents can be identified for uniped locomotion and gymnastic training based on attribute relevance analysis; (2) new agents can be discovered and agent cuboids can be dynamically constructed in an orthogonal MADWH, which resembles an evolving cerebrum/cerebellum system; and (3) dynamic motion laws can be discovered as association rules in first order logic. Although examples in legged robot gymnastics are used to illustrate the basic ideas, the new approach is generally suitable for a broad category of data mining tasks where knowledge can be discovered collectively by a set of agents from a geographically or geometrically distributed but relevant environment, especially in scientific and engineering data environments.

Evolution of a multi-agent system in a cyclical environment.

PubMed

Baptista, Tiago; Costa, Ernesto

2008-06-01

The synchronisation phenomena in biological systems is a current and recurring subject of scientific study. This topic, namely that of circadian clocks, served as inspiration to develop an agent-based simulation that serves the main purpose of being a proof-of-concept of the model used in the BitBang framework, that implements a modern autonomous agent model. Despite having been extensively studied, circadian clocks still have much to be investigated. Rather than wanting to learn more about the internals of this biological process, we look to study the emergence of this kind of adaptation to a daily cycle. To that end we implemented a world with a day/night cycle, and analyse the ways the agents adapt to that cycle. The results show the evolution of the agents' ability to gather food. If we look at the total number of agents over the course of an experiment, we can pinpoint the time when reproductive technology emerges. We also show that the agents adapt to the daily cycle. This circadian rhythm can be shown by analysing the variation on the agents metabolic rate, which is affected by the variation of their movement patterns. In the experiments conducted we can observe that the metabolic rate of the agents varies according to the daily cycle.

Behavior believability in virtual worlds: agents acting when they need to.

PubMed

Avradinis, Nikos; Panayiotopoulos, Themis; Anastassakis, George

2013-12-01

Believability has been a perennial goal for the intelligent virtual agent community. One important aspect of believability largely consists in demonstrating autonomous behavior, consistent with the agent's personality and motivational state, as well as the world conditions. Autonomy, on behalf of the agent, implies the existence of an internal structure and mechanism that allows the agent to have its own needs and interests, based on which the agent will dynamically select and generate goals that will in turn lead to self-determined behavior. Intrinsic motivation allows the agent to function and demonstrate behavior, even when no external stimulus is present, due to the constant change of its internal emotional and physiological state. The concept of motivation has already been investigated by research works on intelligent agents, trying to achieve autonomy. The current work presents an architecture and model to represent and manage internal driving factors in intelligent virtual agents, using the concept of motivations. Based on Maslow and Alderfer's bio-psychological needs theories, we present a motivational approach to represent human needs and produce emergent behavior through motivation synthesis. Particular attention is given to basic, physiological level needs, which are the basis of behavior and can produce tendency to action even when there is no other interaction with the environment.

Model Checking the Remote Agent Planner

NASA Technical Reports Server (NTRS)

Khatib, Lina; Muscettola, Nicola; Havelund, Klaus; Norvig, Peter (Technical Monitor)

2001-01-01

This work tackles the problem of using Model Checking for the purpose of verifying the HSTS (Scheduling Testbed System) planning system. HSTS is the planner and scheduler of the remote agent autonomous control system deployed in Deep Space One (DS1). Model Checking allows for the verification of domain models as well as planning entries. We have chosen the real-time model checker UPPAAL for this work. We start by motivating our work in the introduction. Then we give a brief description of HSTS and UPPAAL. After that, we give a sketch for the mapping of HSTS models into UPPAAL and we present samples of plan model properties one may want to verify.

Quantum Behavior of an Autonomous Maxwell Demon

NASA Astrophysics Data System (ADS)

Chapman, Adrian; Miyake, Akimasa

2015-03-01

A Maxwell Demon is an agent that can exploit knowledge of a system's microstate to perform useful work. The second law of thermodynamics is only recovered upon taking into account the work required to irreversibly update the demon's memory, bringing information theoretic concepts into a thermodynamic framework. Recently, there has been interest in modeling a classical Maxwell demon as an autonomous physical system to study this information-work tradeoff explicitly. Motivated by the idea that states with non-local entanglement structure can be used as a computational resource, we ask whether these states have thermodynamic resource quality as well by generalizing a particular classical autonomous Maxwell demon to the quantum regime. We treat the full quantum description using a matrix product operator formalism, which allows us to handle quantum and classical correlations in a unified framework. Applying this, together with techniques from statistical mechanics, we are able to approximate nonlocal quantities such as the erasure performed on the demon's memory register when correlations are present. Finally, we examine how the demon may use these correlations as a resource to outperform its classical counterpart.

Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles

NASA Technical Reports Server (NTRS)

Wolf, Michael; Kuwata, Yoshiaki; Zarzhitsky, Dimitri V.

2013-01-01

This software implements a motion-planning module for a maritime autonomous surface vehicle (ASV). The module trails a given target while also avoiding static and dynamic surface hazards. When surface hazards are other moving boats, the motion planner must apply International Regulations for Avoiding Collisions at Sea (COLREGS). A key subset of these rules has been implemented in the software. In case contact with the target is lost, the software can receive and follow a "reacquisition route," provided by a complementary system, until the target is reacquired. The programmatic intention is that the trailed target is a submarine, although any mobile naval platform could serve as the target. The algorithmic approach to combining motion with a (possibly moving) goal location, while avoiding local hazards, may be applicable to robotic rovers, automated landing systems, and autonomous airships. The software operates in JPL s CARACaS (Control Architecture for Robotic Agent Command and Sensing) software architecture and relies on other modules for environmental perception data and information on the predicted detectability of the target, as well as the low-level interface to the boat controls.

A linguistic geometry for 3D strategic planning

NASA Technical Reports Server (NTRS)

Stilman, Boris

1995-01-01

This paper is a new step in the development and application of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing Linguistic Geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in this paper on the new pilot example of the solution of the extremely complex 3D optimization problem of strategic planning for the space combat of autonomous vehicles. This example demonstrates deep and highly selective search in comparison with conventional search algorithms.

Distributed Cognition on the road: Using EAST to explore future road transportation systems.

PubMed

Banks, Victoria A; Stanton, Neville A; Burnett, Gary; Hermawati, Setia

2018-04-01

Connected and Autonomous Vehicles (CAV) are set to revolutionise the way in which we use our transportation system. However, we do not fully understand how the integration of wireless and autonomous technology into the road transportation network affects overall network dynamism. This paper uses the theoretical principles underlying Distributed Cognition to explore the dependencies and interdependencies that exist between system agents located within the road environment, traffic management centres and other external agencies in both non-connected and connected transportation systems. This represents a significant step forward in modelling complex sociotechnical systems as it shows that the principles underlying Distributed Cognition can be applied to macro-level systems using the visual representations afforded by the Event Analysis of Systemic Teamwork (EAST) method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation Components

DTIC Science & Technology

2006-09-01

groupings such as mathematical , 3-dimensional and process models. Furthermore, one must remain aware of the potential to use or reuse models (or...semi-autonomous forces (SAF), intelligent forces (IFOR), command forces (CFOR), command agents (CA) and many more like terms. One way of looking at...the effective use of SEs within Europe. One element of the SEDEP is the use of generalised wording and definitions so as to not be solely dedicated

Sense of place: An elusive concept that is finding a home in ecosystem management

Treesearch

Daniel R. Williams; Susan I. Stewart

1998-01-01

One of the great and largely unmet challenges associated with ecosystem management is treating people as a rightful part of ecosystems. In many ecosystem models, despite occasional rhetoric to the contrary, there is still a tendency to treat people as autonomous individual agents outside the ecosystem, at best a source of values to be incorporated into decisions, at...

Designing for Humans in Autonomous Systems: Military Applications

DTIC Science & Technology

2014-01-01

attentional control, and gaming experience are important determinants of how well humans interact with agents supervising multiple assets . 6 4...mission performance, operator workload, trust, SA, and, most important , how they affected human safety. The initial experiments were conducted in a...that humans can also play an important role by being able to identify these objects (perception by proxy). Therefore, human involvement is useful

Computational memory architectures for autobiographic agents interacting in a complex virtual environment: a working model

NASA Astrophysics Data System (ADS)

Ho, Wan Ching; Dautenhahn, Kerstin; Nehaniv, Chrystopher

2008-03-01

In this paper, we discuss the concept of autobiographic agent and how memory may extend an agent's temporal horizon and increase its adaptability. These concepts are applied to an implementation of a scenario where agents are interacting in a complex virtual artificial life environment. We present computational memory architectures for autobiographic virtual agents that enable agents to retrieve meaningful information from their dynamic memories which increases their adaptation and survival in the environment. The design of the memory architectures, the agents, and the virtual environment are described in detail. Next, a series of experimental studies and their results are presented which show the adaptive advantage of autobiographic memory, i.e. from remembering significant experiences. Also, in a multi-agent scenario where agents can communicate via stories based on their autobiographic memory, it is found that new adaptive behaviours can emerge from an individual's reinterpretation of experiences received from other agents whereby higher communication frequency yields better group performance. An interface is described that visualises the memory contents of an agent. From an observer perspective, the agents' behaviours can be understood as individually structured, and temporally grounded, and, with the communication of experience, can be seen to rely on emergent mixed narrative reconstructions combining the experiences of several agents. This research leads to insights into how bottom-up story-telling and autobiographic reconstruction in autonomous, adaptive agents allow temporally grounded behaviour to emerge. The article concludes with a discussion of possible implications of this research direction for future autobiographic, narrative agents.

Semiotics and agents for integrating and navigating through multimedia representations of concepts

NASA Astrophysics Data System (ADS)

Joyce, Dan W.; Lewis, Paul H.; Tansley, Robert H.; Dobie, Mark R.; Hall, Wendy

1999-12-01

The purpose of this paper is two-fold. We begin by exploring the emerging trend to view multimedia information in terms of low-level and high-level components; the former being feature-based and the latter the 'semantics' intrinsic to what is portrayed by the media object. Traditionally, this has been viewed by employing analogies with generative linguistics. Recently, a new perceptive based on the semiotic tradition has been alluded to in several papers. We believe this to be a more appropriate approach. From this, we propose an approach for tackling this problem which uses an associative data structure expressing authored information together with intelligent agents acting autonomously over this structure. We then show how neural networks can be used to implement such agents. The agents act as 'vehicles' for bridging the gap between multimedia semantics and concrete expressions of high-level knowledge, but we suggest that traditional neural network techniques for classification are not architecturally adequate.

Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle

PubMed Central

Barriuso, Alberto L.; De Paz, Juan F.; Lozano, Álvaro

2018-01-01

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed. PMID:29301310

Design and testing of tubular polymeric capsules for self-healing of concrete

NASA Astrophysics Data System (ADS)

Araújo, M.; Van Tittelboom, K.; Feiteira, J.; Gruyaert, E.; Chatrabhuti, S.; Raquez, J.-M.; Šavija, B.; Alderete, N.; Schlangen, E.; De Belie, N.

2017-10-01

Polymeric healing agents have proven their efficiency to heal cracks in concrete in an autonomous way. However, the bottleneck for valorisation of self-healing concrete with polymeric healing agents is their encapsulation. In the present work, the suitability of polymeric materials such as poly(methyl methacrylate) (PMMA), polystyrene (PS) and poly(lactic acid) (PLA) as carriers for healing agents in self-healing concrete has been evaluated. The durability of the polymeric capsules in different environments (demineralized water, salt water and simulated concrete pore solution) and their compatibility with various healing agents have been assessed. Next, a numerical model was used to simulate capsule rupture when intersected by a crack in concrete and validated experimentally. Finally, two real-scale self-healing concrete beams were made, containing the selected polymeric capsules (with the best properties regarding resistance to concrete mixing and breakage upon crack formation) or glass capsules and a reference beam without capsules. The self-healing efficiency was determined after crack creation by 3-point-bending tests.

Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle.

PubMed

Barriuso, Alberto L; Villarrubia González, Gabriel; De Paz, Juan F; Lozano, Álvaro; Bajo, Javier

2018-01-02

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed.

I Feel You: The Design and Evaluation of a Domotic Affect-Sensitive Spoken Conversational Agent

PubMed Central

Lutfi, Syaheerah Lebai; Fernández-Martínez, Fernando; Lorenzo-Trueba, Jaime; Barra-Chicote, Roberto; Montero, Juan Manuel

2013-01-01

We describe the work on infusion of emotion into a limited-task autonomous spoken conversational agent situated in the domestic environment, using a need-inspired task-independent emotion model (NEMO). In order to demonstrate the generation of affect through the use of the model, we describe the work of integrating it with a natural-language mixed-initiative HiFi-control spoken conversational agent (SCA). NEMO and the host system communicate externally, removing the need for the Dialog Manager to be modified, as is done in most existing dialog systems, in order to be adaptive. The first part of the paper concerns the integration between NEMO and the host agent. The second part summarizes the work on automatic affect prediction, namely, frustration and contentment, from dialog features, a non-conventional source, in the attempt of moving towards a more user-centric approach. The final part reports the evaluation results obtained from a user study, in which both versions of the agent (non-adaptive and emotionally-adaptive) were compared. The results provide substantial evidences with respect to the benefits of adding emotion in a spoken conversational agent, especially in mitigating users' frustrations and, ultimately, improving their satisfaction. PMID:23945740

Magician Simulator: A Realistic Simulator for Heterogenous Teams of Autonomous Robots. MAGIC 2010 Challenge

DTIC Science & Technology

2011-02-07

Sensor UGVs (SUGV) or Disruptor UGVs, depending on their payload. The SUGVs included vision, GPS/IMU, and LIDAR systems for identifying and tracking...employed by all the MAGICian research groups. Objects of interest were tracked using standard LIDAR and Computer Vision template-based feature...tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous Locali- zation and Mapping ( SLAM ). Our system contains

Magician Simulator. A Realistic Simulator for Heterogenous Teams of Autonomous Robots

DTIC Science & Technology

2011-01-18

IMU, and LIDAR systems for identifying and tracking mobile OOI at long range (>20m), providing early warnings and allowing neutralization from a... LIDAR and Computer Vision template-based feature tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous...Locali- zation and Mapping ( SLAM ). Our system contains two maps, a physical map and an influence map (location of hostile OOI, explored and unexplored

Evaluating the Dynamics of Agent-Environment Interaction

DTIC Science & Technology

2001-05-01

a color sensor in the gripper, a radio transmitter/receiver for communication and data gathering, and an ultrasound /radio triangulation system for...Cooperative Mobile Robot Control’, Autonomous Robots 4(4), 387{403. Vaughan, R. T., Sty, K., Sukhatme, G. S. & Mataric, M. J. (2000), Whistling in the Dark...sensor in the gripper, a radio transmitter/receiver for communication and data gathering, and an ultrasound /radio triangu- lation system for

Emetic Mechanism in Acute Radiation Sickness

DTIC Science & Technology

1987-08-20

humans renders the subjects refractory to a wide variety of chemical emetic agents, now numbering more than 25 substances of both exogenous and endogenous...tractus solitarius with each of three neurons (shown as large triangles) in the nucleus of the tractus solitarius (NTS). These hells of NTS connect...Outputs are innervated through autonomic ganglia or by direct efferent connections. I4 Acute radiation-induced vomiting is generally typified by the

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

Designing and implementing transparency for real time inspection of autonomous robots

NASA Astrophysics Data System (ADS)

Theodorou, Andreas; Wortham, Robert H.; Bryson, Joanna J.

2017-07-01

The EPSRC's Principles of Robotics advises the implementation of transparency in robotic systems, however research related to AI transparency is in its infancy. This paper introduces the reader of the importance of having transparent inspection of intelligent agents and provides guidance for good practice when developing such agents. By considering and expanding upon other prominent definitions found in literature, we provide a robust definition of transparency as a mechanism to expose the decision-making of a robot. The paper continues by addressing potential design decisions developers need to consider when designing and developing transparent systems. Finally, we describe our new interactive intelligence editor, designed to visualise, develop and debug real-time intelligence.

Bidding-based autonomous process planning and scheduling

NASA Astrophysics Data System (ADS)

Gu, Peihua; Balasubramanian, Sivaram; Norrie, Douglas H.

1995-08-01

Improving productivity through computer integrated manufacturing systems (CIMS) and concurrent engineering requires that the islands of automation in an enterprise be completely integrated. The first step in this direction is to integrate design, process planning, and scheduling. This can be achieved through a bidding-based process planning approach. The product is represented in a STEP model with detailed design and administrative information including design specifications, batch size, and due dates. Upon arrival at the manufacturing facility, the product registered in the shop floor manager which is essentially a coordinating agent. The shop floor manager broadcasts the product's requirements to the machines. The shop contains autonomous machines that have knowledge about their functionality, capabilities, tooling, and schedule. Each machine has its own process planner and responds to the product's request in a different way that is consistent with its capabilities and capacities. When more than one machine offers certain process(es) for the same requirements, they enter into negotiation. Based on processing time, due date, and cost, one of the machines wins the contract. The successful machine updates its schedule and advises the product to request raw material for processing. The concept was implemented using a multi-agent system with the task decomposition and planning achieved through contract nets. The examples are included to illustrate the approach.

Intelligent agents: adaptation of autonomous bimodal microsystems

NASA Astrophysics Data System (ADS)

Smith, Patrice; Terry, Theodore B.

2014-03-01

Autonomous bimodal microsystems exhibiting survivability behaviors and characteristics are able to adapt dynamically in any given environment. Equipped with a background blending exoskeleton it will have the capability to stealthily detect and observe a self-chosen viewing area while exercising some measurable form of selfpreservation by either flying or crawling away from a potential adversary. The robotic agent in this capacity activates a walk-fly algorithm, which uses a built in multi-sensor processing and navigation subsystem or algorithm for visual guidance and best walk-fly path trajectory to evade capture or annihilation. The research detailed in this paper describes the theoretical walk-fly algorithm, which broadens the scope of spatial and temporal learning, locomotion, and navigational performances based on optical flow signals necessary for flight dynamics and walking stabilities. By observing a fly's travel and avoidance behaviors; and, understanding the reverse bioengineering research efforts of others, we were able to conceptualize an algorithm, which works in conjunction with decisionmaking functions, sensory processing, and sensorimotor integration. Our findings suggest that this highly complex decentralized algorithm promotes inflight or terrain travel mobile stability which is highly suitable for nonaggressive micro platforms supporting search and rescue (SAR), and chemical and explosive detection (CED) purposes; a necessity in turbulent, non-violent structured or unstructured environments.

eHive: an artificial intelligence workflow system for genomic analysis.

PubMed

Severin, Jessica; Beal, Kathryn; Vilella, Albert J; Fitzgerald, Stephen; Schuster, Michael; Gordon, Leo; Ureta-Vidal, Abel; Flicek, Paul; Herrero, Javier

2010-05-11

The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios. eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/.

Development of a Commercial Prototype of the Autonomous Pathogen Detection System Final Report CRADA No. TC-02077-04

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dzenitis, J. M.; Haigh, P.

This was a collaborative effort between The Regents of the University of California, Lawrence Livermore National Laboratory (LLNL), and GE Ion Track, Inc. (GEIT) to develop a commercial prototype of the Autonomous Pathogen Detection System (APDS), an instrument that monitors the air for all three biological threat agents (bacteria, viruses and toxins). This was originally a one year CRADA project, with the cost of the work at LLNL being funded by the Department of Homeland Security's Office of National Laboratories. The original project consisted of five major tasks and deliverables. The CRADA was then amended, converting the CRADA from amore » programmatically funded CRADA to a funds-in CRADA, extending the project for an additional 14 months, and adding four new tasks and deliverable to the project.« less

Software agents and the route to the information economy.

PubMed

Kephart, Jeffrey O

2002-05-14

Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

Cooperation in Human-Agent Systems to Support Resilience: A Microworld Experiment.

PubMed

Chiou, Erin K; Lee, John D

2016-09-01

This study uses a dyadic approach to understand human-agent cooperation and system resilience. Increasingly capable technology fundamentally changes human-machine relationships. Rather than reliance on or compliance with more or less reliable automation, we investigate interaction strategies with more or less cooperative agents. A joint-task microworld scenario was developed to explore the effects of agent cooperation on participant cooperation and system resilience. To assess the effects of agent cooperation on participant cooperation, 36 people coordinated with a more or less cooperative agent by requesting resources and responding to requests for resources in a dynamic task environment. Another 36 people were recruited to assess effects following a perturbation in their own hospital. Experiment 1 shows people reciprocated the cooperative behaviors of the agents; a low-cooperation agent led to less effective interactions and less resource sharing, whereas a high-cooperation agent led to more effective interactions and greater resource sharing. Experiment 2 shows that an initial fast-tempo perturbation undermined proactive cooperation-people tended to not request resources. However, the initial fast tempo had little effect on reactive cooperation-people tended to accept resource requests according to cooperation level. This study complements the supervisory control perspective of human-automation interaction by considering interdependence and cooperation rather than the more common focus on reliability and reliance. The cooperativeness of automated agents can influence the cooperativeness of human agents. Design and evaluation for resilience in teams involving increasingly autonomous agents should consider the cooperative behaviors of these agents. © 2016, Human Factors and Ergonomics Society.

Current and Novel Therapeutic Options for Irritable Bowel Syndrome Management

PubMed Central

Camilleri, Michael; Andresen, Viola

2009-01-01

Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder affecting up to 3-15% of the general population in western countries. It is characterized by unexplained abdominal pain, discomfort, and bloating in association with altered bowel habits. The pathophysiology of IBS is multifactorial involving disturbances of the brain-gut-axis. The pathophysiology provides the rationale for pharmacotherapy: abnormal gastrointestinal motor functions, visceral hypersensitivity, psychosocial factors, autonomic dysfunction, and mucosal immune activation. Understanding the mechanisms, and their mediators or modulators including neurotransmitters and receptors have led to several therapeutic approaches including agents acting on the serotonin receptor or serotonin transporter system, antidepressants, novel selective anticholinergics, α-adrenergic agonists, opioid agents, cholecystokinin-antagonists, neurokinin-antagonists, somatostatin receptor agonists, corticotropin releasing factor antagonists, chloride-channel activators, guanylate-cyclase-c agonists, melatonin, atypical benzodiazepines, antibiotics, immune modulators and probiotics. The mechanisms and current evidence regarding efficacy of these agents are reviewed. PMID:19665953

Agent-based modeling: a new approach for theory building in social psychology.

PubMed

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

A Spatial Cognitive Map and a Human-Like Memory Model Dedicated to Pedestrian Navigation in Virtual Urban Environments

NASA Astrophysics Data System (ADS)

Thomas, Romain; Donikian, Stéphane

Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.

Complex adaptive systems and game theory: An unlikely union

USGS Publications Warehouse

Hadzikadic, M.; Carmichael, T.; Curtin, C.

2010-01-01

A Complex Adaptive System is a collection of autonomous, heterogeneous agents, whose behavior is defined with a limited number of rules. A Game Theory is a mathematical construct that assumes a small number of rational players who have a limited number of actions or strategies available to them. The CAS method has the potential to alleviate some of the shortcomings of GT. On the other hand, CAS researchers are always looking for a realistic way to define interactions among agents. GT offers an attractive option for defining the rules of such interactions in a way that is both potentially consistent with observed real-world behavior and subject to mathematical interpretation. This article reports on the results of an effort to build a CAS system that utilizes GT for determining the actions of individual agents. ?? 2009 Wiley Periodicals, Inc. Complexity, 16,24-42, 2010.

Agent-based user-adaptive service provision in ubiquitous systems

NASA Astrophysics Data System (ADS)

Saddiki, H.; Harroud, H.; Karmouch, A.

2012-11-01

With the increasing availability of smartphones, tablets and other computing devices, technology consumers have grown accustomed to performing all of their computing tasks anytime, anywhere and on any device. There is a greater need to support ubiquitous connectivity and accommodate users by providing software as network-accessible services. In this paper, we propose a MAS-based approach to adaptive service composition and provision that automates the selection and execution of a suitable composition plan for a given service. With agents capable of autonomous and intelligent behavior, the composition plan is selected in a dynamic negotiation driven by a utility-based decision-making mechanism; and the composite service is built by a coalition of agents each providing a component necessary to the target service. The same service can be built in variations for catering to dynamic user contexts and further personalizing the user experience. Also multiple services can be grouped to satisfy new user needs.

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

NASA Technical Reports Server (NTRS)

Wolf, Michael T; Assad, Christopher; Kuwata, Yoshiaki; Howard, Andrew; Aghazarian, Hrand; Zhu, David; Lu, Thomas; Trebi-Ollennu, Ashitey; Huntsberger, Terry

2010-01-01

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

Investigating the Use of Cloudbursts for High-Throughput Medical Image Registration

PubMed Central

Kim, Hyunjoo; Parashar, Manish; Foran, David J.; Yang, Lin

2010-01-01

This paper investigates the use of clouds and autonomic cloudbursting to support a medical image registration. The goal is to enable a virtual computational cloud that integrates local computational environments and public cloud services on-the-fly, and support image registration requests from different distributed researcher groups with varied computational requirements and QoS constraints. The virtual cloud essentially implements shared and coordinated task-spaces, which coordinates the scheduling of jobs submitted by a dynamic set of research groups to their local job queues. A policy-driven scheduling agent uses the QoS constraints along with performance history and the state of the resources to determine the appropriate size and mix of the public and private cloud resource that should be allocated to a specific request. The virtual computational cloud and the medical image registration service have been developed using the CometCloud engine and have been deployed on a combination of private clouds at Rutgers University and the Cancer Institute of New Jersey and Amazon EC2. An experimental evaluation is presented and demonstrates the effectiveness of autonomic cloudbursts and policy-based autonomic scheduling for this application. PMID:20640235

Corrosion-Activated Micro-Containers for Environmentally Friendly Corrosion Protective Coatings

NASA Technical Reports Server (NTRS)

Li, Wenyan; Buhrow, J. W.; Zhang, X.; Johnsey, M. N.; Pearman, B. P.; Jolley, S. T.; Calle, L. M.

2016-01-01

This work concerns the development of environmentally friendly encapsulation technology, specifically designed to incorporate corrosion indicators, inhibitors, and self-healing agents into a coating, in such a way that the delivery of the indicators and inhibitors is triggered by the corrosion process, and the delivery of self-healing agents is triggered by mechanical damage to the coating. Encapsulation of the active corrosion control ingredients allows the incorporation of desired autonomous corrosion control functions such as: early corrosion detection, hidden corrosion detection, corrosion inhibition, and self-healing of mechanical damage into a coating. The technology offers the versatility needed to include one or several corrosion control functions into the same coating.The development of the encapsulation technology has progressed from the initial proof-of-concept work, in which a corrosion indicator was encapsulated into an oil-core (hydrophobic) microcapsule and shown to be delivered autonomously, under simulated corrosion conditions, to a sophisticated portfolio of micro carriers (organic, inorganic, and hybrid) that can be used to deliver a wide range of active corrosion ingredients at a rate that can be adjusted to offer immediate as well as long-term corrosion control. The micro carriers have been incorporated into different coating formulas to test and optimize the autonomous corrosion detection, inhibition, and self-healing functions of the coatings. This paper provides an overview of progress made to date and highlights recent technical developments, such as improved corrosion detection sensitivity, inhibitor test results in various types of coatings, and highly effective self-healing coatings based on green chemistry. The NASA Kennedy Space Centers Corrosion Technology Lab at the Kennedy Space Center in Florida, U.S.A. has been developing multifunctional smart coatings based on the microencapsulation of environmentally friendly corrosion indicators, inhibitors and self-healing agents. This allows the incorporation of autonomous corrosion control functionalities, such as corrosion detection and inhibition as well as the self-healing of mechanical damage, into coatings. This paper presents technical details on the characterization of inhibitor-containing particles and their corrosion inhibitive effects using electrochemical and mass loss methods.Three organic environmentally friendly corrosion inhibitors were encapsulated in organic microparticles that are compatible with desired coatings. The release of the inhibitors from the microparticles in basic solution was studied. Fast release, for immediate corrosion protection, as well as long-term release for continued protection, was observed.The inhibition efficacy of the inhibitors, incorporated directly and in microparticles, on carbon steel was evaluated. Polarization curves and mass loss measurements showed that, in the case of 2MBT, its corrosion inhibition effectiveness was greater when it was delivered from microparticles.

An Intelligent Pinger Network for Solid Glacier Environments

NASA Astrophysics Data System (ADS)

Schönitz, S.; Reuter, S.; Henke, C.; Jeschke, S.; Ewert, D.; Eliseev, D.; Heinen, D.; Linder, P.; Scholz, F.; Weinstock, L.; Wickmann, S.; Wiebusch, C.; Zierke, S.

2016-12-01

This talk presents a novel approach for an intelligent, agent-based pinger network in an extraterrestrial glacier environment. Because of recent findings of the Cassini spacecraft, a mission to Saturn's moon Enceladus is planned in order search for extraterrestrial life within the ocean beneath Enceladus' ice crust. Therefore, a maneuverable melting probe, the EnEx probe, was developed to melt into Enceladus' ice and take liquid samples from water-filled crevasses. Hence, the probe collecting the samples has to be able to navigate in ice which is a hard problem, because neither visual nor gravitational methods can be used. To enhance the navigability of the probe, a network of autonomous pinger units (APU) is in development that is able to extract a map of the ice environment via ultrasonic soundwaves. A network of these APUs will be deployed on the surface of Enceladus, melt into the ice and form a network to help guide the probe safely to its destination. The APU network is able to form itself fully autonomously and to compensate system failures of individual APUs. The agents controlling the single APU are realized by rule-based expert systems implemented in CLIPS. The rule-based expert system evaluates available information of the environment, decides for actions to take to achieve the desired goal (e.g. a specific network topology), and executes and monitors such actions. In general, it encodes certain situations that are evaluated whenever an APU is currently idle, and then decides for a next action to take. It bases this decision on its internal world model that is shared with the other APUs. The optimal network topology that defines each agents position is iteratively determined by mixed-integer nonlinear programming. Extensive simulations studies show that the proposed agent design enables the APUs to form a robust network topology that is suited to create a reliable 3D map of the ice environment.

The pressor response to water drinking in humans : a sympathetic reflex?

NASA Technical Reports Server (NTRS)

Jordan, J.; Shannon, J. R.; Black, B. K.; Ali, Y.; Farley, M.; Costa, F.; Diedrich, A.; Robertson, R. M.; Biaggioni, I.; Robertson, D.

2000-01-01

BACKGROUND: Water drinking increases blood pressure profoundly in patients with autonomic failure and substantially in older control subjects. The mechanism that mediates this response is not known. METHODS AND RESULTS: We studied the effect of drinking tap water on seated blood pressure in 47 patients with severe autonomic failure (28 multiple system atrophy [MSA], 19 pure autonomic failure patients [PAF]). Eleven older controls and 8 young controls served as control group. We also studied the mechanisms that could increase blood pressure with water drinking. Systolic blood pressure increased profoundly with water drinking, reaching a maximum of 33+/-5 mm Hg in MSA and 37+/-7 in PAF mm Hg after 30 to 35 minutes. The pressor response was greater in patients with more retained sympathetic function and was almost completely abolished by trimethaphan infusion. Systolic blood pressure increased by 11+/-2.4 mm Hg in elderly but not in young controls. Plasma norepinephrine increased in both groups. Plasma renin activity, vasopressin, and blood volume did not change in any group. CONCLUSIONS: Water drinking significantly and rapidly raises sympathetic activity. Indeed, it raises plasma norepinephrine as much as such classic sympathetic stimuli as caffeine and nicotine. This effect profoundly increases blood pressure in autonomic failure patients, and this effect can be exploited to improve symptoms due to orthostatic hypotension. Water drinking also acutely raises blood pressure in older normal subjects. The pressor effect of oral water is an important yet unrecognized confounding factor in clinical studies of pressor agents and antihypertensive medications.

Automated Planning and Scheduling for Space Mission Operations

NASA Technical Reports Server (NTRS)

Chien, Steve; Jonsson, Ari; Knight, Russell

2005-01-01

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

A Sequential Perspective on Searching for Static Targets

DTIC Science & Technology

2011-01-01

number of expected looks. One possible measure of performance is the amount of slack between the error tolerance and the observed er- ror rate...less than a and it dominates the two alternate procedures. However, the er- ror rates of the two alternate procedures are smaller then when there is...Heterogeneous Autonomous Agents, in: Int’l. Conference on Robotics and Automation, 2009, pp. 939- 945 . [17] K.P. Tognetti, An optimal strategy for whereabouts

Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators

DTIC Science & Technology

1993-05-01

Overview 22 3.1 Issues of Controller Design ........................ 22 3.2 Robot Behavior Control Philosophy .................. 23 3.3 Overview of the... designed and built by our lab as an 9 Figure 1.1- Hannibal. 10 experimental platform to explore planetary micro-rover control issues (Angle 1991). When... designing the robot, careful consideration was given to mobility, sensing, and robustness issues. Much has been said concerning the advan- tages of

Security Games Applied to Real-World: Research Contributions and Challenges

DTIC Science & Technology

2012-01-01

Marecki, J.: GUARDS and PROTECT: Next Generation Applications of Security Games . SIGECOM 10 (March 2011) 31–34 4. Shieh, E ., An, B., Yang, R., Tambe...Steigerwald, E .: GUARDS - Game Theoretic Security Allocation on a National Scale. In: Proc. of The 10th International Conference on Autonomous Agents...Shieh, E ., Kiekintveld, C.: Refinement of Strong Stackelberg Equilibria in Security Games . In: Proc. of the 25th Conference on Artificial Intelligence

Intelligent Adaptive Systems: Literature Research of Design Guidance for Intelligent Adaptive Automation and Interfaces

DTIC Science & Technology

2007-09-01

behaviour based on past experience of interacting with the operator), and mobile (i.e., can move themselves from one machine to another). Edwards argues that...Sofge, D., Bugajska, M., Adams, W., Perzanowski, D., and Schultz, A. (2003). Agent-based Multimodal Interface for Dynamically Autonomous Mobile Robots...based architecture can provide a natural and scalable approach to implementing a multimodal interface to control mobile robots through dynamic

Verification of NASA Emergent Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy K. C. S.; Truszkowski, Walt; Rash, James; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. This mission, the prospective ANTS (Autonomous Nano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of future swarm-based missions. The advantage of using formal methods is their ability to mathematically assure the behavior of a swarm, emergent or otherwise. The ANT mission is being used as an example and case study for swarm-based missions for which to experiment and test current formal methods with intelligent swam. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scheinker, Alexander

Here, we study control of the angular-velocity actuated nonholonomic unicycle, via a simple, bounded extremum seeking controller which is robust to external disturbances and measurement noise. The vehicle performs source seeking despite not having any position information about itself or the source, able only to sense a noise corrupted scalar value whose extremum coincides with the unknown source location. In order to control the angular velocity, rather than the angular heading directly, a controller is developed such that the closed loop system exhibits multiple time scales and requires an analysis approach expanding the previous work of Kurzweil, Jarnik, Sussmann, andmore » Liu, utilizing weak limits. We provide analytic proof of stability and demonstrate how this simple scheme can be extended to include position-independent source seeking, tracking, and collision avoidance of groups on autonomous vehicles in GPS-denied environments, based only on a measure of distance to an obstacle, which is an especially important feature for an autonomous agent.« less

Autonomous vehicle motion control, approximate maps, and fuzzy logic

NASA Technical Reports Server (NTRS)

Ruspini, Enrique H.

1993-01-01

Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.

Microfluidics-based integrated airborne pathogen detection systems

NASA Astrophysics Data System (ADS)

Northrup, M. Allen; Alleman-Sposito, Jennifer; Austin, Todd; Devitt, Amy; Fong, Donna; Lin, Phil; Nakao, Brian; Pourahmadi, Farzad; Vinas, Mary; Yuan, Bob

2006-09-01

Microfluidic Systems is focused on building microfluidic platforms that interface front-end mesofluidics to handle real world sample volumes for optimal sensitivity coupled to microfluidic circuitry to process small liquid volumes for complex reagent metering, mixing, and biochemical analysis, particularly for pathogens. MFSI is the prime contractor on two programs for the US Department of Homeland Security: BAND (Bioagent Autonomous Networked Detector) and IBADS (Instantaneous Bio-Aerosol Detection System). The goal of BAND is to develop an autonomous system for monitoring the air for known biological agents. This consists of air collection, sample lysis, sample purification, detection of DNA, RNA, and toxins, and a networked interface to report the results. For IBADS, MFSI is developing the confirmatory device which must verify the presence of a pathogen with 5 minutes of an air collector/trigger sounding an alarm. Instrument designs and biological assay results from both BAND and IBADS will be presented.

Performance Evaluation of a SLA Negotiation Control Protocol for Grid Networks

NASA Astrophysics Data System (ADS)

Cergol, Igor; Mirchandani, Vinod; Verchere, Dominique

A framework for an autonomous negotiation control protocol for service delivery is crucial to enable the support of heterogeneous service level agreements (SLAs) that will exist in distributed environments. We have first given a gist of our augmented service negotiation protocol to support distinct service elements. The augmentations also encompass related composition of the services and negotiation with several service providers simultaneously. All the incorporated augmentations will enable to consolidate the service negotiation operations for telecom networks, which are evolving towards Grid networks. Furthermore, our autonomous negotiation protocol is based on a distributed multi-agent framework to create an open market for Grid services. Second, we have concisely presented key simulation results of our work in progress. The results exhibit the usefulness of our negotiation protocol for realistic scenarios that involves different background traffic loading, message sizes and traffic flow asymmetry between background and negotiation traffics.

Recent Developments on Autonomous Corrosion Protection Through Encapsulation

NASA Technical Reports Server (NTRS)

Li, W.; Buhrow, J. W.; Calle, L. M.; Gillis, M.; Blanton, M.; Hanna, J.; Rawlins, J.

2015-01-01

This paper concerns recent progress in the development of a multifunctional smart coating, based on microencapsulation, for the autonomous detection and control of corrosion. Microencapsulation has been validated and optimized to incorporate desired corrosion control functionalities, such as early corrosion detection and inhibition, through corrosion-initiated release of corrosion indicators and inhibitors, as well as self-healing agent release triggered by mechanical damage. While proof-of-concept results have been previously reported, more recent research and development efforts have concentrated on improving coating compatibility and synthesis procedure scalability, with a targeted goal of obtaining easily dispersible pigment-grade type microencapsulated materials. The recent progress has resulted in the development of pH-sensitive microparticles as a corrosion-triggered delivery system for corrosion indicators and inhibitors. The synthesis and early corrosion indication results obtained with coating formulations that incorporate these microparticles are reported. The early corrosion indicating results were obtained with color changing and with fluorescent indicators.

Software agents and the route to the information economy

PubMed Central

Kephart, Jeffrey O.

2002-01-01

Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy. PMID:12011399

High-throughput infrared spectrometer for standoff chemical detection

NASA Astrophysics Data System (ADS)

Chadha, Suneet; Stevenson, Chuck; Curtiss, Lawrence E.

1999-01-01

Advanced autonomous detection of chemical warfare agents and other organic materials has long been a major military concern. While significant advances have recently been accomplished in remote spectral sensing using rugged FTIRs with point detectors, efforts towards spatial chemical discrimination have been lacking. Foster-Miller, Inc. has developed a radically different mid-IR and long wave IR spectrometer for standoff detection of chemical warfare agents and other molecular species.This no moving parts device will eliminate the cost, complexity, reliability and bandwidth/resolution problems associated with either Fabry Perot or Michelson Interferometer based approaches currently under consideration. Given the small size and performance insensitivity to on-board vibration, high EMI, thermal variations, the proposed optic would easily adapt cryocooling and field deployable requirements for low radiance detection.

Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

PubMed

Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

2008-12-01

The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

Multiagent robotic systems' ambient light sensor

NASA Astrophysics Data System (ADS)

Iureva, Radda A.; Maslennikov, Oleg S.; Komarov, Igor I.

2017-05-01

Swarm robotics is one of the fastest growing areas of modern technology. Being subclass of multi-agent systems it inherits the main part of scientific-methodological apparatus of construction and functioning of practically useful complexes, which consist of rather autonomous independent agents. Ambient light sensors (ALS) are widely used in robotics. But speaking about swarm robotics, the technology which has great number of specific features and is developing, we can't help mentioning that its important to use sensors on each robot not only in order to help it to get directionally oriented, but also to follow light emitted by robot-chief or to help to find the goal easier. Key words: ambient light sensor, swarm system, multiagent system, robotic system, robotic complexes, simulation modelling

Next Generation System and Software Architectures: Challenges from Future NASA Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Rouff, Christopher A.; Hinchey, Michael G.; Rash, James L.; Truszkowski, Walt

2006-01-01

The four key objective properties of a system that are required of it in order for it to qualify as "autonomic" are now well-accepted-self-configuring, self-healing, self-protecting, and self-optimizing- together with the attribute properties-viz. self-aware, environment-aware, self-monitoring and self- adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms.

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Research on mixed network architecture collaborative application model

NASA Astrophysics Data System (ADS)

Jing, Changfeng; Zhao, Xi'an; Liang, Song

2009-10-01

When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

PubMed

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

Learning to select useful landmarks.

PubMed

Greiner, R; Isukapalli, R

1996-01-01

To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dead-reckoning) and an image taken of a known environment, our agent first attempts to locate a set of landmarks (real-world objects at known locations), then uses their angular separation to obtain an improved estimate of its current position. Unfortunately, some landmarks may not be visible, or worse, may be confused with other landmarks, resulting in both time wasted in searching for the undetected landmarks, and in further errors in the agent's estimate of its position. To address these problems, we propose a method that uses previous experiences to learn a selection function that, given the set of landmarks that might be visible, returns the subset that can be used to reliably provide an accurate registration of the agent's position. We use statistical techniques to prove that the learned selection function is, with high probability, effectively at a local optimum in the space of such functions. This paper also presents empirical evidence, using real-world data, that demonstrate the effectiveness of our approach.

Distributed and cooperative task processing: Cournot oligopolies on a graph.

PubMed

Pavlic, Theodore P; Passino, Kevin M

2014-06-01

This paper introduces a novel framework for the design of distributed agents that must complete externally generated tasks but also can volunteer to process tasks encountered by other agents. To reduce the computational and communication burden of coordination between agents to perfectly balance load around the network, the agents adjust their volunteering propensity asynchronously within a fictitious trading economy. This economy provides incentives for nontrivial levels of volunteering for remote tasks, and thus load is shared. Moreover, the combined effects of diminishing marginal returns and network topology lead to competitive equilibria that have task reallocations that are qualitatively similar to what is expected in a load-balancing system with explicit coordination between nodes. In the paper, topological and algorithmic conditions are given that ensure the existence and uniqueness of a competitive equilibrium. Additionally, a decentralized distributed gradient-ascent algorithm is given that is guaranteed to converge to this equilibrium while not causing any node to over-volunteer beyond its maximum task-processing rate. The framework is applied to an autonomous-air-vehicle example, and connections are drawn to classic studies of the evolution of cooperation in nature.

Using analytic hierarchy process approach in ontological multicriterial decision making - Preliminary considerations

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.

2012-10-01

In this paper we consider combining ontologically demarcated information with Saaty's Analytic Hierarchy Process (AHP) [1] for the multicriterial assessment of offers during contract negotiations. The context for the proposal is provided by the Agents in Grid project (AiG; [2]), which aims at development of an agent-based infrastructure for efficient resource management in the Grid. In the AiG project, software agents representing users can either (1) join a team and earn money, or (2) find a team to execute a job. Moreover, agents form teams, managers of which negotiate with clients and workers terms of potential collaboration. Here, ontologically described contracts (Service Level Agreements) are the results of autonomous multiround negotiations. Therefore, taking into account relatively complex nature of the negotiated contracts, multicriterial assessment of proposals plays a crucial role. The AHP method is based on pairwise comparisons of criteria and relies on the judgement of a panel of experts. It measures how well does an offer serve the objective of a decision maker. In this paper, we propose how the AHP method can be used to assess ontologically described contract proposals.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark; Selinsky, T.

2002-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Cooperative Robot Localization Using Event-Triggered Estimation

NASA Astrophysics Data System (ADS)

Iglesias Echevarria, David I.

It is known that multiple robot systems that need to cooperate to perform certain activities or tasks incur in high energy costs that hinder their autonomous functioning and limit the benefits provided to humans by these kinds of platforms. This work presents a communications-based method for cooperative robot localization. Implementing concepts from event-triggered estimation, used with success in the field of wireless sensor networks but rarely to do robot localization, agents are able to only send measurements to their neighbors when the expected novelty in this information is high. Since all agents know the condition that triggers a measurement to be sent or not, the lack of a measurement is therefore informative and fused into state estimates. In the case agents do not receive either direct nor indirect measurements of all others, the agents employ a covariance intersection fusion rule in order to keep the local covariance error metric bounded. A comprehensive analysis of the proposed algorithm and its estimation performance in a variety of scenarios is performed, and the algorithm is compared to similar cooperative localization approaches. Extensive simulations are performed that illustrate the effectiveness of this method.

The coevolution of partner switching and strategy updating in non-excludable public goods game

NASA Astrophysics Data System (ADS)

Li, Yixiao; Shen, Bin

2013-10-01

Spatial public goods game is a popular metaphor to model the dilemma of collective cooperation on graphs, yet the non-excludable property of public goods has seldom been considered in previous models. Based upon a coevolutionary model where agents play public goods games and adjust their partnerships, the present model incorporates the non-excludable property of public goods: agents are able to adjust their participation in the games hosted by others, whereas they cannot exclude others from their own games. In the coevolution, a directed and dynamical network which represents partnerships among autonomous agents is evolved. We find that non-excludable property counteracts the positive effect of partner switching, i.e., the equilibrium level of cooperation is lower than that in the situation of excludable public goods game. Therefore, we study the effect of individual punishment that cooperative agents pay a personal cost to decrease benefits of those defective neighbors who participate in their hosted games. It is found that the cooperation level in the whole population is heightened in the presence of such a costly behavior.

Foundations of “new” social science: Institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling

PubMed Central

Henrickson, Leslie; McKelvey, Bill

2002-01-01

Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as “autonomous agents” that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a “new” normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a “new” social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this “new” social science legitimacy in scientific circles that current social science approaches lack. PMID:12011408

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

NASA Technical Reports Server (NTRS)

Ho, Nhut; Johnson, Walter; Panesar, Karanvir; Wakeland, Kenny; Sadler, Garrett; Wilson, Nathan; Nguyen, Bao; Lachter, Joel; Stallmann, Summer

2017-01-01

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

Mobile System for Precise Aero Delivery with Global Reach Network Capability

DTIC Science & Technology

2009-08-30

No intention / need for taking advantage of networking with other agents. The Atair’s Onyx Micro Light ( Onyx ML) delivery system (www.atair.com... onyx ) (Fig.9a) is a precision airdrop system designed to address the requirements of the Joint Precision Airdrop System MLW (JPADS-MLW) system of the...autonomous powered paraglider (LEAPP) developed under contract with DARPA (Fig.9b). a) b) Fig. 9. Onyx ML with mock sensor payload release

Stakeholder Analysis To Shape the Enterprise

NASA Astrophysics Data System (ADS)

McCaughin, Keith; Derosa, Joseph

An enterprise is a complex adaptive social system that should maximize stakeholder, not shareholder, value — value to employees, customers, shareholders and others. We expand upon Russell Ackoff s direction to distribute value among stakeholders, to propose a schema of rules that guide the interactions among autonomous agents in the transactional environment of an enterprise. We define an enterprise as an organization and its transactional environment interacting with and adapting to each other. Enterprise behavior can only be understood in the context of this transactional environment where everything depends on everything else and interactions cannot be controlled, but can be influenced if they are guided by an understanding of the internal rules of the autonomous agents. The schema has four complementary rules (control, autonomy, return and value) derived from the work of Russell Ackoff and Michael Porter. The basic rules are applied in combination to eight stakeholder types derived from Richard Hopeman and Raymond McLeod (Leaders, Competitors, Customers, Public, Workers, Collaborators, Suppliers and Regulators). An enterprise can use this schema and rules in a process of stakeholder analysis to develop and continually refine strategies to encourage behaviors that benefit the enterprise and discourage behaviors that harm the enterprise. These strategies are implemented in a relationship management program in support of enterprise strategic management to consciously and explicitly shape the environment to reduce risks and increase opportunities for success.

eHive: An Artificial Intelligence workflow system for genomic analysis

PubMed Central

2010-01-01

Background The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. Results We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios. Conclusions eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/. PMID:20459813

Biomanufacturing and self-propulsion dynamics of nanoscale bacteria-enabled autonomous delivery systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Traore, Mahama A.; Behkam, Bahareh, E-mail: behkam@vt.edu; School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, Virginia 24061

Flagellated bacteria have superb self-propulsion capabilities and are able to effectively move through highly viscous fluid and semi-solid (porous) environments. This innate aptitude has been harvested for whole-cell actuation of bio-hybrid microrobotic systems with applications in directed transport and microassembly. In this work, we present the biomanufacturing of Nanoscale Bacteria-Enabled Autonomous Delivery Systems (NanoBEADS) by controlled self-assembly and investigate the role of nanoparticle load on the dynamics of their self-propulsion in aqueous environments. Each NanoBEADS agent is comprised of spherical polystyrene nanoparticles assembled onto the body of a flagellated Escherichia coli bacterium. We demonstrate that the NanoBEADS assembly configuration ismore » strongly dependent upon the nanoparticles to bacteria ratio. Furthermore, we characterized the stochastic motion of the NanoBEADS as a function of the quantity and size of the nanoparticle load and computationally analyzed the effect of the nanoparticle load on the experienced drag force. We report that the average NanoBEADS swimming speed is reduced to 65% of the free-swimming bacteria speed (31 μm/s) at the highest possible load. NanoBEADS can be utilized as single agents or in a collaborative swarm in order to carry out specific tasks in a wide range of applications ranging from drug delivery to whole cell biosensing.« less

Mechanisms of Resistance in Multiple Myeloma.

PubMed

Papadas, Athanasios; Asimakopoulos, Fotis

2017-03-18

Multiple myeloma (MM) is an incurable hematopoietic cancer that is characterized by malignant plasma cell infiltration of the bone marrow and/or extramedullary sites. Multi-modality approaches including "novel agents," traditional chemotherapy, and/or stem cell transplantation are used in MM therapy. Drug resistance, however, ultimately develops and the disease remains incurable for the vast majority of patients. In this chapter, we review both tumor cell-autonomous and non-autonomous (microenvironment-dependent) mechanisms of drug resistance. MM provides an attractive paradigm highlighting a number of current concepts and challenges in oncology. Firstly, identification of MM cancer stem cells and their unique drug resistance attributes may provide rational avenues towards MM eradication and cure. Secondly, the oligoclonal evolution of MM and alternation of "clonal tides" upon therapy challenge our current understanding of treatment responses. Thirdly, the success of MM "novel agents" provides exemplary evidence for the impact of therapies that target the immune and non-immune microenvironment. Fourthly, the rapid pace of drug approvals for MM creates an impetus for development of precision medicine strategies and biomarkers that promote efficacy and mitigate toxicity and cost. While routine cure of the disease remains the ultimate and yet unattainable prize, MM advances in the last 10-15 years have provided an astounding paradigm for the treatment of blood cancers in the modern era and have radically transformed patient outcomes.

Ambivalent stereotypes of nurses and physicians: impact on students' attitude toward interprofessional education.

PubMed

Sollami, Alfonso; Caricati, Luca; Mancini, Tiziana

2015-03-13

Nurse-physician stereotypes have been proposed as a factor hindering interprofessional collaboration among practitioners and interprofessional learning among nursing and medical students. Using socio-psychological theories about ambivalent stereotypes, the present work aimed to analyse: a) the content of nurse and physician stereotypes held by nursing and medical students and b) the role of auto-stereotype on students' attitude toward interprofessional education (IPE).  Methods. A cross-sectional on-line survey was adopted and a questionnaire was emailed to 205 nursing students and 151 medical students attending an Italian university. Nursing and medical students shared the stereotypical belief that nurses are warmer but less competent than physicians. Nurses and physicians were basically depicted with ambivalent stereotypes: nurses were seen as communal, socially competent and caring but less competent, not agentic and less autonomous, while physicians were seen as agentic, competent and autonomous, but less communal, less collectivist and less socially competent. Moreover, a professional stereotypical image impacted the students' attitude toward IPE. More precisely, when nurses and physicians were seen with classic ambivalent stereotypes, both nursing and medical students were less favourable towards interprofessional education programmes. The content of professional stereotypes of healthcare students was still linked to classical views of nurses as caring and physicians as curing. This seemed to limit students' attitude and intention to be engaged in IPE.

Recognition of flow in everyday life using sensor agent robot with laser range finder

NASA Astrophysics Data System (ADS)

Goshima, Misa; Mita, Akira

2011-04-01

In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

Multi-agent Water Resources Management

NASA Astrophysics Data System (ADS)

Castelletti, A.; Giuliani, M.

2011-12-01

Increasing environmental awareness and emerging trends such as water trading, energy market, deregulation and democratization of water-related services are challenging integrated water resources planning and management worldwide. The traditional approach to water management design based on sector-by-sector optimization has to be reshaped to account for multiple interrelated decision-makers and many stakeholders with increasing decision power. Centralized management, though interesting from a conceptual point of view, is unfeasible in most of the modern social and institutional contexts, and often economically inefficient. Coordinated management, where different actors interact within a full open trust exchange paradigm under some institutional supervision is a promising alternative to the ideal centralized solution and the actual uncoordinated practices. This is a significant issue in most of the Southern Alps regulated lakes, where upstream hydropower reservoirs maximize their benefit independently form downstream users; it becomes even more relevant in the case of transboundary systems, where water management upstream affects water availability downstream (e.g. the River Zambesi flowing through Zambia, Zimbabwe and Mozambique or the Red River flowing from South-Western China through Northern Vietnam. In this study we apply Multi-Agent Systems (MAS) theory to design an optimal management in a decentralized way, considering a set of multiple autonomous agents acting in the same environment and taking into account the pay-off of individual water users, which are inherently distributed along the river and need to coordinate to jointly reach their objectives. In this way each real-world actor, representing the decision-making entity (e.g. the operator of a reservoir or a diversion dam) can be represented one-to-one by a computer agent, defined as a computer system that is situated in some environment and that is capable of autonomous action in this environment in order to meet its design objectives. The proposed approach is numerically tested on a synthetic case study, characterized by two multi-purpose reservoirs in cascade, two diversion dams and four different conflicting water uses: hydropower energy production, drinking supply, flooding prevention along the reservoir shores and irrigation supply. The system is therefore composed by four agents: the two operators of the diversion dams, which are purely reactive agents since they simply respond directly to the environment, and the operators of the two reservoirs, which are more complex agents because they have an internal state and their decisions are taken according to a closed-loop control scheme. In particular, the set of agents can act considering only their own objectives or they can coordinate to jointly reach better compromise solutions. Different interaction scenarios between the two extreme behaviours of centralized management and completely non-cooperation are simulated and analysed.

A Multi Agent Based Approach for Prehospital Emergency Management.

PubMed

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-07-01

To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.

A Multi Agent Based Approach for Prehospital Emergency Management

PubMed Central

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-01-01

Objective: To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Methods: Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Results: Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. Conclusion: In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement. PMID:28795061

Effects of Cholinergic Stimulation with Pyridostigmine Bromide on Chronic Chagasic Cardiomyopathic Mice

PubMed Central

de Cuba, Marília Beatriz; Ribeiro Machado, Marcus Paulo; Farnesi, Thais Soares; Alves, Angelica Cristina; Martins, Livia Alves; de Oliveira, Lucas Felipe; Capitelli, Caroline Santos; Leite, Camila Ferreira; Vinícius Silva, Marcos; Machado, Juliana Reis; Kappel, Henrique Borges; Sales de Campos, Helioswilton; Paiva, Luciano; da Silva Gomes, Natália Lins; Guimarães Faleiros, Ana Carolina; Britto, Constança Felicia de Paoli de Carvalho; Savino, Wilson; Moreira, Otacílio Cruz; Rodrigues Jr., Virmondes; Montano, Nicola; Lages-Silva, Eliane; Ramirez, Luis Eduardo; Dias da Silva, Valdo Jose

2014-01-01

The aim of the present study was to assess the effects of an anticholinesterase agent, pyridostigmine bromide (Pyrido), on experimental chronic Chagas heart disease in mice. To this end, male C57BL/6J mice noninfected (control:Con) or chronically infected (5 months) with Trypanosoma cruzi (chagasic:Chg) were treated or not (NT) with Pyrido for one month. At the end of this period, electrocardiogram (ECG); cardiac autonomic function; heart histopathology; serum cytokines; and the presence of blood and tissue parasites by means of immunohistochemistry and PCR were assessed. In NT-Chg mice, significant changes in the electrocardiographic, autonomic, and cardiac histopathological profiles were observed confirming a chronic inflammatory response. Treatment with Pyrido in Chagasic mice caused a significant reduction of myocardial inflammatory infiltration, fibrosis, and hypertrophy, which was accompanied by a decrease in serum levels of IFNγ with no change in IL-10 levels, suggesting a shift of immune response toward an anti-inflammatory profile. Lower nondifferent numbers of parasite DNA copies were observed in both treated and nontreated chagasic mice. In conclusion, our findings confirm the marked neuroimmunomodulatory role played by the parasympathetic autonomic nervous system in the evolution of the inflammatory-immune response to T. cruzi during experimental chronic Chagas heart disease in mice. PMID:25221388

Effects of cholinergic stimulation with pyridostigmine bromide on chronic chagasic cardiomyopathic mice.

PubMed

de Cuba, Marília Beatriz; Machado, Marcus Paulo Ribeiro; Farnesi, Thais Soares; Alves, Angelica Cristina; Martins, Livia Alves; de Oliveira, Lucas Felipe; Capitelli, Caroline Santos; Leite, Camila Ferreira; Silva, Marcos Vinícius; Machado, Juliana Reis; Kappel, Henrique Borges; de Campos, Helioswilton Sales; Paiva, Luciano; Gomes, Natália Lins da Silva; Faleiros, Ana Carolina Guimarães; Britto, Constança Felicia de Paoli de Carvalho; Savino, Wilson; Moreira, Otacílio Cruz; Rodrigues, Virmondes; Montano, Nicola; Lages-Silva, Eliane; Ramirez, Luis Eduardo; da Silva, Valdo Jose Dias

2014-01-01

The aim of the present study was to assess the effects of an anticholinesterase agent, pyridostigmine bromide (Pyrido), on experimental chronic Chagas heart disease in mice. To this end, male C57BL/6J mice noninfected (control:Con) or chronically infected (5 months) with Trypanosoma cruzi (chagasic:Chg) were treated or not (NT) with Pyrido for one month. At the end of this period, electrocardiogram (ECG); cardiac autonomic function; heart histopathology; serum cytokines; and the presence of blood and tissue parasites by means of immunohistochemistry and PCR were assessed. In NT-Chg mice, significant changes in the electrocardiographic, autonomic, and cardiac histopathological profiles were observed confirming a chronic inflammatory response. Treatment with Pyrido in Chagasic mice caused a significant reduction of myocardial inflammatory infiltration, fibrosis, and hypertrophy, which was accompanied by a decrease in serum levels of IFNγ with no change in IL-10 levels, suggesting a shift of immune response toward an anti-inflammatory profile. Lower nondifferent numbers of parasite DNA copies were observed in both treated and nontreated chagasic mice. In conclusion, our findings confirm the marked neuroimmunomodulatory role played by the parasympathetic autonomic nervous system in the evolution of the inflammatory-immune response to T. cruzi during experimental chronic Chagas heart disease in mice.

Applying self-determination theory for improved understanding of physiotherapists' rationale for using research in clinical practice: a qualitative study in Sweden.

PubMed

Dannapfel, Petra; Peolsson, Anneli; Ståhl, Christian; Öberg, Birgitta; Nilsen, Per

2014-01-01

Physiotherapists are generally positive to evidence-based practice (EBP) and the use of research in clinical practice, yet many still base clinical decisions on knowledge obtained during their initial education and/or personal experience. Our aim was to explore motivations behind physiotherapists' use of research in clinical practice. Self-Determination Theory was applied to identify the different types of motivation for use of research. This theory posits that all behaviours lie along a continuum of relative autonomy, reflecting the extent to which a person endorses their actions. Eleven focus group interviews were conducted, involving 45 physiotherapists in various settings in Sweden. Data were analysed using qualitative content analysis and the findings compared with Self-Determination Theory using a deductive approach. Motivations underlying physiotherapists use of research in clinical practice were identified. Most physiotherapists expressed autonomous forms of motivation for research use, but some exhibited more controlled motivation. Several implications about how more evidence-based physiotherapy can be achieved are discussed, including the potential to tailor educational programs on EBP to better account for differences in motivation among participants, using autonomously motivated physiotherapists as change agents and creating favourable conditions to encourage autonomous motivation by way of feelings of competence, autonomy and a sense of relatedness.

Midodrine improves orgasm in spinal cord-injured men: the effects of autonomic stimulation.

PubMed

Soler, Jean Marc; Previnaire, Jean Gabriel; Plante, Pierre; Denys, Pierre; Chartier-Kastler, Emmanuel

2008-12-01

Orgasm is less frequent in men with spinal cord injury (SCI) than in able-bodied subjects, and is poorly understood. To assess the effect of autonomic stimulation on orgasm in SCI men using midodrine, an alpha1-adrenergic agonist agent. Penile vibratory stimulation (PVS) was performed in 158 SCI men on midodrine as part of a treatment for anejaculation, after they failed a baseline PVS. A maximum of four trials were performed, weekly, with increasing doses of midodrine. The presence and type of ejaculation, orgasm experiences, and cardiovascular data were collected. Ejaculation either antegrade or retrograde was obtained in 102 SCI men (65%). Orgasm without ejaculation was reported by 14 patients (9%) on baseline PVS. Ninety-three patients (59%) experienced orgasm during PVS on midodrine. Orgasm was significantly related to the presence of ejaculation in 86 patients (84%), and more strikingly to antegrade ejaculation (pure or mixed with retrograde), i.e., in 98% of 70 patients. Orgasm was significantly more frequent in patients with upper motor neuron and incomplete lesions who present somatic responses during PVS. There was no effect of the presence of psychogenic erection. There was a significant increase in both systolic and diastolic blood pressure. Sixteen patients, mainly tetraplegics, developed intense autonomic dysreflexia (AD) that required an oral nicardipine chlorhydrate. Orgasm is the brain's cognitive interpretation of genital sensations and somatic responses, AD, and ejaculation. Intact sacral and T10-L2 cord segments are mandatory, allowing coordination between internal and external sphincters. Autonomic stimulation with midodrine enhances orgasm rate, mainly by creating antegrade ejaculation.

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

NASA Astrophysics Data System (ADS)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

The cardiovascular system in the ageing patient

PubMed Central

Moore, A; Mangoni, A A; Lyons, D; Jackson, S H D

2003-01-01

The ageing process is associated with important changes in the responses of the cardiovascular system to pharmacological stimuli. They are not limited to the arterial system, involved in the modulation of cardiac afterload and vascular resistance, but they also involve the low-resistance capacitance venous system and the heart. The main changes include loss of large artery compliance, dysfunction of some of the systems modulating resistance vessel tone, increased activity of the sympathetic nervous system, and reduced haemodynamic responses to inotropic agents. This review focuses on the effects of ageing on arterial and venous reactivity to drugs and hormones, the autonomic nervous system, and the cardiovascular responses to inotropic agents. Some of the age-related changes might be at least partially reversible. This may have important therapeutic implications. PMID:12919173

Adaptive Sensing of Time Series with Application to Remote Exploration

NASA Technical Reports Server (NTRS)

Thompson, David R.; Cabrol, Nathalie A.; Furlong, Michael; Hardgrove, Craig; Low, Bryan K. H.; Moersch, Jeffrey; Wettergreen, David

2013-01-01

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

Multi-Agent Software Design and Engineering for Human Centered Collaborative Autonomous Space Systems: NASA Intelligent Systems

NASA Technical Reports Server (NTRS)

Bradshaw, Jeffrey M.

2005-01-01

Detailed results of this three-year project are available in 37 publications, including 7 book chapters, 3 journal articles, and 27 refereed conference proceedings. In addition, various aspects of the project were the subject of 31 invited presentations and 6 tutorials at international conferences and workshops. Good descriptions of prior and ongoing work on foundational technologies in Brahms, KAoS, NOMADS, and the PSA project can be found in numerous publications not listed here.

Distributed Control of a Swarm of Autonomous Unmanned Aerial Vehicles

DTIC Science & Technology

2003-03-01

wisdom, and love have provided a firm anchor in rough times, and a light in the darkness . “Come to me, all you who are weary and burdened, and I will...time. The light-gray trails represent the area that has been covered in the past 50 timesteps. The dark -gray areas are overlapping areas calculated...during the current timestep. The dark line encloses the total contigu- ous sensor area for this example. Note that while agent 1’s footprint does not

Distributed Hybrid Information and Plan Consensus HIPC for Semi-autonomous UAV Teams

DTIC Science & Technology

2015-09-18

finalized. To do all of the onboard computations we are using Raspberry Pi B+’s (this hardware as shown in Fig. 16.) These computers are used to do all...public release. Figure 16: Raspberry Pi hardware Figure 17: Raspberry Pi hardware with case and DigiMesh Xbee Figure 18: Team of 11 Raspberry Pi powered...agents with Digimesh Xbee communication hardware. DISTRIBUTION A: Distribution approved for public release. Figure 19: Raspberry Pi network in real

Tactical assessment in a squad of intelligent bots

NASA Astrophysics Data System (ADS)

Gołuński, Marcel; Wasiewicz, Piotr

2010-09-01

In this paper we explore the problem of communication and coordination in a team of intelligent game bots (aka embodied agents). It presents a tactical decision making system controlling the behavior of an autonomous bot followed by the concept of a team tactical decision making system controlling the team of intelligent bots. The algorithms to be introduced have been implemented in the Java language by means of Pogamut 2 framework, interfacing the bot logic with Unreal Tournament 2004 virtual environment.

The Blood Volume of the Guinea Pig: Effects of Epinephrine and Isoproterenol upon the Red Cell and Plasma Volumes, Heart Rate, and Mean Arterial Pressure,

DTIC Science & Technology

1987-09-01

capillaries (4), blood volumes calculated from plasma volume measures must correct for label that has left the system between the time of the injected dose...Splenic sequestration and contraction are mediated by the autonomic nervous system and blood-borne agents (10). Sympathetic nerve fibers from the truncus...sympathlcus and parasympathetic neurons of the nervus vagus (cranial nerve X) innervate the celiac plexus (8, 11). A subdivision of the celiac plexus

Design and Integration of a Three Degrees-of-Freedom Robotic Vehicle with Control Moment Gyro for the Autonomous Multi-Agent Physically Interacting Spacecraft (AMPHIS) Testbed

DTIC Science & Technology

2006-09-01

required directional control for each thruster due to their high precision and equivalent power and computer interface requirements to those for the...Universal Serial Bus) ports, LPT (Line Printing Terminal) and KVM (Keyboard-Video- Mouse) interfaces. Additionally, power is supplied to the computer through...of the IDE cable to the Prometheus Development Kit ACC-IDEEXT. Connect a small drive power connector from the desktop ATX power supply to the ACC

A Lightweight Intelligent Virtual Cinematography System for Machinima Production

DTIC Science & Technology

2007-01-01

portmanteau of machine and cinema , machinima refers to the innovation of leveraging video game technology to greatly ease the creation of computer...selecting camera angles to capture the action of an a priori unknown script as aesthetically appropriate cinema . There are a number of challenges therein...Proc. of the 4th International Conf. on Autonomous Agents. Young, R.M. and Riedl, M.O. 2003. Towards an Architecture for Intelligent Control of Narrative in Interactive Virtual Worlds. In Proc. of IUI 2003.

Coordinated Resource Allocation Among Multiple Agents With Application to Autonomous Refueling and Servicing of Satellite Constellations

DTIC Science & Technology

2008-03-01

invited). • American Control Conference, Minneapolis, MN, June 14–16, 2006 (invited). • AAS Spaceflight Mechanics Meeting, Sedona, AZ, Jan. 28-Feb. 1...Rensselaer Polytechnic Institute, Troy, NY, October 22, 2007. 4.2 Transitions Parts of this work have been used by the group of Dr. Alan Lovell of AFRL... Lovell , Space Vehicles Directorate, AFRL/VSES, 3550 Aberdeen Ave SE, Kirtland AFB, New Mexico 87117-5776, Tel: (505) 853-4132, Fax: (505) 846-6053, Email

Density Control of Multi-Agent Systems with Safety Constraints: A Markov Chain Approach

NASA Astrophysics Data System (ADS)

Demirer, Nazli

The control of systems with autonomous mobile agents has been a point of interest recently, with many applications like surveillance, coverage, searching over an area with probabilistic target locations or exploring an area. In all of these applications, the main goal of the swarm is to distribute itself over an operational space to achieve mission objectives specified by the density of swarm. This research focuses on the problem of controlling the distribution of multi-agent systems considering a hierarchical control structure where the whole swarm coordination is achieved at the high-level and individual vehicle/agent control is managed at the low-level. High-level coordination algorithms uses macroscopic models that describes the collective behavior of the whole swarm and specify the agent motion commands, whose execution will lead to the desired swarm behavior. The low-level control laws execute the motion to follow these commands at the agent level. The main objective of this research is to develop high-level decision control policies and algorithms to achieve physically realizable commanding of the agents by imposing mission constraints on the distribution. We also make some connections with decentralized low-level motion control. This dissertation proposes a Markov chain based method to control the density distribution of the whole system where the implementation can be achieved in a decentralized manner with no communication between agents since establishing communication with large number of agents is highly challenging. The ultimate goal is to guide the overall density distribution of the system to a prescribed steady-state desired distribution while satisfying desired transition and safety constraints. Here, the desired distribution is determined based on the mission requirements, for example in the application of area search, the desired distribution should match closely with the probabilistic target locations. The proposed method is applicable for both systems with a single agent and systems with large number of agents due to the probabilistic nature, where the probability distribution of each agent's state evolves according to a finite-state and discrete-time Markov chain (MC). Hence, designing proper decision control policies requires numerically tractable solution methods for the synthesis of Markov chains. The synthesis problem has the form of a Linear Matrix Inequality Problem (LMI), with LMI formulation of the constraints. To this end, we propose convex necessary and sufficient conditions for safety constraints in Markov chains, which is a novel result in the Markov chain literature. In addition to LMI-based, offline, Markov matrix synthesis method, we also propose a QP-based, online, method to compute a time-varying Markov matrix based on the real-time density feedback. Both problems are convex optimization problems that can be solved in a reliable and tractable way, utilizing existing tools in the literature. A Low Earth Orbit (LEO) swarm simulations are presented to validate the effectiveness of the proposed algorithms. Another problem tackled as a part of this research is the generalization of the density control problem to autonomous mobile agents with two control modes: ON and OFF. Here, each mode consists of a (possibly overlapping) finite set of actions, that is, there exist a set of actions for the ON mode and another set for the OFF mode. We give formulation for a new Markov chain synthesis problem, with additional measurements for the state transitions, where a policy is designed to ensure desired safety and convergence properties for the underlying Markov chain.

Microcapsule-based techniques for improving the safety of lithium-ion batteries

NASA Astrophysics Data System (ADS)

Baginska, Marta

Lithium-ion batteries are vital energy storage devices due to their high specific energy density, lack of memory effect, and long cycle life. While they are predominantly used in small consumer electronics, new strategies for improving battery safety and lifetime are critical to the successful implementation of high-capacity, fast-charging materials required for advanced Li-ion battery applications. Currently, the presence of a volatile, combustible electrolyte and an oxidizing agent (Lithium oxide cathodes) make the Li-ion cell susceptible to fire and explosions. Thermal overheating, electrical overcharging, or mechanical damage can trigger thermal runaway, and if left unchecked, combustion of battery materials. To improve battery safety, autonomic, thermally-induced shutdown of Li-ion batteries is demonstrated by depositing thermoresponsive polymer microspheres onto battery anodes. When the internal temperature of the cell reaches a critical value, the microspheres melt and conformally coat the anode and/or separator with an ion insulating barrier, halting Li-ion transport and shutting down the cell permanently. Charge and discharge capacity is measured for Li-ion coin cells containing microsphere-coated anodes or separators as a function of capsule coverage. Scanning electron microscopy images of electrode surfaces from cells that have undergone autonomic shutdown provides evidence of melting, wetting, and re-solidification of polyethylene (PE) into the anode and polymer film formation at the anode/separator interface. As an extension of this autonomic shutdown approach, a particle-based separator capable of performing autonomic shutdown, but which reduces the shorting hazard posed by current bi- and tri-polymer commercial separators, is presented. This dual-particle separator is composed of hollow glass microspheres acting as a physical spacer between electrodes, and PE microspheres to impart autonomic shutdown functionality. An oil-immersion technique is developed to simulate an overheating condition while the cell is cycling. Experimental protocols are developed to assess the performance of the separator in terms of its ability to perform autonomic shutdown and examine tested battery materials using scanning electron microscopy. Another approach to improving battery functionality is via the microencapsulation of battery additives. Currently, additives are added directly into a battery electrolyte, and while they typically perform their function given a sufficient loading, these additives often do so at the expense of battery performance. Microencapsulation allows for a high loading of additives to be incorporated into the cell and their release triggered only when and where they are needed. In this work, microencapsulation techniques are developed to successfully encapsulate 3-hexylthiophene, a stabilizing agent for high-voltage cathodes in Li-ion batteries and conductive polymer precursor, as well as the flame retardant Tris(2-choloroethyl phosphate) (TCP). Microcapsules containing 3-hexylthiophene are coated onto model battery electrodes and immersed in electrolyte. The microcapsule shell wall insulates the 3-hexylthiophene until the microcapsules are mechanically crushed and electropolymerization of the released core to form poly(3-ht) occurs under cyclic voltammetry. In addition, TCP was encapsulated using in situ polymerization. TCP-containing microcapsules are stable in electrolyte at room temperature, but are thermally triggered to release their payload at elevated temperatures. Experimental protocols are developed to study the in situ triggering and release of microencapsulated additives.

RoBlock: a prototype autonomous manufacturing cell

NASA Astrophysics Data System (ADS)

Baekdal, Lars K.; Balslev, Ivar; Eriksen, Rene D.; Jensen, Soren P.; Jorgensen, Bo N.; Kirstein, Brian; Kristensen, Bent B.; Olsen, Martin M.; Perram, John W.; Petersen, Henrik G.; Petersen, Morten L.; Ruhoff, Peter T.; Skjolstrup, Carl E.; Sorensen, Anders S.; Wagenaar, Jeroen M.

2000-10-01

RoBlock is the first phase of an internally financed project at the Institute aimed at building a system in which two industrial robots suspended from a gantry, as shown below, cooperate to perform a task specified by an external user, in this case, assembling an unstructured collection of colored wooden blocks into a specified 3D pattern. The blocks are identified and localized using computer vision and grasped with a suction cup mechanism. Future phases of the project will involve other processes such as grasping and lifting, as well as other types of robot such as autonomous vehicles or variable geometry trusses. Innovative features of the control software system include: The use of an advanced trajectory planning system which ensures collision avoidance based on a generalization of the method of artificial potential fields, the use of a generic model-based controller which learns the values of parameters, including static and kinetic friction, of a detailed mechanical model of itself by comparing actual with planned movements, the use of fast, flexible, and robust pattern recognition and 3D-interpretation strategies, integration of trajectory planning and control with the sensor systems in a distributed Java application running on a network of PC's attached to the individual physical components. In designing this first stage, the aim was to build in the minimum complexity necessary to make the system non-trivially autonomous and to minimize the technological risks. The aims of this project, which is planned to be operational during 2000, are as follows: To provide a platform for carrying out experimental research in multi-agent systems and autonomous manufacturing systems, to test the interdisciplinary cooperation architecture of the Maersk Institute, in which researchers in the fields of applied mathematics (modeling the physical world), software engineering (modeling the system) and sensor/actuator technology (relating the virtual and real worlds) could collaborate with systems integrators to construct intelligent, autonomous systems, and to provide a showpiece demonstrator in the entrance hall of the Institute's new building.

Trust-based learning and behaviors for convoy obstacle avoidance

NASA Astrophysics Data System (ADS)

Mikulski, Dariusz G.; Karlsen, Robert E.

2015-05-01

In many multi-agent systems, robots within the same team are regarded as being fully trustworthy for cooperative tasks. However, the assumption of trustworthiness is not always justified, which may not only increase the risk of mission failure, but also endanger the lives of friendly forces. In prior work, we addressed this issue by using RoboTrust to dynamically adjust to observed behaviors or recommendations in order to mitigate the risks of illegitimate behaviors. However, in the simulations in prior work, all members of the convoy had knowledge of the convoy goal. In this paper, only the lead vehicle has knowledge of the convoy goals and the follow vehicles must infer trustworthiness strictly from lead vehicle performance. In addition, RoboTrust could only respond to observed performance and did not dynamically learn agent behavior. In this paper, we incorporate an adaptive agent-specific bias into the RoboTrust algorithm that modifies its trust dynamics. This bias is learned incrementally from agent interactions, allowing good agents to benefit from faster trust growth and slower trust decay and bad agents to be penalized with slower trust growth and faster trust decay. We then integrate this new trust model into a trust-based controller for decentralized autonomous convoy operations. We evaluate its performance in an obstacle avoidance mission, where the convoy attempts to learn the best speed and following distances combinations for an acceptable obstacle avoidance probability.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

PubMed Central

2016-01-01

Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

The influence of active vision on the exoskeleton of intelligent agents

NASA Astrophysics Data System (ADS)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

Fusing terrain and goals: agent control in urban environments

NASA Astrophysics Data System (ADS)

Kaptan, Varol; Gelenbe, Erol

2006-04-01

The changing face of contemporary military conflicts has forced a major shift of focus in tactical planning and evaluation from the classical Cold War battlefield to an asymmetric guerrilla-type warfare in densely populated urban areas. The new arena of conflict presents unique operational difficulties due to factors like complex mobility restrictions and the necessity to preserve civilian lives and infrastructure. In this paper we present a novel method for autonomous agent control in an urban environment. Our approach is based on fusing terrain information and agent goals for the purpose of transforming the problem of navigation in a complex environment with many obstacles into the easier problem of navigation in a virtual obstacle-free space. The main advantage of our approach is its ability to act as an adapter layer for a number of efficient agent control techniques which normally show poor performance when applied to an environment with many complex obstacles. Because of the very low computational and space complexity at runtime, our method is also particularly well suited for simulation or control of a huge number of agents (military as well as civilian) in a complex urban environment where traditional path-planning may be too expensive or where a just-in-time decision with hard real-time constraints is required.

Mixed reality framework for collective motion patterns of swarms with delay coupling

NASA Astrophysics Data System (ADS)

Szwaykowska, Klementyna; Schwartz, Ira

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is an important subject for many applications within the field of distributed robotic systems. However, there are significant logistical challenges associated with testing fully distributed systems in real-world settings. In this paper, we provide a rigorous theoretical justification for the use of mixed-reality experiments as a stepping stone to fully physical testing of distributed robotic systems. We also model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. Our analyses, assuming agents communicating over an Erdos-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm. K. S. was a National Research Council postdoctoral fellow. I.B.S was supported by the U.S. Naval Research Laboratory funding (N0001414WX00023) and office of Naval Research (N0001414WX20610).

Autonomous Shepherding Behaviors of Multiple Target Steering Robots.

PubMed

Lee, Wonki; Kim, DaeEun

2017-11-25

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots' position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

Autonomous Shepherding Behaviors of Multiple Target Steering Robots

PubMed Central

Lee, Wonki; Kim, DaeEun

2017-01-01

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach. PMID:29186836

Evolvable mathematical models: A new artificial Intelligence paradigm

NASA Astrophysics Data System (ADS)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

Integrating robotic action with biologic perception: A brain-machine symbiosis theory

NASA Astrophysics Data System (ADS)

Mahmoudi, Babak

In patients with motor disability the natural cyclic flow of information between the brain and external environment is disrupted by their limb impairment. Brain-Machine Interfaces (BMIs) aim to provide new communication channels between the brain and environment by direct translation of brain's internal states into actions. For enabling the user in a wide range of daily life activities, the challenge is designing neural decoders that autonomously adapt to different tasks, environments, and to changes in the pattern of neural activity. In this dissertation, a novel decoding framework for BMIs is developed in which a computational agent autonomously learns how to translate neural states into action based on maximization of a measure of shared goal between user and the agent. Since the agent and brain share the same goal, a symbiotic relationship between them will evolve therefore this decoding paradigm is called a Brain-Machine Symbiosis (BMS) framework. A decoding agent was implemented within the BMS framework based on the Actor-Critic method of Reinforcement Learning. The rule of the Actor as a neural decoder was to find mapping between the neural representation of motor states in the primary motor cortex (MI) and robot actions in order to solve reaching tasks. The Actor learned the optimal control policy using an evaluative feedback that was estimated by the Critic directly from the user's neural activity of the Nucleus Accumbens (NAcc). Through a series of computational neuroscience studies in a cohort of rats it was demonstrated that NAcc could provide a useful evaluative feedback by predicting the increase or decrease in the probability of earning reward based on the environmental conditions. Using a closed-loop BMI simulator it was demonstrated the Actor-Critic decoding architecture was able to adapt to different tasks as well as changes in the pattern of neural activity. The custom design of a dual micro-wire array enabled simultaneous implantation of MI and NAcc for the development of a full closed-loop system. The Actor-Critic decoding architecture was able to solve the brain-controlled reaching task using a robotic arm by capturing the interdependency between the simultaneous action representation in MI and reward expectation in NAcc.

Artificial consciousness, artificial emotions, and autonomous robots.

PubMed

Cardon, Alain

2006-12-01

Nowadays for robots, the notion of behavior is reduced to a simple factual concept at the level of the movements. On another hand, consciousness is a very cultural concept, founding the main property of human beings, according to themselves. We propose to develop a computable transposition of the consciousness concepts into artificial brains, able to express emotions and consciousness facts. The production of such artificial brains allows the intentional and really adaptive behavior for the autonomous robots. Such a system managing the robot's behavior will be made of two parts: the first one computes and generates, in a constructivist manner, a representation for the robot moving in its environment, and using symbols and concepts. The other part achieves the representation of the previous one using morphologies in a dynamic geometrical way. The robot's body will be seen for itself as the morphologic apprehension of its material substrata. The model goes strictly by the notion of massive multi-agent's organizations with a morphologic control.

Autonomous Information Fading and Provision to Achieve High Response Time in Distributed Information Systems

NASA Astrophysics Data System (ADS)

Lu, Xiaodong; Arfaoui, Helene; Mori, Kinji

In highly dynamic electronic commerce environment, the need for adaptability and rapid response time to information service systems has become increasingly important. In order to cope with the continuously changing conditions of service provision and utilization, Faded Information Field (FIF) has been proposed. FIF is a distributed information service system architecture, sustained by push/pull mobile agents to bring high-assurance of services through a recursive demand-oriented provision of the most popular information closer to the users to make a tradeoff between the cost of information service allocation and access. In this paper, based on the analysis of the relationship that exists among the users distribution, information provision and access time, we propose the technology for FIF design to resolve the competing requirements of users and providers to improve users' access time. In addition, to achieve dynamic load balancing with changing users preference, the autonomous information reallocation technology is proposed. We proved the effectiveness of the proposed technology through the simulation and comparison with the conventional system.

Bounded extremum seeking for angular velocity actuated control of nonholonomic unicycle

DOE PAGES

Scheinker, Alexander

2016-08-17

Here, we study control of the angular-velocity actuated nonholonomic unicycle, via a simple, bounded extremum seeking controller which is robust to external disturbances and measurement noise. The vehicle performs source seeking despite not having any position information about itself or the source, able only to sense a noise corrupted scalar value whose extremum coincides with the unknown source location. In order to control the angular velocity, rather than the angular heading directly, a controller is developed such that the closed loop system exhibits multiple time scales and requires an analysis approach expanding the previous work of Kurzweil, Jarnik, Sussmann, andmore » Liu, utilizing weak limits. We provide analytic proof of stability and demonstrate how this simple scheme can be extended to include position-independent source seeking, tracking, and collision avoidance of groups on autonomous vehicles in GPS-denied environments, based only on a measure of distance to an obstacle, which is an especially important feature for an autonomous agent.« less

Homo sapiens Systemic RNA Interference-defective-1 Transmembrane Family Member 1 (SIDT1) Protein Mediates Contact-dependent Small RNA Transfer and MicroRNA-21-driven Chemoresistance*

PubMed Central

Elhassan, Mohamed O.; Christie, Jennifer; Duxbury, Mark S.

2012-01-01

Locally initiated RNA interference (RNAi) has the potential for spatial propagation, inducing posttranscriptional gene silencing in distant cells. In Caenorhabditis elegans, systemic RNAi requires a phylogenetically conserved transmembrane channel, SID-1. Here, we show that a human SID-1 orthologue, SIDT1, facilitates rapid, contact-dependent, bidirectional small RNA transfer between human cells, resulting in target-specific non-cell-autonomous RNAi. Intercellular small RNA transfer can be both homotypic and heterotypic. We show SIDT1-mediated intercellular transfer of microRNA-21 to be a driver of resistance to the nucleoside analog gemcitabine in human adenocarcinoma cells. Documentation of a SIDT1-dependent small RNA transfer mechanism and the associated phenotypic effects on chemoresistance in human cancer cells raises the possibility that conserved systemic RNAi pathways contribute to the acquisition of drug resistance. Mediators of non-cell-autonomous RNAi may be tractable targets for novel therapies aimed at improving the efficacy of current cytotoxic agents. PMID:22174421

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

PubMed

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles.

PubMed

Atman, Jamal; Popp, Manuel; Ruppelt, Jan; Trommer, Gert F

2016-09-16

Micro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV's navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results.

Self-organized adaptation of a simple neural circuit enables complex robot behaviour

NASA Astrophysics Data System (ADS)

Steingrube, Silke; Timme, Marc; Wörgötter, Florentin; Manoonpong, Poramate

2010-03-01

Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum. To rapidly interact with the environment, this control needs to be fast and adaptive. Present robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns. Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot. In the presented system, 18 sensors drive 18 motors by means of a simple neural control circuit, thereby generating 11 basic behavioural patterns (for example, orienting, taxis, self-protection and various gaits) and their combinations. The control signal quickly and reversibly adapts to new situations and also enables learning and synaptic long-term storage of behaviourally useful motor responses. Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

Robot soccer anywhere: achieving persistent autonomous navigation, mapping, and object vision tracking in dynamic environments

NASA Astrophysics Data System (ADS)

Dragone, Mauro; O'Donoghue, Ruadhan; Leonard, John J.; O'Hare, Gregory; Duffy, Brian; Patrikalakis, Andrew; Leederkerken, Jacques

2005-06-01

The paper describes an ongoing effort to enable autonomous mobile robots to play soccer in unstructured, everyday environments. Unlike conventional robot soccer competitions that are usually held on purpose-built robot soccer "fields", in our work we seek to develop the capability for robots to demonstrate aspects of soccer-playing in more diverse environments, such as schools, hospitals, or shopping malls, with static obstacles (furniture) and dynamic natural obstacles (people). This problem of "Soccer Anywhere" presents numerous research challenges including: (1) Simultaneous Localization and Mapping (SLAM) in dynamic, unstructured environments, (2) software control architectures for decentralized, distributed control of mobile agents, (3) integration of vision-based object tracking with dynamic control, and (4) social interaction with human participants. In addition to the intrinsic research merit of these topics, we believe that this capability would prove useful for outreach activities, in demonstrating robotics technology to primary and secondary school students, to motivate them to pursue careers in science and engineering.

APDS: Autonomous Pathogen Detection System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langlois, R G; Brown, S; Burris, L

An early warning system to counter bioterrorism, the Autonomous Pathogen Detection System (APDS) continuously monitors the environment for the presence of biological pathogens (e.g., anthrax) and once detected, it sounds an alarm much like a smoke detector warns of a fire. Long before September 11, 2001, this system was being developed to protect domestic venues and events including performing arts centers, mass transit systems, major sporting and entertainment events, and other high profile situations in which the public is at risk of becoming a target of bioterrorist attacks. Customizing off-the-shelf components and developing new components, a multidisciplinary team developed APDS,more » a stand-alone system for rapid, continuous monitoring of multiple airborne biological threat agents in the environment. The completely automated APDS samples the air, prepares fluid samples in-line, and performs two orthogonal tests: immunoassay and nucleic acid detection. When compared to competing technologies, APDS is unprecedented in terms of flexibility and system performance.« less

Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Pisanich, Greg; Ippolito, Corey; Plice, Laura; Young, Larry A.; Lau, Benton

2003-01-01

This paper details the development and demonstration of an autonomous aerial vehicle embodying search and find mission planning and execution srrategies inspired by foraging behaviors found in biology. It begins by describing key characteristics required by an aeria! explorer to support science and planetary exploration goals, and illustrates these through a hypothetical mission profile. It next outlines a conceptual bio- inspired search and find autonomy architecture that implements observations, decisions, and actions through an "ecology" of producer, consumer, and decomposer agents. Moving from concepts to development activities, it then presents the results of mission representative UAV aerial surveys at a Mars analog site. It next describes hardware and software enhancements made to a commercial small fixed-wing UAV system, which inc!nde a ncw dpvelopnent architecture that also provides hardware in the loop simulation capability. After presenting the results of simulated and actual flights of bioinspired flight algorithms, it concludes with a discussion of future development to include an expansion of system capabilities and field science support.

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

Analytical model for effects of capsule shape on the healing efficiency in self-healing materials

PubMed Central

Li, Songpeng; Chen, Huisu

2017-01-01

The fundamental requirement for the autonomous capsule-based self-healing process to work is that cracks need to reach the capsules and break them such that the healing agent can be released. Ignoring all other aspects, the amount of healing agents released into the crack is essential to obtain a good healing. Meanwhile, from the perspective of the capsule shapes, spherical or elongated capsules (hollow tubes/fibres) are the main morphologies used in capsule-based self-healing materials. The focus of this contribution is the description of the effects of capsule shape on the efficiency of healing agent released in capsule-based self-healing material within the framework of the theory of geometrical probability and integral geometry. Analytical models are developed to characterize the amount of healing agent released per crack area from capsules for an arbitrary crack intersecting with capsules of various shapes in a virtual capsule-based self-healing material. The average crack opening distance is chosen to be a key parameter in defining the healing potential of individual cracks in the models. Furthermore, the accuracy of the developed models was verified by comparison to the data from a published numerical simulation study. PMID:29095862

Designing an architectural style for dynamic medical Cross-Organizational Workflow management system: an approach based on agents and web services.

PubMed

Bouzguenda, Lotfi; Turki, Manel

2014-04-01

This paper shows how the combined use of agent and web services technologies can help to design an architectural style for dynamic medical Cross-Organizational Workflow (COW) management system. Medical COW aims at supporting the collaboration between several autonomous and possibly heterogeneous medical processes, distributed over different organizations (Hospitals, Clinic or laboratories). Dynamic medical COW refers to occasional cooperation between these health organizations, free of structural constraints, where the medical partners involved and their number are not pre-defined. More precisely, this paper proposes a new architecture style based on agents and web services technologies to deal with two key coordination issues of dynamic COW: medical partners finding and negotiation between them. It also proposes how the proposed architecture for dynamic medical COW management system can connect to a multi-agent system coupling the Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE). The idea is to assist the health professionals such as doctors, nurses and pharmacists with decision making tasks, as determining diagnosis or patient data analysis without stopping their clinical processes in order to act in a coherent way and to give care to the patient.

Agent-based power sharing scheme for active hybrid power sources

NASA Astrophysics Data System (ADS)

Jiang, Zhenhua

The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

Distributed reconfigurable control strategies for switching topology networked multi-agent systems.

PubMed

Gallehdari, Z; Meskin, N; Khorasani, K

2017-11-01

In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Growing Up of Autonomous Agents: an Emergent Phenomenon

NASA Astrophysics Data System (ADS)

Morgavi, Giovanna; Marconi, Lucia

2008-10-01

A fundamental research challenge is the design of robust artifacts that are capable of operating under changing environments and noisy input, and yet exhibit the desired behavior and response time. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to biological entities. The turn to nature has brought us many unforeseen great concepts. Biological systems are able to handle many of these challenges with an elegance and efficiency still far beyond current human artifacts. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. In the attempt to define an architecture for autonomous growing up agents [1]. We conducted an experiment on the abstraction process in children as natural parts of a cognitive system. We found that linguistic growing up involve a number of different trial processes. We identified a fixed number of distinct paths that were crossed by children. Once a given interpretation paths was discovered useless, they tried to follow another path, until the new meaning was emerging. This study generates suggestion about the evolutionary conditions conducive to the emergence of growing up in robots and provides guidelines for designing artificial evolutionary systems displaying spontaneous adaptation abilities. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.

Contrasting effects of vasodilators on blood pressure and sodium balance in the hypertension of autonomic failure

NASA Technical Reports Server (NTRS)

Jordan, J.; Shannon, J. R.; Pohar, B.; Paranjape, S. Y.; Robertson, D.; Robertson, R. M.; Biaggioni, I.

1999-01-01

Supine hypertension, which is very common in patients with autonomic failure, limits the use of pressor agents and induces nighttime natriuresis. In 13 patients with severe orthostatic hypotension due to autonomic failure (7 women, 6 men, 72 +/- 3 yr) and supine hypertension, the effect of 30 mg nifedipine (n = 10) and 0.025 to 0.2 mg/h nitroglycerin patch (n = 11) on supine BP, renal sodium handling, and orthostatic tolerance was determined. Medications were given at 8 p.m.; patients stood up at 8 a.m. Nitroglycerin was removed at 6 a.m. Compared with placebo, nifedipine and nitroglycerin decreased systolic BP during the night by a maximum of 37 +/- 9 and 36 +/- 10 mmHg, respectively (P < 0.01). At 8 a.m., supine systolic BP was 23 +/- 7 mmHg lower with nifedipine than with placebo (P < 0.05), but was similar with nitroglycerin and placebo. Sodium excretion during the night was not reduced with nitroglycerin (0.13 +/- 0.02 mmol/mg creatinine [Cr] versus 0.15 +/- 0.03 mmol/mg Cr with placebo), but it was increased with nifedipine (0.35 +/- 0.06 mmol/mg Cr versus 0.13 +/- 0.02 mmol/mg Cr with placebo, P < 0.05). Nifedipine but not nitroglycerin worsened orthostatic hypotension in the morning. It is concluded that nifedipine and transdermal nitroglycerin are effective in controlling supine hypertension in patients with autonomic failure. However, nifedipine has a prolonged depressor effect and worsens orthostatic hypotension in the morning. The decrease in pressure natriuresis that would be expected with the substantial decrease in BP obtained with nitroglycerin and nifedipine may be offset by a direct effect of both drugs on renal sodium handling.

Cluster headache: present and future therapy.

PubMed

Leone, Massimo; Giustiniani, Alessandro; Cecchini, Alberto Proietti

2017-05-01

Cluster headache is characterized by severe, unilateral headache attacks of orbital, supraorbital or temporal pain lasting 15-180 min accompanied by ipsilateral lacrimation, rhinorrhea and other cranial autonomic manifestations. Cluster headache attacks need fast-acting abortive agents because the pain peaks very quickly; sumatriptan injection is the gold standard acute treatment. First-line preventative drugs include verapamil and carbolithium. Other drugs demonstrated effective in open trials include topiramate, valproic acid, gabapentin and others. Steroids are very effective; local injection in the occipital area is also effective but its prolonged use needs caution. Monoclonal antibodies against calcitonin gene-related peptide are under investigation as prophylactic agents in both episodic and chronic cluster headache. A number of neurostimulation procedures including occipital nerve stimulation, vagus nerve stimulation, sphenopalatine ganglion stimulation and the more invasive hypothalamic stimulation are employed in chronic intractable cluster headache.

Diagnosis of multiple system atrophy

PubMed Central

Palma, Jose-Alberto; Norcliffe-Kaufmann, Lucy; Kaufmann, Horacio

2017-01-01

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs. PMID:29111419

Effects of propranolol on conversational reciprocity in autism spectrum disorder: a pilot, double-blind, single-dose psychopharmacological challenge study.

PubMed

Zamzow, Rachel M; Ferguson, Bradley J; Stichter, Janine P; Porges, Eric C; Ragsdale, Alexandra S; Lewis, Morgan L; Beversdorf, David Q

2016-04-01

Pharmacological intervention for autism spectrum disorder (ASD) is an important addition to treatment, yet currently available agents target co-morbid psychiatric concerns, such as aggression and irritability. Propranolol, a beta-adrenergic antagonist with anxiolytic effects, has been shown to improve verbal fluency and working memory in adults and adolescents with ASD in single-dose challenges. The present pilot study explores the acute effects of propranolol on a measure of conversational reciprocity in this population. We also examined whether autonomic activity and anxiety moderate or mediate response to the drug, given relationships between these variables and ASD, as well as the drug's effects. In a within-subject crossover design, 20 individuals with ASD received a single dose of propranolol or placebo during two sessions in a double-blinded, counterbalanced manner. After drug administration, participants performed a conversational reciprocity task by engaging in a short conversation with the researcher. Measurements of autonomic activity and anxiety were obtained before and after drug administration. Propranolol significantly improved performance on the conversational reciprocity task total [d = 0.40] and nonverbal communication domain scores when compared to the placebo condition. However, neither autonomic activity nor anxiety was significantly associated with drug response. Acute propranolol administration improved conversational reciprocity in ASD. Further exploration of these preliminary findings, as well as other potential treatment response predictors, with serial doses is warranted.

Autonomic self-healing in epoxidized natural rubber.

PubMed

Rahman, Arifur; Sartore, Luciana; Bignotti, Fabio; Di Landro, Luca

2013-02-01

The development of polymers that can repair damage autonomously would be useful to improve the lifetime of polymeric materials. To date, limited attention has been dedicated to developing elastomers with autonomic self-healing ability, which can recover damages without need for an external or internal source of healing agents. This work investigates the self-healing behavior of epoxidized natural rubber (ENR) with two different epoxidation levels (25 and 50 mol % epoxidation) and of the corresponding unfunctionalized rubber, cis-1,4-polyisoprene (PISP). A self-adhesion assisted self-healing behavior was revealed by T-peel tests on slightly vulcanized rubbers. A higher epoxidation level was found to enhance self-healing. Self-healing of rubbers following ballistic damages was also investigated. A pressurized air flow test setup was used to evaluate the self-healing of ballistic damages in rubbers. Microscope (OM, SEM, and TEM) analyses were carried out to provide further evidence of healing in the impact zones. Self-healing of ballistic damages was observed only in ENR with 50 mol % epoxidation and it was found to be influenced significantly by the cross-link density. Finally, self-healing of ballistic damages was also observed in ENR50/PISP blends only when the content of the healing component (i.e., ENR50) was at least 25 wt %. From an analysis of the results, it was concluded that a synergistic effect between interdiffusion and interaction among polar groups leads to self-healing in ENR.

The influence of oxazaphosphorines alkylating agents on autonomic nervous system activity in rat experimental cystitis model.

PubMed

Dobrek, Łukasz; Baranowska, Agnieszka; Thor, Piotr J

2013-01-01

The oxazaphosphorines alkylating agents (cyclophosphamide; CP and ifosfamide; IF) are often used in common clinical practice. However, treatment with CP/IF is burdened with the risk of many adverse drug reactions, especially including hemorrhagic cystitis (HC) that is associated with bladder overactivity symptoms (OAB). The HC pathophysiology is still not fully displayed; it seems that autonomic nervous system (ANS) functional abnormalities play important role in this disturbance. The aim of our study was to reveal the potential ANS differences in rat experimental HC model, evoked by CP and IF by an indirect ANS assessment--heart rate variability (HRV) study. We carried out our experimental research in three essential groups: control group (group 1), cyclophosphamide-induced HC (CP-HC; group 2) one and ifosfamide-induced HC (IF-HC; group 3) one. CP was i.p. administrated four times in dose of 75 mg/kg body weight while IF-treated rats received i.p. five drug doses; 50 mg/kg body weight. Control rats were administrated i.p. vehicle in appropriate volumes as CP/IF treated animals. HRV studies were performed the next day after the last oxazaphosphorines dose. Standard time- and spectral (frequency) domain parameters were estimated. We confirmed the HC development after both CP/IF in macroscopic assessment and bladder wet weight measurement; however, it was more aggravated in CP-HC group. Moreover, we demonstrated HRV disturbances, suggesting ANS impairment after both studied oxazaphosphorines, however, consistent with the findings mentioned above, the autonomic dysfunction was more emphasized after CP. CP treatment was also associated with changes of non-normalized HRV spectral components percentage distribution--a marked very low frequency--VLF [%] increase together with low frequency--LF [%] and high frequency--HF [%] decrease were observed. Taking into consideration the next findings, demonstrating the lack of both normalized power spectral components (nLF and nHF) values, the VLF percentage change seems to be of special meaning. IF produced smaller autonomic disturbances, and gentler bladders histological abnormalities comparing to CP. However, similar to CP, VLF [%] relative augmentation together with LF [%] and HF [%] drop accompanied the global ANS activity decrease. Additionally, in the case of IF treatment, a slight trend of nLF increase with nHF decrease was noted, suggesting the possible functional rearrangement between sympathetic (nLF) and parasympathetic (nHF) tension. It seems possible that the vagal withdrawal and--as a consequence--sympathetic overactivity, reflected by VLF [%] enlargement and HF and LF [%] diminishing (as well as LF and HF values decrease), may be an evidence of impaired anti-inflammatory cholinergic pathway, aggravating bladder inflammatory lesions. To sum up, our study showed ANS impairment in both CP- and IF-evoked experimental HC that was reflected in HRV recordings. HRV study, thus, may be considered to be a diagnostic tool for CP/IF treated patients, estimating autonomic abnormalities, associated with the HC development risk and its clinical course.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

SLAM algorithm applied to robotics assistance for navigation in unknown environments.

PubMed

Cheein, Fernando A Auat; Lopez, Natalia; Soria, Carlos M; di Sciascio, Fernando A; Pereira, Fernando Lobo; Carelli, Ricardo

2010-02-17

The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.

Life Science Research in Outer Space: New Platform Technologies for Low-Cost, Autonomous Small Satellite Missions

NASA Technical Reports Server (NTRS)

Ricco, Antonio J.; Parra, Macarena P.; Niesel, David; McGinnis, Michael; Ehrenfreund, Pascale; Nicholson, Wayne; Mancinelli, Rocco; Piccini, Matthew E.; Beasley, Christopher C.; Timucin, Linda R.;

Agent Transparency for an Autonomous Squad Member

DTIC Science & Technology

2015-05-01

C. Attentional  Control  Survey  41  Appendix D. System Usability Scale  45  Appendix E. Modified Jian Pre‐Post Trust Survey  47  Appendix F.  Posttest ...failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE...information in a simulation-based unmanned ground vehicle monitoring task. Three groups were tested with visual displays representing 1 of 3 types of

Does stress induce bowel dysfunction?

PubMed

Chang, Yu-Ming; El-Zaatari, Mohamad; Kao, John Y

2014-08-01

Psychological stress is known to induce somatic symptoms. Classically, many gut physiological responses to stress are mediated by the hypothalamus-pituitary-adrenal axis. There is, however, a growing body of evidence of stress-induced corticotrophin-releasing factor (CRF) release causing bowel dysfunction through multiple pathways, either through the HPA axis, the autonomic nervous systems, or directly on the bowel itself. In addition, recent findings of CRF influencing the composition of gut microbiota lend support for the use of probiotics, antibiotics, and other microbiota-altering agents as potential therapeutic measures in stress-induced bowel dysfunction.

Flexible Wing Base Micro Aerial Vehicles: Micro Air Vehicles (MAVs) for Surveillance and Remote Sensor Delivery

NASA Technical Reports Server (NTRS)

Ifju, Peter

2002-01-01

Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).

An agent-based hydroeconomic model to evaluate water policies in Jordan

NASA Astrophysics Data System (ADS)

Yoon, J.; Gorelick, S.

2014-12-01

Modern water systems can be characterized by a complex network of institutional and private actors that represent competing sectors and interests. Identifying solutions to enhance water security in such systems calls for analysis that can adequately account for this level of complexity and interaction. Our work focuses on the development of a hierarchical, multi-agent, hydroeconomic model that attempts to realistically represent complex interactions between hydrologic and multi-faceted human systems. The model is applied to Jordan, one of the most water-poor countries in the world. In recent years, the water crisis in Jordan has escalated due to an ongoing drought and influx of refugees from regional conflicts. We adopt a modular approach in which biophysical modules simulate natural and engineering phenomena, and human modules represent behavior at multiple scales of decision making. The human modules employ agent-based modeling, in which agents act as autonomous decision makers at the transboundary, state, organizational, and user levels. A systematic nomenclature and conceptual framework is used to characterize model agents and modules. Concepts from the Unified Modeling Language (UML) are adopted to promote clear conceptualization of model classes and process sequencing, establishing a foundation for full deployment of the integrated model in a scalable object-oriented programming environment. Although the framework is applied to the Jordanian water context, it is generalizable to other regional human-natural freshwater supply systems.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

PubMed

Raju, Leo; Milton, R S; Mahadevan, Senthilkumaran

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX

PubMed Central

Raju, Leo; Milton, R. S.; Mahadevan, Senthilkumaran

2016-01-01

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations. PMID:27127802

A constructivist connectionist model of transitions on false-belief tasks.

PubMed

Berthiaume, Vincent G; Shultz, Thomas R; Onishi, Kristine H

2013-03-01

How do children come to understand that others have mental representations, e.g., of an object's location? Preschoolers go through two transitions on verbal false-belief tasks, in which they have to predict where an agent will search for an object that was moved in her absence. First, while three-and-a-half-year-olds usually fail at approach tasks, in which the agent wants to find the object, children just under four succeed. Second, only after four do children succeed at tasks in which the agent wants to avoid the object. We present a constructivist connectionist model that autonomously reproduces the two transitions and suggests that the transitions are due to increases in general processing abilities enabling children to (1) overcome a default true-belief attribution by distinguishing false- from true-belief situations, and to (2) predict search in avoidance situations, where there is often more than one correct, empty search location. Constructivist connectionist models are rigorous, flexible and powerful tools that can be analyzed before and after transitions to uncover novel and emergent mechanisms of cognitive development. Copyright © 2012 Elsevier B.V. All rights reserved.

Agent-Based Intelligent Interface for Wheelchair Movement Control

PubMed Central

Barriuso, Alberto L.; De Paz, Juan F.

2018-01-01

People who suffer from any kind of motor difficulty face serious complications to autonomously move in their daily lives. However, a growing number research projects which propose different powered wheelchairs control systems are arising. Despite of the interest of the research community in the area, there is no platform that allows an easy integration of various control methods that make use of heterogeneous sensors and computationally demanding algorithms. In this work, an architecture based on virtual organizations of agents is proposed that makes use of a flexible and scalable communication protocol that allows the deployment of embedded agents in computationally limited devices. In order to validate the proper functioning of the proposed system, it has been integrated into a conventional wheelchair and a set of alternative control interfaces have been developed and deployed, including a portable electroencephalography system, a voice interface or as specifically designed smartphone application. A set of tests were conducted to test both the platform adequacy and the accuracy and ease of use of the proposed control systems yielding positive results that can be useful in further wheelchair interfaces design and implementation. PMID:29751603

Autonomous change of behavior for environmental context: An intermittent search model with misunderstanding search pattern

NASA Astrophysics Data System (ADS)

Murakami, Hisashi; Gunji, Yukio-Pegio

2017-07-01

Although foraging patterns have long been predicted to optimally adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, i.e., careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, i.e., the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an optimal change of strategy from Brownian-type to Lévy-type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.

Ravines and Sugar Pills: Defending Deceptive Placebo Use

PubMed Central

2015-01-01

In this paper, I argue that deceptive placebo use can be morally permissible, on the grounds that the deception involved in the prescription of deceptive placebos can differ in kind to the sorts of deception that undermine personal autonomy. In order to argue this, I shall first delineate two accounts of why deception is inimical to autonomy. On these accounts, deception is understood to be inimical to the deceived agent’s autonomy because it either involves subjugating the deceived agent’s will to another’s authority or because it precludes the agent from acting effectively in pursuit of their ends. I shall argue that providing an agent with false beliefs is not inimical to their autonomy if they are only able to effectively pursue their autonomously chosen ends by virtue of holding those particular false beliefs. Finally, I show that deceptive placebo use need only involve this latter sort of deception. PMID:25503607

Phytochemical and genetic analyses of ancient cannabis from Central Asia

PubMed Central

Russo, Ethan B.; Jiang, Hong-En; Li, Xiao; Sutton, Alan; Carboni, Andrea; del Bianco, Francesca; Mandolino, Giuseppe; Potter, David J.; Zhao, You-Xing; Bera, Subir; Zhang, Yong-Bing; Lü, En-Guo; Ferguson, David K.; Hueber, Francis; Zhao, Liang-Cheng; Liu, Chang-Jiang; Wang, Yu-Fei; Li, Cheng-Sen

2008-01-01

The Yanghai Tombs near Turpan, Xinjiang-Uighur Autonomous Region, China have recently been excavated to reveal the 2700-year-old grave of a Caucasoid shaman whose accoutrements included a large cache of cannabis, superbly preserved by climatic and burial conditions. A multidisciplinary international team demonstrated through botanical examination, phytochemical investigation, and genetic deoxyribonucleic acid analysis by polymerase chain reaction that this material contained tetrahydrocannabinol, the psychoactive component of cannabis, its oxidative degradation product, cannabinol, other metabolites, and its synthetic enzyme, tetrahydrocannabinolic acid synthase, as well as a novel genetic variant with two single nucleotide polymorphisms. The cannabis was presumably employed by this culture as a medicinal or psychoactive agent, or an aid to divination. To our knowledge, these investigations provide the oldest documentation of cannabis as a pharmacologically active agent, and contribute to the medical and archaeological record of this pre-Silk Road culture. PMID:19036842

Development of an evolutionary simulator and an overall control system for intelligent wheelchair

NASA Astrophysics Data System (ADS)

Imai, Makoto; Kawato, Koji; Hamagami, Tomoki; Hirata, Hironori

The goal of this research is to develop an intelligent wheelchair (IWC) system which aids an indoor safe mobility for elderly and disabled people with a new conceptual architecture which realizes autonomy, cooperativeness, and a collaboration behavior. In order to develop the IWC system in real environment, we need design-tools and flexible architecture. In particular, as more significant ones, this paper describes two key techniques which are an evolutionary simulation and an overall control mechanism. The evolutionary simulation technique corrects the error between the virtual environment in a simulator and real one in during the learning of an IWC agent, and coevolves with the agent. The overall control mechanism is implemented with subsumption architecture which is employed in an autonomous robot controller. By using these techniques in both simulations and experiments, we confirm that our IWC system acquires autonomy, cooperativeness, and a collaboration behavior efficiently.

IDENTIFICATION AND MANAGEMENT OF ALCOHOL WITHDRAWAL SYNDROME

PubMed Central

Mirijello, Antonio; D’Angelo, Cristina; Ferrulli, Anna; Vassallo, Gabriele; Antonelli, Mariangela; Caputo, Fabio; Leggio, Lorenzo; Gasbarrini, Antonio; Addolorato, Giovanni

2016-01-01

Symptoms of alcohol withdrawal syndrome may develop within 6–24 hours after the abrupt discontinuation or decrease of alcohol consumption. Symptoms can vary from autonomic hyperactivity and agitation to delirium tremens. The gold-standard treatment for alcohol withdrawal syndrome is represented by benzodiazepines. Among them, different agents (i.e., long-acting or short-acting) and different regimens (front-loading, fixed dose or symptom-triggered) may be chosen on the basis of patient characteristics. Severe withdrawal could require ICU admission and the use of barbiturates or propofol. Other drugs, such as alpha2-agonists (clonidine and dexmetedomidine) and beta-blockers can be used as adjunctive treatments to control neuroautonomic hyperactivity. Furthermore, neuroleptics can help control hallucinations. Finally, other medications for the treatment for alcohol withdrawal syndrome have been investigated with promising results. These include carbamazepine, valproate, sodium oxybate, baclofen, gabapentin, and topiramate. The usefulness of these agents will be discussed in the text. PMID:25666543

Automated Bilateral Negotiation and Bargaining Impasse

NASA Astrophysics Data System (ADS)

Lopes, Fernando; Novais, A. Q.; Coelho, Helder

The design and implementation of autonomous negotiating agents involve the consideration of insights from multiple relevant research areas to integrate different perspectives on negotiation. As a starting point for an interdisciplinary research effort, this paper employs game-theoretic techniques to define equilibrium strategies for the bargaining game of alternating offers and formalizes a set of negotiation strategies studied in the social sciences. This paper also shifts the emphasis to negotiations that are "difficult" to resolve and can hit an impasse. Specifically, it analyses a situation where two agents bargain over the division of the surplus of several distinct issues to demonstrate how a procedure to avoid impasses can be utilized in a specific negotiation setting. The procedure is based on the addition of new issues to the agenda during the course of negotiation and the exploration of the differences in the valuation of these issues to capitalize on Pareto optimal agreements.

Leader-Follower Output Synchronization of Linear Heterogeneous Systems With Active Leader Using Reinforcement Learning.

PubMed

Yang, Yongliang; Modares, Hamidreza; Wunsch, Donald C; Yin, Yixin

2018-06-01

This paper develops optimal control protocols for the distributed output synchronization problem of leader-follower multiagent systems with an active leader. Agents are assumed to be heterogeneous with different dynamics and dimensions. The desired trajectory is assumed to be preplanned and is generated by the leader. Other follower agents autonomously synchronize to the leader by interacting with each other using a communication network. The leader is assumed to be active in the sense that it has a nonzero control input so that it can act independently and update its control to keep the followers away from possible danger. A distributed observer is first designed to estimate the leader's state and generate the reference signal for each follower. Then, the output synchronization of leader-follower systems with an active leader is formulated as a distributed optimal tracking problem, and inhomogeneous algebraic Riccati equations (AREs) are derived to solve it. The resulting distributed optimal control protocols not only minimize the steady-state error but also optimize the transient response of the agents. An off-policy reinforcement learning algorithm is developed to solve the inhomogeneous AREs online in real time and without requiring any knowledge of the agents' dynamics. Finally, two simulation examples are conducted to illustrate the effectiveness of the proposed algorithm.

Model-free learning on robot kinematic chains using a nested multi-agent topology

NASA Astrophysics Data System (ADS)

Karigiannis, John N.; Tzafestas, Costas S.

2016-11-01

This paper proposes a model-free learning scheme for the developmental acquisition of robot kinematic control and dexterous manipulation skills. The approach is based on a nested-hierarchical multi-agent architecture that intuitively encapsulates the topology of robot kinematic chains, where the activity of each independent degree-of-freedom (DOF) is finally mapped onto a distinct agent. Each one of those agents progressively evolves a local kinematic control strategy in a game-theoretic sense, that is, based on a partial (local) view of the whole system topology, which is incrementally updated through a recursive communication process according to the nested-hierarchical topology. Learning is thus approached not through demonstration and training but through an autonomous self-exploration process. A fuzzy reinforcement learning scheme is employed within each agent to enable efficient exploration in a continuous state-action domain. This paper constitutes in fact a proof of concept, demonstrating that global dexterous manipulation skills can indeed evolve through such a distributed iterative learning of local agent sensorimotor mappings. The main motivation behind the development of such an incremental multi-agent topology is to enhance system modularity, to facilitate extensibility to more complex problem domains and to improve robustness with respect to structural variations including unpredictable internal failures. These attributes of the proposed system are assessed in this paper through numerical experiments in different robot manipulation task scenarios, involving both single and multi-robot kinematic chains. The generalisation capacity of the learning scheme is experimentally assessed and robustness properties of the multi-agent system are also evaluated with respect to unpredictable variations in the kinematic topology. Furthermore, these numerical experiments demonstrate the scalability properties of the proposed nested-hierarchical architecture, where new agents can be recursively added in the hierarchy to encapsulate individual active DOFs. The results presented in this paper demonstrate the feasibility of such a distributed multi-agent control framework, showing that the solutions which emerge are plausible and near-optimal. Numerical efficiency and computational cost issues are also discussed.

Zebrafish heart as a model to study the integrative autonomic control of pacemaker function

PubMed Central

Stoyek, Matthew R.; Quinn, T. Alexander; Croll, Roger P.

2016-01-01

The cardiac pacemaker sets the heart's primary rate, with pacemaker discharge controlled by the autonomic nervous system through intracardiac ganglia. A fundamental issue in understanding the relationship between neural activity and cardiac chronotropy is the identification of neuronal populations that control pacemaker cells. To date, most studies of neurocardiac control have been done in mammalian species, where neurons are embedded in and distributed throughout the heart, so they are largely inaccessible for whole-organ, integrative studies. Here, we establish the isolated, innervated zebrafish heart as a novel alternative model for studies of autonomic control of heart rate. Stimulation of individual cardiac vagosympathetic nerve trunks evoked bradycardia (parasympathetic activation) and tachycardia (sympathetic activation). Simultaneous stimulation of both vagosympathetic nerve trunks evoked a summative effect. Effects of nerve stimulation were mimicked by direct application of cholinergic and adrenergic agents. Optical mapping of electrical activity confirmed the sinoatrial region as the site of origin of normal pacemaker activity and identified a secondary pacemaker in the atrioventricular region. Strong vagosympathetic nerve stimulation resulted in a shift in the origin of initial excitation from the sinoatrial pacemaker to the atrioventricular pacemaker. Putative pacemaker cells in the sinoatrial and atrioventricular regions expressed adrenergic β2 and cholinergic muscarinic type 2 receptors. Collectively, we have demonstrated that the zebrafish heart contains the accepted hallmarks of vertebrate cardiac control, establishing this preparation as a viable model for studies of integrative physiological control of cardiac function by intracardiac neurons. PMID:27342878

Diagnosis of multiple system atrophy.

PubMed

Palma, Jose-Alberto; Norcliffe-Kaufmann, Lucy; Kaufmann, Horacio

2018-05-01

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of acute beta-adrenergic antagonism on verbal problem solving in autism spectrum disorder and exploration of treatment response markers.

PubMed

Zamzow, Rachel M; Ferguson, Bradley J; Ragsdale, Alexandra S; Lewis, Morgan L; Beversdorf, David Q

2017-08-01

Autism spectrum disorder (ASD) is characterized by impairments in social communication as well as restricted, repetitive behaviors. Evidence suggests that some individuals with ASD have cognitive impairments related to weak central coherence and hyperrestricted processing. Reducing noradrenergic activity may improve aspects of network processing and thus improve cognitive abilities, such as verbal problem solving, in individuals with ASD. The present pilot study explores the effects of acute administration of the beta-adrenergic antagonist propranolol on verbal problem solving in adults and adolescents with ASD. In a within-subject crossover-design, 20 participants with ASD received a single dose of propranolol or placebo on one of two sessions in a double-blinded, counterbalanced manner. Verbal problem solving was assessed via an anagram task. Baseline measurements of autonomic nervous system functioning were obtained, and anxiety was assessed at baseline and following drug administration. Participants solved the anagrams more quickly in the propranolol condition, as compared to the placebo condition, suggesting a potential cognitive benefit of this agent. Additionally, we observed a negative linear relationship between response to propranolol on the anagram task and two measures of baseline autonomic activity, as well as a positive linear relationship between drug response and baseline anxiety. These relationships propose potential markers for treatment response, as propranolol influences both autonomic functioning and anxiety. Further investigation is needed to expand on the present single-dose psychopharmacological challenge and explore the observed effects of propranolol in a serial-dose setting.

Autophagy induction for the treatment of cancer.

PubMed

Pietrocola, Federico; Pol, Jonathan; Vacchelli, Erika; Baracco, Elisa E; Levesque, Sarah; Castoldi, Francesca; Maiuri, Maria Chiara; Madeo, Frank; Kroemer, Guido

2016-10-02

Cancer can be viewed in 2 rather distinct ways, namely (i) as a cell-autonomous disease in which malignant cells have escaped control from cell-intrinsic barriers against proliferation and dissemination or (ii) as a systemic disease that involves failing immune control of aberrant cells. Since macroautophagy/autophagy generally increases the fitness of cells as well as their resistance against endogenous or iatrogenic (i.e., relating to illness due to medical intervention) stress, it has been widely proposed that inhibition of autophagy would constitute a valid strategy for sensitizing cancer cells to chemotherapy or radiotherapy. Colliding with this cell-autonomous vision, however, we found that immunosurveillance against transplantable, carcinogen-induced or genetically engineered cancers can be improved by pharmacologically inducing autophagy with caloric restriction mimetics. This positive effect depends on autophagy induction in cancer cells and is mediated by alterations in extracellular ATP metabolism, namely increased release of immunostimulatory ATP and reduced adenosine-dependent recruitment of immunosuppressive regulatory T cells into the tumor bed. The combination of autophagy inducers and chemotherapeutic agents is particularly efficient in reducing cancer growth through the stimulation of CD8 + T lymphocyte-dependent anticancer immune responses.

Autonomous Preference-Aware Information Services Integration for High Response in Integrated Faded Information Field Systems

NASA Astrophysics Data System (ADS)

Lu, Xiaodong; Mori, Kinji

The market and users' requirements have been rapidly changing and diversified. Under these heterogeneous and dynamic situations, not only the system structure itself, but also the accessible information services would be changed constantly. To cope with the continuously changing conditions of service provision and utilization, Faded Information Field (FIF) has been proposed, which is a agent-based distributed information service system architecture. In the case of a mono-service request, the system is designed to improve users' access time and preserve load balancing through the information structure. However, with interdependent requests of multi-service increasing, adaptability and timeliness have to be assured by the system. In this paper, the relationship that exists among the correlated services and the users' preferences for separate and integrated services is clarified. Based on these factors, the autonomous preference-aware information services integration technology to provide one-stop service for users multi-service requests is proposed. As compared to the conventional system, we show that proposed technology is able to reduce the total access time.

Nocturnal Anxiety in a Youth with Rapid-onset Obesity, Hypothalamic Dysfunction, Hypoventilation, and Autonomic Dysregulation (ROHHAD).

PubMed

Grudnikoff, Eugene; Foley, Carmel; Poole, Claudette; Theodosiadis, Eva

2013-08-01

Behavioral and psychiatric disorders are common in youth with rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD). We outline a rational approach to psychiatric treatment of a patient with a complex medical condition. We report the course of symptoms in a teen with ROHHAD, the inpatient treatment, and review current evidence for use of psychopharmacologic agents in youth with sleep and anxiety disturbances. A 14-year-old female began rapidly gaining weight as a preschooler, developed hormonal imbalance, and mixed sleep apnea. Consultation was requested after a month of ROHHAD exacerbation, with severe anxiety, insomnia, and auditory hallucinations. Olanzapine and citalopram were helpful in controlling the symptoms. Following discharge, the patient gained weight and olanzapine was discontinued. Lorazepam was started in coordination with pulmonary service. Relevant pharmacologic considerations included risk of respiratory suppression, history of paradoxical reaction to hypnotics, hepatic isoenzyme interactions and side effects of antipsychotics. Core symptoms of ROHHAD may precipitate psychiatric disorders. A systematic evidence-based approach to psychopharmacology is necessary in the setting of psychiatric consultation.

Nocturnal Anxiety in a Youth with Rapid-onset Obesity, Hypothalamic Dysfunction, Hypoventilation, and Autonomic Dysregulation (ROHHAD)

PubMed Central

Grudnikoff, Eugene; Foley, Carmel; Poole, Claudette; Theodosiadis, Eva

2013-01-01

Objective: Behavioral and psychiatric disorders are common in youth with rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD). We outline a rational approach to psychiatric treatment of a patient with a complex medical condition. Methods: We report the course of symptoms in a teen with ROHHAD, the inpatient treatment, and review current evidence for use of psychopharmacologic agents in youth with sleep and anxiety disturbances. Results: A 14-year-old female began rapidly gaining weight as a preschooler, developed hormonal imbalance, and mixed sleep apnea. Consultation was requested after a month of ROHHAD exacerbation, with severe anxiety, insomnia, and auditory hallucinations. Olanzapine and citalopram were helpful in controlling the symptoms. Following discharge, the patient gained weight and olanzapine was discontinued. Lorazepam was started in coordination with pulmonary service. Relevant pharmacologic considerations included risk of respiratory suppression, history of paradoxical reaction to hypnotics, hepatic isoenzyme interactions and side effects of antipsychotics. Conclusions: Core symptoms of ROHHAD may precipitate psychiatric disorders. A systematic evidence-based approach to psychopharmacology is necessary in the setting of psychiatric consultation. PMID:23970913

Overview of Intelligent Systems and Operations Development

NASA Technical Reports Server (NTRS)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles

PubMed Central

Atman, Jamal; Popp, Manuel; Ruppelt, Jan; Trommer, Gert F.

2016-01-01

Micro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV’s navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results. PMID:27649203

How should a virtual agent present psychoeducation? Influence of verbal and textual presentation on adherence

PubMed Central

Tielman, Myrthe L.; Neerincx, Mark A.; van Meggelen, Marieke; Franken, Ingmar; Brinkman, Willem-Paul

2017-01-01

BACKGROUND AND OBJECTIVE: With the rise of autonomous e-mental health applications, virtual agents can play a major role in improving trustworthiness, therapy outcome and adherence. In these applications, it is important that patients adhere in the sense that they perform the tasks, but also that they adhere to the specific recommendations on how to do them well. One important construct in improving adherence is psychoeducation, information on the why and how of therapeutic interventions. In an e-mental health context, this can be delivered in two different ways: verbally by a (virtual) embodied conversational agent or just via text on the screen. The aim of this research is to study which presentation mode is preferable for improving adherence. METHODS : This study takes the approach of evaluating a specific part of a therapy, namely psychoeducation. This was done in a non-clinical sample, to first test the general constructs of the human-computer interaction. We performed an experimental study on the effect of presentation mode of psychoeducation on adherence. In this study, we took into account the moderating effects of attitude towards the virtual agent and recollection of the information. Within the paradigm of expressive writing, we asked participants (n= 46) to pick one of their worst memories to describe in a digital diary after receiving verbal or textual psychoeducation. RESULTS AND CONCLUSION: We found that both the attitude towards the virtual agent and how well the psychoeducation was recollected were positively related to adherence in the form of task execution. Moreover, after controlling for the attitude to the agent and recollection, presentation of psychoeducation via text resulted in higher adherence than verbal presentation by the virtual agent did. PMID:28800346

A Hybrid Approach for Fault Detection in Autonomous Physical Agents

DTIC Science & Technology

2014-05-01

r l e c c f t d f a d c r r r t m e o i m s f U m d o s a u v c o t c r c t a c u n b S...escription e a set of attrib d, heading, pi et of values for alue assigned to t i s 1 l m a o p a r tr l c tr w o t n data H & ow detection mode roach is...dete Note that any ch can be used t e an autonomou e SFDD

Recent advances in the treatment of orthostatic hypotension

NASA Technical Reports Server (NTRS)

Robertson, D.; Davis, T. L.

1995-01-01

Orthostatic hypotension is a fall in blood pressure on standing that causes symptoms of dizziness, visual changes, and discomfort in the head and neck. The goal of treatment is the improvement of the patient's functional capacity, rather than a target blood pressure. For treatment to be successful, it must be individualized. Non-pharmalogic interventions include carefully managed exercise, scheduled activities, and monitoring of the environmental temperature. Agents such as fludrocortisone, midodrine, and epoetin alfa offer successful pharmacologic interventions. Although these measures ease the symptoms of orthostatic hypotension, current approaches neither reverse nor stabilize the disease process in autonomic disorders.

A Formal Investigation of the Organization of Guidance Behavior: Implications for Humans and Autonomous Guidance

NASA Astrophysics Data System (ADS)

Kong, Zhaodan

Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.

ANTS: A New Concept for Very Remote Exploration with Intelligent Software Agents

NASA Astrophysics Data System (ADS)

Clark, P. E.; Curtis, S.; Rilee, M.; Truszkowski, W.; Iyengar, J.; Crawford, H.

2001-12-01

ANTS (Autonomous Nano-Technology Swarm), a NASA advanced mission concept, is a large (100 to 1000 member) swarm of pico-class (1 kg) totally autonomous spacecraft that prospect the asteroid belt. As the capacity and complexity of hardware and software, and the sophistication of technical and scientific goals have increased, greater cost constraints have led to fewer resources and thus, the need to operate spacecraft with less frequent contact. At present, autonomous operation of spacecraft systems allows great capability of spacecraft to 'safe' themselves when conditions threaten spacecraft safety. To further develop spacecraft capability, NASA is at the forefront of Intelligent Software Agent (ISA) research, performing experiments in space and on the ground to advance deliberative and collaborative autonomous control techniques. Selected missions in current planning stages require small groups of spacecraft to cooperate at a tactical level to select and schedule measurements to be made by appropriate instruments to characterize rapidly unfolding real-time events on a routine basis. The next level of development, which we are considering here, is in the use of ISAs at a strategic level, to explore the final, remote frontiers of the solar system, potentially involving a large class of objects with only infrequent contact possible. Obvious mission candidates are mainbelt asteroids, a population consisting of more than a million small bodies. Although a large fraction of solar system objects are asteroids, little data is available for them because the vast majority of them are too small to be observed except in close proximity. Asteroids originated in the transitional region between the inner (rocky) and outer (solidified gases) solar system, have remained largely unmodified since formation, and thus have a more primitive composition which includes higher abundances of siderophile (metallic iron-associated) elements and volatiles than other planetary surfaces. As a result, there has been interest in asteroids as sources of exploitable resources. Far more reconnaissance is required before such a program is undertaken. A traditional mission approach (to explore larger asteroids sequentially) is not adequate for determining the systematic distribution of exploitable material in the asteroid population. Our approach involves the use of distributed intelligence in a swarm of tiny spacecraft, each with specialized instrument capability (e.g., advanced computing, imaging, spectrometry, etc.) to evaluate the resource potential of the entire population. Supervised clusters of spacecraft will operate simultaneously within a broadly defined framework of goals to select targets (>1000) from among available candidates and to develop scenarios for studying targets simultaneously. Spacecraft use solar sails to fly directly to asteroids 1 kilometer or greater in diameter. Selected swarm members return to Earth with data, replacements join the swarm as needed. We would like to acknowledge our students R. Watson, V. Cox, and F. Olukomo for their support of this work.

Design of a Mobile Agent-Based Adaptive Communication Middleware for Federations of Critical Infrastructure Simulations

NASA Astrophysics Data System (ADS)

Görbil, Gökçe; Gelenbe, Erol

The simulation of critical infrastructures (CI) can involve the use of diverse domain specific simulators that run on geographically distant sites. These diverse simulators must then be coordinated to run concurrently in order to evaluate the performance of critical infrastructures which influence each other, especially in emergency or resource-critical situations. We therefore describe the design of an adaptive communication middleware that provides reliable and real-time one-to-one and group communications for federations of CI simulators over a wide-area network (WAN). The proposed middleware is composed of mobile agent-based peer-to-peer (P2P) overlays, called virtual networks (VNets), to enable resilient, adaptive and real-time communications over unreliable and dynamic physical networks (PNets). The autonomous software agents comprising the communication middleware monitor their performance and the underlying PNet, and dynamically adapt the P2P overlay and migrate over the PNet in order to optimize communications according to the requirements of the federation and the current conditions of the PNet. Reliable communications is provided via redundancy within the communication middleware and intelligent migration of agents over the PNet. The proposed middleware integrates security methods in order to protect the communication infrastructure against attacks and provide privacy and anonymity to the participants of the federation. Experiments with an initial version of the communication middleware over a real-life networking testbed show that promising improvements can be obtained for unicast and group communications via the agent migration capability of our middleware.

Extending self-organizing particle systems to problem solving.

PubMed

Rodríguez, Alejandro; Reggia, James A

2004-01-01

Self-organizing particle systems consist of numerous autonomous, purely reflexive agents ("particles") whose collective movements through space are determined primarily by local influences they exert upon one another. Inspired by biological phenomena (bird flocking, fish schooling, etc.), particle systems have been used not only for biological modeling, but also increasingly for applications requiring the simulation of collective movements such as computer-generated animation. In this research, we take some first steps in extending particle systems so that they not only move collectively, but also solve simple problems. This is done by giving the individual particles (agents) a rudimentary intelligence in the form of a very limited memory and a top-down, goal-directed control mechanism that, triggered by appropriate conditions, switches them between different behavioral states and thus different movement dynamics. Such enhanced particle systems are shown to be able to function effectively in performing simulated search-and-collect tasks. Further, computational experiments show that collectively moving agent teams are more effective than similar but independently moving ones in carrying out such tasks, and that agent teams of either type that split off members of the collective to protect previously acquired resources are most effective. This work shows that the reflexive agents of contemporary particle systems can readily be extended to support goal-directed problem solving while retaining their collective movement behaviors. These results may prove useful not only for future modeling of animal behavior, but also in computer animation, coordinated movement control in robotic teams, particle swarm optimization, and computer games.

SLAM algorithm applied to robotics assistance for navigation in unknown environments

PubMed Central

2010-01-01

Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). Methods In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. Conclusions The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation. PMID:20163735

Effects of cilnidipine, a novel dihydropyridine calcium antagonist, on autonomic function, ambulatory blood pressure and heart rate in patients with essential hypertension.

PubMed

Minami, J; Kawano, Y; Makino, Y; Matsuoka, H; Takishita, S

2000-12-01

The aim of the present study was to evaluate the effects of cilnidipine, a novel dihydropyridine calcium antagonist, on autonomic function, ambulatory blood pressure and heart rate in patients with essential hypertension. Ten inpatients with mild to moderate essential hypertension (four men and six women; age: 44-64 years) underwent a drug-free period for 7 days and a treatment period with cilnidipine 10 mg orally for another 7 days, in a randomized crossover study. On the sixth day of each period, they underwent autonomic function tests including a mental arithmetic test, a cold pressor test and a Valsalva manoeuvre. After these tests, 24 h ambulatory blood pressure, heart rate, and the electrocardiogram R-R intervals were monitored every 30 min. A power spectral analysis of R-R intervals was performed to obtain the low-and high-frequency components. Cilnidipine significantly decreased the 24 h blood pressure by 6.5 +/- 1.7 mm Hg systolic (mean +/- s.e.mean; P < 0.01) and 5.0 +/- 1.1 mmHg diastolic (P < 0.01), whereas cilnidipine did not change heart rate or any indices of power spectral components. During the cold pressor test, the maximum change in systolic blood pressure and percentage changes in both systolic and diastolic blood pressures were significantly lower during the treatment period with cilnidipine than during the drug-free period. The baroreflex sensitivity measured from the overshoot phase of the Valsalva manoeuvre did not differ significantly between the two periods. Cilnidipine is effective as a once-daily antihypertensive agent and causes little influence on heart rate and the autonomic nervous system in patients with mild to moderate essential hypertension. Moreover, it is suggested that cilnidipine has an additional clinical benefit in the inhibition of the pressor response induced by acute cold stress.

Safe Exploration Algorithms for Reinforcement Learning Controllers.

PubMed

Mannucci, Tommaso; van Kampen, Erik-Jan; de Visser, Cornelis; Chu, Qiping

2018-04-01

Self-learning approaches, such as reinforcement learning, offer new possibilities for autonomous control of uncertain or time-varying systems. However, exploring an unknown environment under limited prediction capabilities is a challenge for a learning agent. If the environment is dangerous, free exploration can result in physical damage or in an otherwise unacceptable behavior. With respect to existing methods, the main contribution of this paper is the definition of a new approach that does not require global safety functions, nor specific formulations of the dynamics or of the environment, but relies on interval estimation of the dynamics of the agent during the exploration phase, assuming a limited capability of the agent to perceive the presence of incoming fatal states. Two algorithms are presented with this approach. The first is the Safety Handling Exploration with Risk Perception Algorithm (SHERPA), which provides safety by individuating temporary safety functions, called backups. SHERPA is shown in a simulated, simplified quadrotor task, for which dangerous states are avoided. The second algorithm, denominated OptiSHERPA, can safely handle more dynamically complex systems for which SHERPA is not sufficient through the use of safety metrics. An application of OptiSHERPA is simulated on an aircraft altitude control task.

Integrated Dynamic Process Planning and Scheduling in Flexible Manufacturing Systems via Autonomous Agents

NASA Astrophysics Data System (ADS)

Nejad, Hossein Tehrani Nik; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans and schedules in the dynamic manufacturing environment. A simulation software has been developed to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

Using Swarming Agents for Scalable Security in Large Network Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

Assessment of Composite Delamination Self-Healing Under Cyclic Loading

NASA Technical Reports Server (NTRS)

O'Brien, T. Kevin

2009-01-01

Recently, the promise of self-healing materials for enhanced autonomous durability has been introduced using a micro-encapsulation technique where a polymer based healing agent is encapsulated in thin walled spheres and embedded into a base polymer along with a catalyst phase. For this study, composite skin-stiffener flange debonding specimens were manufactured from composite prepreg containing interleaf layers with a polymer based healing agent encapsulated in thin-walled spheres. Constant amplitude fatigue tests in three-point bending showed the effect of self-healing on the fatigue response of the skin-stiffener flange coupons. After the cycling that created debonding, fatigue tests were held at the mean load for 24 hours. For roughly half the specimens tested, when the cyclic loading was resumed a decrease in compliance (increase in stiffness) was observed, indicating that some healing had occurred. However, with continued cycling, the specimen compliance eventually increased to the original level before the hold, indicating that the damage had returned to its original state. As was noted in a prevoius study conducted with specimens tested under monotonically increasing loads to failure, healing achieved via the micro-encapsulation technique may be limited to the volume of healing agent available relative to the crack volume.

Evidence-Responsiveness and the Ongoing Autonomy of Treatment Preferences.

PubMed

Weimer, Steven

2017-06-14

To be an autonomous agent is to determine one's own path in life. However, this cannot plausibly be seen as a one-off affair. An autonomous agent does not merely set herself on a particular course and then lock the steering wheel in place, so to speak, but must maintain some form of ongoing control over her direction in life-must keep her eyes on the road and her hands on the wheel. Circumstances often change in important and unexpected ways, after all, and it is reasonable to think that a crucial part of autonomy consists of the ability and disposition to recognize and properly respond to such changes. This implies, I contend, that a patient whose initial decision to undergo a given treatment satisfied plausible requirements of autonomy, but who is now unable to recognize that available evidence indicates the need to reconsider her medical situation and options has come to lack autonomy with respect to her desire to continue that treatment. However, and despite its importance with respect to both theoretical understandings of autonomy and applications of the concept to clinical ethics, this ongoing aspect of autonomy has received little attention. This paper aims to go some way toward remedying that. I first critically review two of the few theories of autonomy that do address "evidence-responsiveness" so as to identify and elaborate what I take to be the most promising way in which to account for this aspect of autonomy. After considering and responding to a possible objection to the evidence-responsiveness condition I propose, I conclude by discussing its clinical implications. That condition, I argue, is not merely theoretically sound, but can and should be applied to clinical practice.

Dual autonomic inhibitory action of central Apelin on gastric motor functions in rats.

PubMed

Bülbül, Mehmet; Sinen, Osman

2018-07-01

Centrally administered apelin has been shown to inhibit gastric emptying (GE) in rodents, however, the relevant mechanism has been investigated incompletely. Using male Wistar rats, we investigated the efferent pathways involved in gastroinhibitory action of central apelin. Stereotaxic intracerebroventricular (icv) cannulation, subdiaphragmatic vagotomy (VGX) and/or celiac ganglionectomy (CGX) were performed 7 days prior to the experiments. Apelin-13 was administered (30 nmol, icv) 90 min prior to GE measurement. Nitric oxide synthase inhibitor L-NAME (100 mg/kg), sympatholytic agent guanethidine (5 mg/kg) and/or muscarinic receptor agonist bethanechol (1 mg/kg) were administered intraperitoneally 30 min prior to the central apelin-13 injection. Two strain gages were implanted serosally onto antrum and pylorus to monitor gastric postprandial motility. Heart rate variability (HRV) analysis was performed before and after central vehicle or apelin-13 administration. Apelin-13 delayed solid GE significantly by disturbing coordinated antral and pyloric postprandial contractions. The apelin-induced delayed GE was attenuated partially by CGX or VGX, whereas it was restored completely in rats underwent both CGX and VGX. L-NAME did not change the apelin-induced alterations. Guanethidine or bethanechol restored the apelin-induced gastroinhibition partially, while it was abolished completely in rats received both agents. Apelin-13 decreased the HRV spectral activity in high-frequency range by increasing low-frequency component and the ratio of LF:HF. The present data suggest that (1) both vagal parasympathetic and sympathetic pathways play a role in apelin-induced gastroinhibition, (2) central apelin attenuates vagal cholinergic pathway rather than activating nonadrenergic-noncholinergic pathway. Apelin/APJ receptor system might be candidate for the treatment of autonomic dysfunction and gastrointestinal motor disorders. Copyright © 2018 Elsevier B.V. All rights reserved.

Acute and chronic effects of aerobic exercise on blood pressure in resistant hypertension: study protocol for a randomized controlled trial.

PubMed

Nascimento, L S; Santos, A C; Lucena, Jms; Silva, Lgo; Almeida, Aem; Brasileiro-Santos, M S

2017-06-02

Resistant hypertension is a specific condition that affects approximately 10% of subjects with hypertension, and is characterized by persistently high blood pressure levels even using therapy of three or more antihypertensive agents or with blood pressure control using therapy with four or more antihypertensive agents. Changes in lifestyle, such as physical exercise, are indicated for controlling blood pressure. However, investigating studies about this therapy in individuals with resistant hypertension are few. This is a randomized controlled clinical trial. Forty-eight patients with resistant hypertension will be submitted to perform four short-term interventions: aerobic exercise sessions (mild-, moderate- and high-intensity) and control session, in random order and on separate days. After the short-term sessions, the patients will be randomly allocated into four groups for 8 weeks of follow-up: mild-, moderate- and high-intensity aerobic exercise, and a control group. The primary outcome is the occurrence of blood pressure reduction (office and ambulatory analysis, and acute and chronic effects). Secondary outcomes are autonomic and hemodynamic mechanisms: cardiac and vasomotor autonomic modulation, spontaneous baroreflex sensitivity, forearm blood flow and vascular resistance. The importance of exercise for hypertension has been known for decades, but little is known about the effects on patients with resistant hypertension. This study will help to understand whether different aerobic exercise intensities can induce different responses, as well as by what mechanisms adjustments in blood pressure levels may occur. ClinicalTrials.gov, ID: NCT02670681 . Registered on 28 January 2016 (first version); Brazilian Registry Platform Clinical Trials: protocol RBR-5q24zh . Registered on 24 June 2015.

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

NASA Astrophysics Data System (ADS)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

The roles of the analogy with natural selection in B.F. Skinner's philosophy.

PubMed

Smith, Terry L

2018-02-17

Beginning in the 1950s, B.F. Skinner made increasing reference to an analogy between operant conditioning and natural selection. This analogy is the basis of an argument that, in contrast to Skinner's other critiques of cognitive science, is neither epistemological nor pragmatic. Instead, it is based on the claim that ontogenetic adaptation is due to a special mode of causation he called "selection by consequences." He argued that this mode of causation conflicts with explanations that attribute action to an autonomous agent with reasons for acting. This argument dismisses ordinary explanations of action, and has implications not only for cognitive science but also for morals. Skinner cited the latter implications to counter objections to the application of behavior analysis to the reform of society and its institutions. Skinner's critique, however, rests upon empirical assumptions that have been criticized by other behavior analysts. Although for Skinner the major role of the analogy was to propose an empirical thesis, it also can play a metaphysical role-namely, to demonstrate the possibility of ontogenetic adaptation without reference to agents who have reasons for acting. These two roles, empirical and metaphysical, are the mirror image of the empirical and metaphysical roles of the computer analogy for cognitive science. That analogy also can be (and has been) interpreted as an empirical thesis. Its empirical implications, however, have been difficult to confirm. It also, however, has played a metaphysical role-namely, to demonstrate the possibility that a physical process could perform logical operations on states having propositional content. Neither analogy provides a well-confirmed, general answer to the question of how to explain the process of ontogenetic adaptation. But together they show there are two metaphysically coherent, but conflicting, answers to this question. Depending upon one's epistemology, the analogy with natural selection may provide a useful point of departure for a strategy of research. Such a pragmatic grounding for a research strategy does not, however, provide sufficient reason to abandon for purposes of ethics the concept of persons as autonomous agents. Copyright © 2018 Elsevier B.V. All rights reserved.

Extended Neural Metastability in an Embodied Model of Sensorimotor Coupling

PubMed Central

Aguilera, Miguel; Bedia, Manuel G.; Barandiaran, Xabier E.

2016-01-01

The hypothesis that brain organization is based on mechanisms of metastable synchronization in neural assemblies has been popularized during the last decades of neuroscientific research. Nevertheless, the role of body and environment for understanding the functioning of metastable assemblies is frequently dismissed. The main goal of this paper is to investigate the contribution of sensorimotor coupling to neural and behavioral metastability using a minimal computational model of plastic neural ensembles embedded in a robotic agent in a behavioral preference task. Our hypothesis is that, under some conditions, the metastability of the system is not restricted to the brain but extends to the system composed by the interaction of brain, body and environment. We test this idea, comparing an agent in continuous interaction with its environment in a task demanding behavioral flexibility with an equivalent model from the point of view of “internalist neuroscience.” A statistical characterization of our model and tools from information theory allow us to show how (1) the bidirectional coupling between agent and environment brings the system closer to a regime of criticality and triggers the emergence of additional metastable states which are not found in the brain in isolation but extended to the whole system of sensorimotor interaction, (2) the synaptic plasticity of the agent is fundamental to sustain open structures in the neural controller of the agent flexibly engaging and disengaging different behavioral patterns that sustain sensorimotor metastable states, and (3) these extended metastable states emerge when the agent generates an asymmetrical circular loop of causal interaction with its environment, in which the agent responds to variability of the environment at fast timescales while acting over the environment at slow timescales, suggesting the constitution of the agent as an autonomous entity actively modulating its sensorimotor coupling with the world. We conclude with a reflection about how our results contribute in a more general way to current progress in neuroscientific research. PMID:27721746

Extended Neural Metastability in an Embodied Model of Sensorimotor Coupling.

PubMed

Aguilera, Miguel; Bedia, Manuel G; Barandiaran, Xabier E

2016-01-01

The hypothesis that brain organization is based on mechanisms of metastable synchronization in neural assemblies has been popularized during the last decades of neuroscientific research. Nevertheless, the role of body and environment for understanding the functioning of metastable assemblies is frequently dismissed. The main goal of this paper is to investigate the contribution of sensorimotor coupling to neural and behavioral metastability using a minimal computational model of plastic neural ensembles embedded in a robotic agent in a behavioral preference task. Our hypothesis is that, under some conditions, the metastability of the system is not restricted to the brain but extends to the system composed by the interaction of brain, body and environment. We test this idea, comparing an agent in continuous interaction with its environment in a task demanding behavioral flexibility with an equivalent model from the point of view of "internalist neuroscience." A statistical characterization of our model and tools from information theory allow us to show how (1) the bidirectional coupling between agent and environment brings the system closer to a regime of criticality and triggers the emergence of additional metastable states which are not found in the brain in isolation but extended to the whole system of sensorimotor interaction, (2) the synaptic plasticity of the agent is fundamental to sustain open structures in the neural controller of the agent flexibly engaging and disengaging different behavioral patterns that sustain sensorimotor metastable states, and (3) these extended metastable states emerge when the agent generates an asymmetrical circular loop of causal interaction with its environment, in which the agent responds to variability of the environment at fast timescales while acting over the environment at slow timescales, suggesting the constitution of the agent as an autonomous entity actively modulating its sensorimotor coupling with the world. We conclude with a reflection about how our results contribute in a more general way to current progress in neuroscientific research.

Treating Diabetic Neuropathy: Present Strategies and Emerging Solutions

PubMed Central

Javed, Saad; Alam, Uazman; Malik, Rayaz A.

2015-01-01

Diabetic peripheral neuropathies (DPN) are a heterogeneous group of disorders caused by neuronal dysfunction in patients with diabetes. They have differing clinical courses, distributions, fiber involvement (large or small), and pathophysiology. These complications are associated with increased morbidity, distress, and healthcare costs. Approximately 50% of patients with diabetes develop peripheral neuropathy, and the projected rise in the global burden of diabetes is spurring an increase in neuropathy. Distal symmetrical polyneuropathy (DSPN) with painful diabetic neuropathy, occurring in around 20% of diabetes patients, and diabetic autonomic neuropathy (DAN) are the most common manifestations of DPN. Optimal glucose control represents the only broadly accepted therapeutic option though evidence of its benefit in type 2 diabetes is unclear. A number of symptomatic treatments are recommended in clinical guidelines for the management of painful DPN, including antidepressants such as amitriptyline and duloxetine, the γ-aminobutyric acid analogues gabapentin and pregabalin, opioids, and topical agents such as capsaicin. However, monotherapy is frequently not effective in achieving complete resolution of pain in DPN. There is a growing need for head-to-head studies of different single-drug and combination pharmacotherapies. Due to the ubiquity of autonomic innervation in the body, DAN causes a plethora of symptoms and signs affecting cardiovascular, urogenital, gastrointestinal, pupillomotor, thermoregulatory, and sudomotor systems. The current treatment of DAN is largely symptomatic, and does not correct the underlying autonomic nerve deficit. A number of novel potential candidates, including erythropoietin analogues, angiotensin II receptor type 2 antagonists, and sodium channel blockers are currently being evaluated in phase II clinical trials. PMID:26676662

N-Acetylmannosamine improves sleep-wake quality in middle-aged mice: relevance to autonomic nervous function.

PubMed

Kuwahara, Masayoshi; Ito, Koichi; Hayakawa, Koji; Yagi, Shintaro; Shiota, Kunio

2015-01-01

Aging is associated with a variety of physiological changes originating peripherally and centrally, including within the autonomic nervous system. Sleep-wake disturbances constitute reliable hallmarks of aging in several animal species and humans. Recent studies have been interested in N-acetylmannosamine (ManNAc) a potential therapeutic agent for improving quality of life, as well as preventing age-related cognitive decline. In this study, ManNAc (5.0 mg/ml) was administered in the drinking water of middle-aged male C57BL/6J mice (55 weeks old) for 7 days. Mice were housed under a 12:12 h light:dark cycle at 23-24 °C. We evaluated bio-behavioral activity using electrocardiogram, body temperature and locomotor activity recorded by an implanted telemetry transmitter. To estimate sleep-wake profile, surface electroencephalogram and electromyogram leads connected to a telemetry transmitter were also implanted in mice. Autonomic nervous activity was evaluated using power spectral analysis of heart rate variability. ManNAc-treated mice spent more time in a wakeful state and less time in slow wave sleep during the dark phase. Parasympathetic nervous activity was increased following ManNAc treatment, then the sympatho-vagal balance was shifted predominance of parasympathetic nervous system. Furthermore, improvement in sleep-wake pattern was associated with increased parasympathetic nervous activity. These results suggest that ManNAc treatment can improve bio-behavioral activity and sleep-wake quality in middle-aged mice. This may have implications for improving sleep patterns in elderly humans. Copyright © 2014 Elsevier B.V. All rights reserved.

Differentiation in the angiotensin II receptor 1 blocker class on autonomic function.

PubMed

Krum, H

2001-09-01

Autonomic function is disordered in cardiovascular disease states such as chronic heart failure (CHF) and hypertension. Interactions between the renin-angiotensin-aldosterone system (RAAS) and the sympathetic nervous system (SNS) may potentially occur at a number of sites. These include central sites (eg, rostral ventrolateral medulla), at the level of baroreflex control, and at the sympathetic prejunctional angiotensin II receptor 1 (AT(1)) receptor, which is facilitatory for norepinephrine release from the sympathetic nerve terminal. Therefore, drugs that block the RAAS may be expected to improve autonomic dysfunction in cardiovascular disease states. In order to test the hypothesis that RAAS inhibition directly reduces SNS activity, a pithed rat model of sympathetic stimulation has been established. In this model, an increase in frequency of stimulation results in a pressor response that is sympathetically mediated and highly reproducible. This pressor response is enhanced in the presence of angiotensin II and is reduced in the presence of nonselective AIIRAs that block both AT(1) and AT(2) receptor subtypes (eg, saralasin). AT(1)-selective antagonists have also been studied in this model, at pharmacologically relevant doses. In one such study, only the AT(1) blocker eprosartan reduced sympathetically stimulated increases in blood pressure, whereas comparable doses of losartan, valsartan, and irbesartan did not. The reason(s) for the differences between eprosartan and other agents of this class on sympathetic modulation are not clear, but may relate to the chemical structure of the drug (a non- biphenyl tetrazole structure that is chemically distinct from the structure of other AIIRAs), receptor binding characteristics (competitive), or unique effects on presynaptic AT(1) receptors.

Self-Organizing Map With Time-Varying Structure to Plan and Control Artificial Locomotion.

PubMed

Araujo, Aluizio F R; Santana, Orivaldo V

2015-08-01

This paper presents an algorithm, self-organizing map-state trajectory generator (SOM-STG), to plan and control legged robot locomotion. The SOM-STG is based on an SOM with a time-varying structure characterized by constructing autonomously close-state trajectories from an arbitrary number of robot postures. Each trajectory represents a cyclical movement of the limbs of an animal. The SOM-STG was designed to possess important features of a central pattern generator, such as rhythmic pattern generation, synchronization between limbs, and swapping between gaits following a single command. The acquisition of data for SOM-STG is based on learning by demonstration in which the data are obtained from different demonstrator agents. The SOM-STG can construct one or more gaits for a simulated robot with six legs, can control the robot with any of the gaits learned, and can smoothly swap gaits. In addition, SOM-STG can learn to construct a state trajectory form observing an animal in locomotion. In this paper, a dog is the demonstrator agent.

Modeling Negotiation by a Paticipatory Approach

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru; Bousquet, François

In a participatory approach by social scientists, role playing games (RPG) are effectively used to understand real thinking and behavior of stakeholders, but RPG is not sufficient to handle a dynamic process like negotiation. In this study, a participatory simulation where user-controlled avatars and autonomous agents coexist is introduced to the participatory approach for modeling negotiation. To establish a modeling methodology of negotiation, we have tackled the following two issues. First, for enabling domain experts to concentrate interaction design for participatory simulation, we have adopted the architecture in which an interaction layer controls agents and have defined three types of interaction descriptions (interaction protocol, interaction scenario and avatar control scenario) to be described. Second, for enabling domain experts and stakeholders to capitalize on participatory simulation, we have established a four-step process for acquiring negotiation model: 1) surveys and interviews to stakeholders, 2) RPG, 3) interaction design, and 4) participatory simulation. Finally, we discussed our methodology through a case study of agricultural economics in the northeast Thailand.

Autonomous Agents for Dynamic Process Planning in the Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Nik Nejad, Hossein Tehrani; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Rapid changes of market demands and pressures of competition require manufacturers to maintain highly flexible manufacturing systems to cope with a complex manufacturing environment. This paper deals with development of an agent-based architecture of dynamic systems for incremental process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A negotiation protocol is discussed, in this paper, to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans are searched and generated to cope with both the dynamic changes of the product specifications and the disturbances of the manufacturing resources. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans in the dynamic manufacturing environment.

Self-healing of low-velocity impact damage in glass fabric/epoxy composites using an epoxy-mercaptan healing agent

NASA Astrophysics Data System (ADS)

Chao Yuan, Yan; Ye, Yueping; Zhi Rong, Min; Chen, Haibin; Wu, Jingshen; Qiu Zhang, Ming; Qin, Shi Xiang; Yang, Gui Cheng

2011-01-01

Self-healing woven glass fabric-reinforced epoxy composite laminates were made by embedding epoxy- and mercaptan-loaded microcapsules. After being subjected to low-velocity impact, the laminates were able to heal the damage in an autonomic way at room temperature. The healing-induced reduction in the damaged areas was visualized using a scanning acoustic microscope. The rate of damage area reduction, which is closely related to the effect of crack rehabilitation and mechanical recovery, is a function of impact energy, content and size of the healing microcapsules. Minor damage, such as microcracks in the matrix, can be completely repaired by the healing system without manual intervention, including external pressure. Microcapsules with larger size and/or higher concentration are propitious for delivering more healing agent to cracked portions, while imposition of lateral pressure on damaged specimens forces the separated faces to approach each other. Both can improve the rate of damage area reduction in the case of severe damage.

Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

A novel methodology for self-healing at the nanoscale in CNT/epoxy composites

NASA Astrophysics Data System (ADS)

Quigley, E.; Datta, S.; Chattopadhyay, A.

2016-04-01

Self-healing materials have the potential to repair induced damage and extend the service life of aerospace or civil components as well as prevent catastrophic failure. A novel technique to provide self-healing capabilities at the nanoscale in carbon nanotube/epoxy nanocomposites is presented in this paper. Carbon nanotubes (CNTs) functionalized with the healing agent (dicyclopentadiene) were used to fabricate self-healing CNT/epoxy nanocomposite films. The structure of CNTs was considered suitable for this application since they are nanosized, hollow, and provide a more consistent size distribution than polymeric nanocapsules. Specimens with different weight fractions of the functionalized CNTs were fabricated to explore the effect of weight fraction of functionalized CNTs on the extent of healing. Optical micrographs with different fluorescent filters showed partial or complete healing of damage approximately two to three weeks after damage was induced. Results indicate that by using CNTs to encapsulate a healing agent, crack growth in self-healing CNT/epoxy nanocomposites can be retarded, leading to safer materials that can autonomously repair itself.

In vitro assembly of a prohead-like structure of the Rhodobacter capsulatus gene transfer agent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spano, Anthony J.; Chen, Frank S.; Goodman, Benjamin E.

2007-07-20

The gene transfer agent (GTA) is a phage-like particle capable of exchanging double-stranded DNA fragments between cells of the photosynthetic bacterium Rhodobacter capsulatus. Here we show that the major capsid protein of GTA, expressed in E. coli, can be assembled into prohead-like structures in the presence of calcium ions in vitro. Transmission electron microscopy (TEM) of uranyl acetate staining material and thin sections of glutaraldehyde-fixed material demonstrates that these associates have spherical structures with diameters in the range of 27-35 nm. The analysis of scanning TEM images revealed particles of mass {approx} 4.3 MDa, representing 101 {+-} 11 copies ofmore » the monomeric subunit. The establishment of this simple and rapid method to form prohead-like particles permits the GTA system to be used for genome manipulation within the photosynthetic bacterium, for specific targeted drug delivery, and for the construction of biologically based distributed autonomous sensors for environmental monitoring.« less

An industrial information integration approach to in-orbit spacecraft

NASA Astrophysics Data System (ADS)

Du, Xiaoning; Wang, Hong; Du, Yuhao; Xu, Li Da; Chaudhry, Sohail; Bi, Zhuming; Guo, Rong; Huang, Yongxuan; Li, Jisheng

2017-01-01

To operate an in-orbit spacecraft, the spacecraft status has to be monitored autonomously by collecting and analysing real-time data, and then detecting abnormities and malfunctions of system components. To develop an information system for spacecraft state detection, we investigate the feasibility of using ontology-based artificial intelligence in the system development. We propose a new modelling technique based on the semantic web, agent, scenarios and ontologies model. In modelling, the subjects of astronautics fields are classified, corresponding agents and scenarios are defined, and they are connected by the semantic web to analyse data and detect failures. We introduce the modelling methodologies and the resulted framework of the status detection information system in this paper. We discuss system components as well as their interactions in details. The system has been prototyped and tested to illustrate its feasibility and effectiveness. The proposed modelling technique is generic which can be extended and applied to the system development of other large-scale and complex information systems.

Atopic Dermatitis (Eczema): An Appraisal

PubMed Central

Hudson, Arthur L.

1962-01-01

Atopic (spontaneous) allergies and nonatopic (induced) allergies are often confused. The meaning of these terms is definite, but the occurrence of either (in a given individual) may depend upon his autonomic nervous system control. The evidence that allergens produce the cutaneous changes in atopic dermatitis is flimsy, and neurodermatitis would be a more appropriate term since the entity falls into that pattern of skin changes. Treatment carried out, from infancy sometimes to old age, consists of careful management of the patient in the physical and emotional spheres, avoidance of external irritation and the use of a multiplicity of anti-pruritic, anti-inflammatory and sedative agents. PMID:13955448

Microswimmers - From Single Particle Motion to Collective Behavior

NASA Astrophysics Data System (ADS)

Gompper, Gerhard; Bechinger, Clemens; Herminghaus, Stephan; Isele-Holder, Rolf; Kaupp, U. Benjamin; Löwen, Hartmut; Stark, Holger; Winkler, Roland G.

2016-11-01

Locomotion of autonomous microswimmers is a fascinating field at the cutting edge of science. It combines the biophysics of self-propulsion via motor proteins, artificial propulsion mechanisms, swimming strategies at low Reynolds numbers, the hydrodynamic interaction of swimmers, and the collective motion and synchronisation of large numbers of agents. The articles of this Special Issue are based on the lecture notes of an international summer school, which was organized by the DFG Priority Programme 1726 "Microswimmers - From Single Particle Motion to Collective Behaviour" in the fall of 2015. The minireviews provide a broad overview of the field, covering both elementary and advanced material, as well as selected areas from current research.

Noradrenergic modulation of neural erotic stimulus perception.

PubMed

Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

2017-09-01

We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

A neural network-based exploratory learning and motor planning system for co-robots

PubMed Central

Galbraith, Byron V.; Guenther, Frank H.; Versace, Massimiliano

2015-01-01

Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or “learning by doing,” an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object. PMID:26257640

Situated Agents and Humans in Social Interaction for Elderly Healthcare: From Coaalas to AVICENA.

PubMed

Gómez-Sebastià, Ignasi; Moreno, Jonathan; Álvarez-Napagao, Sergio; Garcia-Gasulla, Dario; Barrué, Cristian; Cortés, Ulises

2016-02-01

Assistive Technologies (AT) are an application area where several Artificial Intelligence techniques and tools have been successfully applied to support elderly or impeded people on their daily activities. However, approaches to AT tend to center in the user-tool interaction, neglecting the user's connection with its social environment (such as caretakers, relatives and health professionals) and the possibility to monitor undesired behaviour providing both adaptation to a dynamic environment and early response to potentially dangerous situations. In previous work we have presented COAALAS, an intelligent social and norm-aware device for elderly people that is able to autonomously organize, reorganize and interact with the different actors involved in elderly-care, either human actors or other devices. In this paper we put our work into context, by first examining what are the desirable properties of such a system, analysing the state-of-the-art on the relevant topics, and verifying the validity of our proposal in a larger context that we call AVICENA. AVICENA's aim is develop a semi-autonomous (collaborative) tool to promote monitored, intensive, extended and personalized therapeutic regime adherence at home based on adaptation techniques.

APDS: the autonomous pathogen detection system.

PubMed

Hindson, Benjamin J; Makarewicz, Anthony J; Setlur, Ujwal S; Henderer, Bruce D; McBride, Mary T; Dzenitis, John M

2005-04-15

We have developed and tested a fully autonomous pathogen detection system (APDS) capable of continuously monitoring the environment for airborne biological threat agents. The system was developed to provide early warning to civilians in the event of a bioterrorism incident and can be used at high profile events for short-term, intensive monitoring or in major public buildings or transportation nodes for long-term monitoring. The APDS is completely automated, offering continuous aerosol sampling, in-line sample preparation fluidics, multiplexed detection and identification immunoassays, and nucleic acid-based polymerase chain reaction (PCR) amplification and detection. Highly multiplexed antibody-based and duplex nucleic acid-based assays are combined to reduce false positives to a very low level, lower reagent costs, and significantly expand the detection capabilities of this biosensor. This article provides an overview of the current design and operation of the APDS. Certain sub-components of the ADPS are described in detail, including the aerosol collector, the automated sample preparation module that performs multiplexed immunoassays with confirmatory PCR, and the data monitoring and communications system. Data obtained from an APDS that operated continuously for 7 days in a major U.S. transportation hub is reported.

A neural network-based exploratory learning and motor planning system for co-robots.

PubMed

Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

2015-01-01

Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

Knowledge focus via software agents

NASA Astrophysics Data System (ADS)

Henager, Donald E.

2001-09-01

The essence of military Command and Control (C2) is making knowledge intensive decisions in a limited amount of time using uncertain, incorrect, or outdated information. It is essential to provide tools to decision-makers that provide: * Management of friendly forces by treating the "friendly resources as a system". * Rapid assessment of effects of military actions againt the "enemy as a system". * Assessment of how an enemy should, can, and could react to friendly military activities. Software agents in the form of mission agents, target agents, maintenance agents, and logistics agents can meet this information challenge. The role of each agent is to know all the details about its assigned mission, target, maintenance, or logistics entity. The Mission Agent would fight for mission resources based on the mission priority and analyze the effect that a proposed mission's results would have on the enemy. The Target Agent (TA) communicates with other targets to determine its role in the system of targets. A system of TAs would be able to inform a planner or analyst of the status of a system of targets, the effect of that status, adn the effect of attacks on that system. The system of TAs would also be able to analyze possible enemy reactions to attack by determining ways to minimize the effect of attack, such as rerouting traffic or using deception. The Maintenance Agent would scheudle maintenance events and notify the maintenance unit. The Logistics Agent would manage shipment and delivery of supplies to maintain appropriate levels of weapons, fuel and spare parts. The central idea underlying this case of software agents is knowledge focus. Software agents are createad automatically to focus their attention on individual real-world entities (e.g., missions, targets) and view the world from that entities perspective. The agent autonomously monitors the entity, identifies problems/opportunities, formulates solutions, and informs the decision-maker. The agent must be able to communicate to receive and disseminate information and provide the decision-maker with assistance via focused knowledge. THe agent must also be able to monitor the state of its own environment and make decisions necessary to carry out its delegated tasks. Agents bring three elements to the C2 domain that offer to improve decision-making. First, they provide higher-quality feedback and provide it more often. In doing so, the feedback loop becomes nearly continuous, reducing or eliminating delays in situation updates to decision-makers. Working with the most current information possible improves the control process, thus enabling effects based operations. Second, the agents accept delegation of actions and perform those actions following an established process. Agents' consistent actions reduce the variability of human input and stabilize the control process. Third, through the delegation of actions, agents ensure 100 percent consideration of plan details.

Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

NASA Astrophysics Data System (ADS)

Bosse, Stefan

2013-05-01

Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour, interaction (communication), and mobility features are modelled and specified on a machine-independent abstract programming level using a state-based agent behaviour language (APL). With this APL a high-level agent compiler is able to synthesize a hardware model (RTL, VHDL), a software model (C, ML), or a simulation model (XML) suitable to simulate a multi-agent system using the SeSAm simulator framework. Agent communication is provided by a simple tuple-space database implemented on node level providing fault tolerant access of global data. A novel synthesis development kit (SynDK) based on a graph-structured database approach is introduced to support the rapid development of compilers and synthesis tools, used for example for the design and implementation of the APL compiler.

Basic emotions and adaptation. A computational and evolutionary model.

PubMed

Pacella, Daniela; Ponticorvo, Michela; Gigliotta, Onofrio; Miglino, Orazio

2017-01-01

The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior to a genetically selected pattern in order to maximize the possible reward. We also prove the determinant presence of an internal time perception unit for the robots to achieve the highest performance and survivability across all conditions.

Clinical and electrophysiologic attributes as predictors of results of autonomic function tests

NASA Technical Reports Server (NTRS)

Wu, C. L.; Denq, J. C.; Harper, C. M.; O'Brien, P. C.; Low, P. A.

1998-01-01

Autonomic dysfunction is a feature of some neuropathies and not others. It has been suggested that some clinical and electrophysiologic attributes are predictable of autonomic impairment detected using laboratory testing; however, dear guidelines are unavailable. We evaluated 138 relatively unselected patients with peripheral neuropathy who underwent neurologic evaluation, electromyography (EMG), nerve conduction studies, and autonomic function tests to determine which variables were predictive of laboratory findings of autonomic failure. The variables evaluated were 1) clinical somatic neuropathic findings, 2) clinical autonomic symptoms, and 3) electrophysiologic findings. Autonomic symptoms were strongly predictive (Rs = 0.40, p < 0.001) of autonomic failure. Among the non-autonomic indices, absent ankle reflexes were mildly predictive (Rs = 0.19, p = 0.022) of autonomic impairment, but all others were not (duration, clinical pattern, severity, weakness, sensory loss). Electrophysiologic changes of an axonal neuropathy predicted autonomic impairment while demyelinating neuropathy did not. We conclude that autonomic studies will most likely be abnormal in patients who have symptoms of autonomic involvement and those who have an axonal neuropathy.

Reusable Reinforcement Learning via Shallow Trails.

PubMed

Yu, Yang; Chen, Shi-Yong; Da, Qing; Zhou, Zhi-Hua

2018-06-01

Reinforcement learning has shown great success in helping learning agents accomplish tasks autonomously from environment interactions. Meanwhile in many real-world applications, an agent needs to accomplish not only a fixed task but also a range of tasks. For this goal, an agent can learn a metapolicy over a set of training tasks that are drawn from an underlying distribution. By maximizing the total reward summed over all the training tasks, the metapolicy can then be reused in accomplishing test tasks from the same distribution. However, in practice, we face two major obstacles to train and reuse metapolicies well. First, how to identify tasks that are unrelated or even opposite with each other, in order to avoid their mutual interference in the training. Second, how to characterize task features, according to which a metapolicy can be reused. In this paper, we propose the MetA-Policy LEarning (MAPLE) approach that overcomes the two difficulties by introducing the shallow trail. It probes a task by running a roughly trained policy. Using the rewards of the shallow trail, MAPLE automatically groups similar tasks. Moreover, when the task parameters are unknown, the rewards of the shallow trail also serve as task features. Empirical studies on several controlling tasks verify that MAPLE can train metapolicies well and receives high reward on test tasks.

Modelling of internal architecture of kinesin nanomotor as a machine language.

PubMed

Khataee, H R; Ibrahim, M Y

2012-09-01

Kinesin is a protein-based natural nanomotor that transports molecular cargoes within cells by walking along microtubules. Kinesin nanomotor is considered as a bio-nanoagent which is able to sense the cell through its sensors (i.e. its heads and tail), make the decision internally and perform actions on the cell through its actuator (i.e. its motor domain). The study maps the agent-based architectural model of internal decision-making process of kinesin nanomotor to a machine language using an automata algorithm. The applied automata algorithm receives the internal agent-based architectural model of kinesin nanomotor as a deterministic finite automaton (DFA) model and generates a regular machine language. The generated regular machine language was acceptable by the architectural DFA model of the nanomotor and also in good agreement with its natural behaviour. The internal agent-based architectural model of kinesin nanomotor indicates the degree of autonomy and intelligence of the nanomotor interactions with its cell. Thus, our developed regular machine language can model the degree of autonomy and intelligence of kinesin nanomotor interactions with its cell as a language. Modelling of internal architectures of autonomous and intelligent bio-nanosystems as machine languages can lay the foundation towards the concept of bio-nanoswarms and next phases of the bio-nanorobotic systems development.

Regulation of Glucose Homeostasis by GLP-1

PubMed Central

Nadkarni, Prashant; Chepurny, Oleg G.; Holz, George G.

2014-01-01

Glucagon-like peptide-1(7–36)amide (GLP-1) is a secreted peptide that acts as a key determinant of blood glucose homeostasis by virtue of its abilities to slow gastric emptying, to enhance pancreatic insulin secretion, and to suppress pancreatic glucagon secretion. GLP-1 is secreted from L cells of the gastrointestinal mucosa in response to a meal, and the blood glucose-lowering action of GLP-1 is terminated due to its enzymatic degradation by dipeptidyl-peptidase-IV (DPP-IV). Released GLP-1 activates enteric and autonomic reflexes while also circulating as an incretin hormone to control endocrine pancreas function. The GLP-1 receptor (GLP-1R) is a G protein-coupled receptor that is activated directly or indirectly by blood glucose-lowering agents currently in use for the treatment of type 2 diabetes mellitus (T2DM). These therapeutic agents include GLP-1R agonists (exenatide, liraglutide, lixisenatide, albiglutide, dulaglutide, and langlenatide) and DPP-IV inhibitors (sitagliptin, vildagliptin, saxagliptin, linagliptin, and alogliptin). Investigational agents for use in the treatment of T2DM include GPR119 and GPR40 receptor agonists that stimulate the release of GLP-1 from L cells. Summarized here is the role of GLP-1 to control blood glucose homeo-stasis, with special emphasis on the advantages and limitations of GLP-1-based therapeutics. PMID:24373234

A new unifying hypothesis for lathyrism, konzo and tropical ataxic neuropathy: nitriles are the causative agents.

PubMed

Llorens, Jordi; Soler-Martín, Carla; Saldaña-Ruíz, Sandra; Cutillas, Blanca; Ambrosio, Santiago; Boadas-Vaello, Pere

2011-03-01

Konzo and lathyrism are associated with consumption of cassava and grass pea, respectively. Cassava consumption has also been associated with a third disease, tropical ataxic neuropathy (TAN). This review presents a new unifying hypothesis on the causative agents for these diseases: namely, that they are nitriles, compounds containing cyano groups. The diseases may be caused by different but similar nitriles through direct neurotoxic actions not mediated by systemic cyanide release. Both cassava and Lathyrus contain nitriles, and other unidentified nitriles can be generated during food processing or in the human body. Available data indicate that several small nitriles cause a variety of neurotoxic effects. In experimental animals, 3,3'-iminodipropionitrile (IDPN), allylnitrile and cis-crotononitrile cause sensory toxicity, whereas hexadienenitrile and trans-crotononitrile induce selective neuronal degeneration in discrete brain regions. IDPN also induces a neurofilamentous axonopathy, and dimethylaminopropionitrile is known to cause autonomic (genito-urinary) neurotoxicity in both humans and rodents. Some of these actions depend on metabolic bioactivation of the parental nitriles, and sex- and species-dependent differences in susceptibility have been recorded. Recently, neuronal degeneration has been found in rats exposed to acetone cyanohydrin. Taken together, the neurotoxic properties of nitriles make them excellent candidates as causative agents for konzo, lathyrism and TAN. Copyright © 2010 Elsevier Ltd. All rights reserved.

Router Agent Technology for Policy-Based Network Management

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

2011-01-01

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

Building distributed rule-based systems using the AI Bus

NASA Technical Reports Server (NTRS)

Schultz, Roger D.; Stobie, Iain C.

1990-01-01

The AI Bus software architecture was designed to support the construction of large-scale, production-quality applications in areas of high technology flux, running heterogeneous distributed environments, utilizing a mix of knowledge-based and conventional components. These goals led to its current development as a layered, object-oriented library for cooperative systems. This paper describes the concepts and design of the AI Bus and its implementation status as a library of reusable and customizable objects, structured by layers from operating system interfaces up to high-level knowledge-based agents. Each agent is a semi-autonomous process with specialized expertise, and consists of a number of knowledge sources (a knowledge base and inference engine). Inter-agent communication mechanisms are based on blackboards and Actors-style acquaintances. As a conservative first implementation, we used C++ on top of Unix, and wrapped an embedded Clips with methods for the knowledge source class. This involved designing standard protocols for communication and functions which use these protocols in rules. Embedding several CLIPS objects within a single process was an unexpected problem because of global variables, whose solution involved constructing and recompiling a C++ version of CLIPS. We are currently working on a more radical approach to incorporating CLIPS, by separating out its pattern matcher, rule and fact representations and other components as true object oriented modules.

An investigation of the evolutionary origin of reciprocal communication using simulated autonomous agents.

PubMed

Tuci, Elio

2009-09-01

How does communication originates in a population of originally non-communicating individuals? Providing an answer to this question from a neo-Darwinian epistemological perspective is not a trivial task. The reason is that, for non-communicating agents, the capabilities of emitting signals and responding to them are both adaptively neutral traits if they are not simultaneously present. Research studies based on rather general and theoretically oriented evolutionary simulation models have, so far, demonstrated that at least two different processes can account for the origin of communication. On the one hand, communicative behaviour may first evolve in a non-communicative context and only subsequently acquire its adaptive function.On the other hand, communication may originate thanks to cognitive constraints; that is, communication may originate thanks to the existence of neural substrates that are common to the signalling and categorising capabilities. This article provides a proof-of-concept demonstration of the origin of communication in a novel-simulated scenario in which groups of two homogeneous (i.e. genetically identical) agents exploit reciprocal communication to develop common perceptual categories nd to perform a collective task. In particular, in circumstances in which communication is evolutionarily advantageous, simulated agents evolve from scratch social behaviour through acoustic interactions.We look into the phylogeny of successful communication protocol, and we describe the evolutionary phenomena that, in early evolutionary stages, paved the way for the subsequent development of reciprocal communication, categorisation capabilities and successful cooperative strategies.

Review of adjunctive dexmedetomidine in the management of severe acute alcohol withdrawal syndrome.

PubMed

Wong, Adrian; Smithburger, Pamela L; Kane-Gill, Sandra L

2015-01-01

The primary management of alcohol withdrawal involves the administration of a γ-aminobutyric acid agonist, such as benzodiazepines, for management of symptoms and to prevent further progression to seizure or delirium tremens. Despite escalating doses of benzodiazepines, published literature indicates that some patient's alcohol withdrawal syndrome symptoms do not respond, and that the use of adjunctive agents may be beneficial in these patients. Dexmedetomidine, an α2-agonist, serves as a potential adjunctive agent through management of associated autonomic symptoms. Understanding of recent literature evaluating its use is necessary for appropriate selection. To review available literature supporting the use of adjunctive dexmedetomidine for management of severe alcohol withdrawal syndrome. A total of 13 published articles evaluating the efficacy and safety of dexmedetomidine as an adjunctive agent for the treatment of alcohol withdrawal in adult patients were identified from a MEDLINE search using the key words alcohol withdrawal, delirium tremens and dexmedetomidine. Evaluation of the literature indicates that dexmedetomidine is associated with a decrease in short-term benzodiazepine requirements after initiation, and improvement in hemodynamic parameters in relation to the adrenergic drive present in alcohol withdrawal. The use of dexmedetomidine in the management of severe alcohol withdrawal should be considered as an adjunctive agent. Dexmedetomidine appears to be well tolerated, with an expected decrease in blood pressure and heart rate. Seizures have occurred in patients with alcohol withdrawal despite the use of dexmedetomidine, with and without benzodiazepines, due to lack of γ-aminobutyric acid agonist administration.