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.

An Agent-Based Data Mining System for Ontology Evolution

NASA Astrophysics Data System (ADS)

Hadzic, Maja; Dillon, Darshan

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

Guidance and Navigation Software Architecture Design for the Autonomous Multi-Agent Physically Interacting Spacecraft (AMPHIS) Test Bed

DTIC Science & Technology

2006-12-01

NAVIGATION SOFTWARE ARCHITECTURE DESIGN FOR THE AUTONOMOUS MULTI-AGENT PHYSICALLY INTERACTING SPACECRAFT (AMPHIS) TEST BED by Blake D. Eikenberry...Engineer Degree 4. TITLE AND SUBTITLE Guidance and Navigation Software Architecture Design for the Autonomous Multi- Agent Physically Interacting...iii Approved for public release; distribution is unlimited GUIDANCE AND NAVIGATION SOFTWARE ARCHITECTURE DESIGN FOR THE AUTONOMOUS MULTI

Relay tracking control for second-order multi-agent systems with damaged agents.

PubMed

Dong, Lijing; Li, Jing; Liu, Qin

2017-11-01

This paper investigates a situation where smart agents capable of sensory and mobility are deployed to monitor a designated area. A preset number of agents start tracking when a target intrudes this area. Some of the tracking agents are possible to be out of order over the tracking course. Thus, we propose a cooperative relay tracking strategy to ensure the successful tracking with existence of damaged agents. Relay means that, when a tracking agent quits tracking due to malfunction, one of the near deployed agents replaces it to continue the tracking task. This results in jump of tracking errors and dynamic switching of topology of the multi-agent system. Switched system technique is employed to solve this specific problem. Finally, the effectiveness of proposed tracking strategy and validity of the theoretical results are verified by conducting a numerical simulation. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed cooperative H∞ optimal tracking control of MIMO nonlinear multi-agent systems in strict-feedback form via adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Luy, N. T.

2018-04-01

The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.

A multi-agent system for monitoring patient flow.

PubMed

Rosati, Samanta; Tralli, Augusta; Balestra, Gabriella

2013-01-01

Patient flow within a healthcare facility may follow different and, sometimes, complicated paths. Each path phase is associated with the documentation of the activities carried out during it and may require the consultation of clinical guidelines, medical literature and the use of specific software and decision aid systems. In this study we present the design of a Patient Flow Management System (PFMS) based on Multi Agent Systems (MAS) methodology. System requirements were identified by means of process modeling tools and a MAS consisting of six agents was designed and is under construction. Its main goal is to support both the medical staff during the health care process and the hospital managers in assuring that all the required documentation is completed and available. Moreover, such a tool can be used for the assessment and comparison of different clinical pathways, in order to identify possible improvementsand the optimum patient flow.

Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure.

PubMed

Yazdani, Sahar; Haeri, Mohammad

2017-11-01

In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Biomorphic Multi-Agent Architecture for Persistent Computing

NASA Technical Reports Server (NTRS)

Lodding, Kenneth N.; Brewster, Paul

2009-01-01

A multi-agent software/hardware architecture, inspired by the multicellular nature of living organisms, has been proposed as the basis of design of a robust, reliable, persistent computing system. Just as a multicellular organism can adapt to changing environmental conditions and can survive despite the failure of individual cells, a multi-agent computing system, as envisioned, could adapt to changing hardware, software, and environmental conditions. In particular, the computing system could continue to function (perhaps at a reduced but still reasonable level of performance) if one or more component( s) of the system were to fail. One of the defining characteristics of a multicellular organism is unity of purpose. In biology, the purpose is survival of the organism. The purpose of the proposed multi-agent architecture is to provide a persistent computing environment in harsh conditions in which repair is difficult or impossible. A multi-agent, organism-like computing system would be a single entity built from agents or cells. Each agent or cell would be a discrete hardware processing unit that would include a data processor with local memory, an internal clock, and a suite of communication equipment capable of both local line-of-sight communications and global broadcast communications. Some cells, denoted specialist cells, could contain such additional hardware as sensors and emitters. Each cell would be independent in the sense that there would be no global clock, no global (shared) memory, no pre-assigned cell identifiers, no pre-defined network topology, and no centralized brain or control structure. Like each cell in a living organism, each agent or cell of the computing system would contain a full description of the system encoded as genes, but in this case, the genes would be components of a software genome.

Tutoring and Multi-Agent Systems: Modeling from Experiences

ERIC Educational Resources Information Center

Bennane, Abdellah

2010-01-01

Tutoring systems become complex and are offering varieties of pedagogical software as course modules, exercises, simulators, systems online or offline, for single user or multi-user. This complexity motivates new forms and approaches to the design and the modelling. Studies and research in this field introduce emergent concepts that allow the…

Global adaptation in networks of selfish components: emergent associative memory at the system scale.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L

2011-01-01

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational principles familiar in connectionist models of organismic learning.

A Demand-Driven Approach for a Multi-Agent System in Supply Chain Management

NASA Astrophysics Data System (ADS)

Kovalchuk, Yevgeniya; Fasli, Maria

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit.

Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Tumer, Kagan

2005-01-01

Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the thousands and will reach tens or hundreds of thousands in the near future.

A practical approach for active camera coordination based on a fusion-driven multi-agent system

NASA Astrophysics Data System (ADS)

Bustamante, Alvaro Luis; Molina, José M.; Patricio, Miguel A.

2014-04-01

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.

Quadratic stabilisability of multi-agent systems under switching topologies

NASA Astrophysics Data System (ADS)

Guan, Yongqiang; Ji, Zhijian; Zhang, Lin; Wang, Long

2014-12-01

This paper addresses the stabilisability of multi-agent systems (MASs) under switching topologies. Necessary and/or sufficient conditions are presented in terms of graph topology. These conditions explicitly reveal how the intrinsic dynamics of the agents, the communication topology and the external control input affect stabilisability jointly. With the appropriate selection of some agents to which the external inputs are applied and the suitable design of neighbour-interaction rules via a switching topology, an MAS is proved to be stabilisable even if so is not for each of uncertain subsystem. In addition, a method is proposed to constructively design a switching rule for MASs with norm-bounded time-varying uncertainties. The switching rules designed via this method do not rely on uncertainties, and the switched MAS is quadratically stabilisable via decentralised external self-feedback for all uncertainties. With respect to applications of the stabilisability results, the formation control and the cooperative tracking control are addressed. Numerical simulations are presented to demonstrate the effectiveness of the proposed results.

Designing of Roaming Protocol for Bluetooth Equipped Multi Agent Systems

NASA Astrophysics Data System (ADS)

Subhan, Fazli; Hasbullah, Halabi B.

Bluetooth is an established standard for low cost, low power, wireless personal area network. Currently, Bluetooth does not support any roaming protocol in which handoff occurs dynamically when a Bluetooth device is moving out of the piconet. If a device is losing its connection to the master device, no provision is made to transfer it to another master. Handoff is not possible in a piconet, as in order to stay within the network, a slave would have to keep the same master. So, by definition intra-handoff is not possible within a piconet. This research mainly focuses on Bluetooth technology and designing a roaming protocol for Bluetooth equipped multi agent systems. A mathematical model is derived for an agent. The idea behind the mathematical model is to know when to initiate the roaming process for an agent. A desired trajectory for the agent is calculated using its x and y coordinates system, and is simulated in SIMULINK. Various roaming techniques are also studied and discussed. The advantage of designing a roaming protocol is to ensure the Bluetooth enabled roaming devices can freely move inside the network coverage without losing its connection or break of service in case of changing the base stations.

Investigating accident causation through information network modelling.

PubMed

Griffin, T G C; Young, M S; Stanton, N A

2010-02-01

Management of risk in complex domains such as aviation relies heavily on post-event investigations, requiring complex approaches to fully understand the integration of multi-causal, multi-agent and multi-linear accident sequences. The Event Analysis of Systemic Teamwork methodology (EAST; Stanton et al. 2008) offers such an approach based on network models. In this paper, we apply EAST to a well-known aviation accident case study, highlighting communication between agents as a central theme and investigating the potential for finding agents who were key to the accident. Ultimately, this work aims to develop a new model based on distributed situation awareness (DSA) to demonstrate that the risk inherent in a complex system is dependent on the information flowing within it. By identifying key agents and information elements, we can propose proactive design strategies to optimize the flow of information and help work towards avoiding aviation accidents. Statement of Relevance: This paper introduces a novel application of an holistic methodology for understanding aviation accidents. Furthermore, it introduces an ongoing project developing a nonlinear and prospective method that centralises distributed situation awareness and communication as themes. The relevance of findings are discussed in the context of current ergonomic and aviation issues of design, training and human-system interaction.

Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

Design and Simulation of Material-Integrated Distributed Sensor Processing with a Code-Based Agent Platform and Mobile Multi-Agent Systems

PubMed Central

Bosse, Stefan

2015-01-01

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques. PMID:25690550

Design and simulation of material-integrated distributed sensor processing with a code-based agent platform and mobile multi-agent systems.

PubMed

Bosse, Stefan

2015-02-16

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

A new class of finite-time nonlinear consensus protocols for multi-agent systems

NASA Astrophysics Data System (ADS)

Zuo, Zongyu; Tie, Lin

2014-02-01

This paper is devoted to investigating the finite-time consensus problem for a multi-agent system in networks with undirected topology. A new class of global continuous time-invariant consensus protocols is constructed for each single-integrator agent dynamics with the aid of Lyapunov functions. In particular, it is shown that the settling time of the proposed new class of finite-time consensus protocols is upper bounded for arbitrary initial conditions. This makes it possible for network consensus problems that the convergence time is designed and estimated offline for a given undirected information flow and a group volume of agents. Finally, a numerical simulation example is presented as a proof of concept.

Designing normative open virtual enterprises

NASA Astrophysics Data System (ADS)

Garcia, Emilia; Giret, Adriana; Botti, Vicente

2016-03-01

There is an increasing interest on developing virtual enterprises in order to deal with the globalisation of the economy, the rapid growth of information technologies and the increase of competitiveness. In this paper we deal with the development of normative open virtual enterprises (NOVEs). They are systems with a global objective that are composed of a set of heterogeneous entities and enterprises that exchange services following a specific normative context. In order to analyse and design systems of this kind the multi-agent paradigm seems suitable because it offers a specific solution for supporting the social and contractual relationships between enterprises and for formalising their business processes. This paper presents how the Regulated Open Multi-agent systems (ROMAS) methodology, an agent-oriented software methodology, can be used to analyse and design NOVEs. ROMAS offers a complete development process that allows identifying and formalising of the structure of NOVEs, their normative context and the interactions among their members. The use of ROMAS is exemplified by means of a case study that represents an automotive supply chain.

Distributed event-triggered consensus strategy for multi-agent systems under limited resources

NASA Astrophysics Data System (ADS)

Noorbakhsh, S. Mohammad; Ghaisari, Jafar

2016-01-01

The paper proposes a distributed structure to address an event-triggered consensus problem for multi-agent systems which aims at concurrent reduction in inter-agent communication, control input actuation and energy consumption. Following the proposed approach, asymptotic convergence of all agents to consensus requires that each agent broadcasts its sampled-state to the neighbours and updates its control input only at its own triggering instants, unlike the existing related works. Obviously, it decreases the network bandwidth usage, sensor energy consumption, computation resources usage and actuator wears. As a result, it facilitates the implementation of the proposed consensus protocol in the real-world applications with limited resources. The stability of the closed-loop system under an event-based protocol is proved analytically. Some numerical results are presented which confirm the analytical discussion on the effectiveness of the proposed design.

Construction of Multi-Mode Affective Learning System: Taking Affective Design as an Example

ERIC Educational Resources Information Center

Lin, Hao-Chiang Koong; Su, Sheng-Hsiung; Chao, Ching-Ju; Hsieh, Cheng-Yen; Tsai, Shang-Chin

2016-01-01

This study aims to design a non-simultaneous distance instruction system with affective computing, which integrates interactive agent technology with the curricular instruction of affective design. The research subjects were 78 students, and prototype assessment and final assessment were adopted to assess the interface and usability of the system.…

A Multi-Agent Environment for Negotiation

NASA Astrophysics Data System (ADS)

Hindriks, Koen V.; Jonker, Catholijn M.; Tykhonov, Dmytro

In this chapter we introduce the System for Analysis of Multi-Issue Negotiation (SAMIN). SAMIN offers a negotiation environment that supports and facilitates the setup of various negotiation setups. The environment has been designed to analyse negotiation processes between human negotiators, between human and software agents, and between software agents. It offers a range of different agents, different domains, and other options useful to define a negotiation setup. The environment has been used to test and evaluate a range of negotiation strategies in various domains playing against other negotiating agents as well as humans. We discuss some of the results obtained by means of these experiments.

The Study on Collaborative Manufacturing Platform Based on Agent

NASA Astrophysics Data System (ADS)

Zhang, Xiao-yan; Qu, Zheng-geng

To fulfill the trends of knowledge-intensive in collaborative manufacturing development, we have described multi agent architecture supporting knowledge-based platform of collaborative manufacturing development platform. In virtue of wrapper service and communication capacity agents provided, the proposed architecture facilitates organization and collaboration of multi-disciplinary individuals and tools. By effectively supporting the formal representation, capture, retrieval and reuse of manufacturing knowledge, the generalized knowledge repository based on ontology library enable engineers to meaningfully exchange information and pass knowledge across boundaries. Intelligent agent technology increases traditional KBE systems efficiency and interoperability and provides comprehensive design environments for engineers.

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

2000-01-01

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Group consensus control for networked multi-agent systems with communication delays.

PubMed

An, Bao-Ran; Liu, Guo-Ping; Tan, Chong

2018-05-01

This paper investigates group consensus problems in networked multi-agent systems (NMAS) with communication delays. Based on the sed state prediction scheme, the group consensus control protocol is designed to compensate the communication delay actively. In light of algebraic graph theories and matrix theories, necessary and(or) sufficient conditions of group consensus with respect to a given admissible control set are obtained for the NMAS with communication delays under mild assumptions. Finally, simulations are performed to demonstrate the effectiveness of the theoretical results. Copyright © 2018 ISA. All rights reserved.

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

FRIEND: a brain-monitoring agent for adaptive and assistive systems.

PubMed

Morris, Alexis; Ulieru, Mihaela

2012-01-01

This paper presents an architectural design for adaptive-systems agents (FRIEND) that use brain state information to make more effective decisions on behalf of a user; measuring brain context versus situational demands. These systems could be useful for alerting users to cognitive workload levels or fatigue, and could attempt to compensate for higher cognitive activity by filtering noise information. In some cases such systems could also share control of devices, such as pulling over in an automated vehicle. These aim to assist people in everyday systems to perform tasks better and be more aware of internal states. Achieving a functioning system of this sort is a challenge, involving a unification of brain- computer-interfaces, human-computer-interaction, soft-computin deliberative multi-agent systems disciplines. Until recently, these were not able to be combined into a usable platform due largely to technological limitations (e.g., size, cost, and processing speed), insufficient research on extracting behavioral states from EEG signals, and lack of low-cost wireless sensing headsets. We aim to surpass these limitations and develop control architectures for making sense of brain state in applications by realizing an agent architecture for adaptive (human-aware) technology. In this paper we present an early, high-level design towards implementing a multi-purpose brain-monitoring agent system to improve user quality of life through the assistive applications of psycho-physiological monitoring, noise-filtering, and shared system control.

A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

NASA Astrophysics Data System (ADS)

Tapia, Dante I.; RodríGuez, Sara; Corchado, Juan M.

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems.

Design for interaction between humans and intelligent systems during real-time fault management

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Thronesbery, Carroll G.

1992-01-01

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Observer-based output consensus of a class of heterogeneous multi-agent systems with unmatched disturbances

NASA Astrophysics Data System (ADS)

Zhang, Jiancheng; Zhu, Fanglai

2018-03-01

In this paper, the output consensus of a class of linear heterogeneous multi-agent systems with unmatched disturbances is considered. Firstly, based on the relative output information among neighboring agents, we propose an asymptotic sliding-mode based consensus control scheme, under which, the output consensus error can converge to zero by removing the disturbances from output channels. Secondly, in order to reach the consensus goal, we design a novel high-order unknown input observer for each agent. It can estimate not only each agent's states and disturbances, but also the disturbances' high-order derivatives, which are required in the control scheme aforementioned above. The observer-based consensus control laws and the convergence analysis of the consensus error dynamics are given. Finally, a simulation example is provided to verify the validity of our methods.

Combining a Multi-Agent System and Communication Middleware for Smart Home Control: A Universal Control Platform Architecture

PubMed Central

Zheng, Song; Zhang, Qi; Zheng, Rong; Huang, Bi-Qin; Song, Yi-Lin; Chen, Xin-Chu

2017-01-01

In recent years, the smart home field has gained wide attention for its broad application prospects. However, families using smart home systems must usually adopt various heterogeneous smart devices, including sensors and devices, which makes it more difficult to manage and control their home system. How to design a unified control platform to deal with the collaborative control problem of heterogeneous smart devices is one of the greatest challenges in the current smart home field. The main contribution of this paper is to propose a universal smart home control platform architecture (IAPhome) based on a multi-agent system and communication middleware, which shows significant adaptability and advantages in many aspects, including heterogeneous devices connectivity, collaborative control, human-computer interaction and user self-management. The communication middleware is an important foundation to design and implement this architecture which makes it possible to integrate heterogeneous smart devices in a flexible way. A concrete method of applying the multi-agent software technique to solve the integrated control problem of the smart home system is also presented. The proposed platform architecture has been tested in a real smart home environment, and the results indicate that the effectiveness of our approach for solving the collaborative control problem of different smart devices. PMID:28926957

Combining a Multi-Agent System and Communication Middleware for Smart Home Control: A Universal Control Platform Architecture.

PubMed

Zheng, Song; Zhang, Qi; Zheng, Rong; Huang, Bi-Qin; Song, Yi-Lin; Chen, Xin-Chu

2017-09-16

In recent years, the smart home field has gained wide attention for its broad application prospects. However, families using smart home systems must usually adopt various heterogeneous smart devices, including sensors and devices, which makes it more difficult to manage and control their home system. How to design a unified control platform to deal with the collaborative control problem of heterogeneous smart devices is one of the greatest challenges in the current smart home field. The main contribution of this paper is to propose a universal smart home control platform architecture (IAPhome) based on a multi-agent system and communication middleware, which shows significant adaptability and advantages in many aspects, including heterogeneous devices connectivity, collaborative control, human-computer interaction and user self-management. The communication middleware is an important foundation to design and implement this architecture which makes it possible to integrate heterogeneous smart devices in a flexible way. A concrete method of applying the multi-agent software technique to solve the integrated control problem of the smart home system is also presented. The proposed platform architecture has been tested in a real smart home environment, and the results indicate that the effectiveness of our approach for solving the collaborative control problem of different smart devices.

The California Central Coast Research Partnership: Building Relationships, Partnerships and Paradigms for University-Industry Research Collaboration

DTIC Science & Technology

2005-10-14

of the decision-support systems that underlie and are key to these strategies. Cal Poly’s Collaborative Agent Design (CAD) Research Center is the...architect and lead developer of one of the first such systems: IMMACCS (Integrated Marine Multi- Agent Command and Control System), with JPL, SPAWAR...presented later in this document. An overview of accomplishments to date on the project follows: " Research carried out by the CADRC (Cooperative Agent

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.

Modelling of Robotized Manufacturing Systems Using MultiAgent Formalism

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The evolution of manufacturing systems has greatly accelerated due to development of sophisticated control systems. On top of determined, one way production flow the need of decision making has arisen as a result of growing product range that are manufactured simultaneously, using the same resources. On the other hand, the intelligent flow control could address the “bottleneck” problem caused by the machine failure. This sort of manufacturing systems uses advanced control algorithms that are introduced by the use of logic controllers. The complex algorithms used in the control systems requires to employ appropriate methods during the modelling process, like the agent-based one, which is the subject of this paper. The concept of an agent is derived from the object-based methodology of modelling, so it meets the requirements of representing the physical properties of the machines as well as the logical form of control systems. Each agent has a high level of autonomy and could be considered separately. The multi-agent system consists of minimum two agents that can interact and modify the environment, where they act. This may lead to the creation of self-organizing structure, what could be interesting feature during design and test of manufacturing system.

Unifying Temporal and Structural Credit Assignment Problems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2004-01-01

Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions. Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these two forms of the credit assignment problem are equivalent. In this unified frame-work, a single-agent Markov decision process can be broken down into a single-time-step multi-agent process. Furthermore we show that Monte-Carlo estimation or Q-learning (depending on whether the values of resulting actions in the episode are known at the time of learning) are equivalent to different agent utility functions in a multi-agent system. This equivalence shows how an often neglected issue in multi-agent systems is equivalent to a well-known deficiency in multi-time-step learning and lays the basis for solving time-extended multi-agent problems, where both credit assignment problems are present.

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

NASA Astrophysics Data System (ADS)

Cui, Bing; Zhao, Chunhui; Ma, Tiedong; Feng, Chi

2017-02-01

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.

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'.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

Model of interaction in Smart Grid on the basis of multi-agent system

NASA Astrophysics Data System (ADS)

Engel, E. A.; Kovalev, I. V.; Engel, N. E.

2016-11-01

This paper presents model of interaction in Smart Grid on the basis of multi-agent system. The use of travelling waves in the multi-agent system describes the behavior of the Smart Grid from the local point, which is being the complement of the conventional approach. The simulation results show that the absorption of the wave in the distributed multi-agent systems is effectively simulated the interaction in Smart Grid.

Facilitating the Specification Capture and Transformation Process in the Development of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Filho, Aluzio Haendehen; Caminada, Numo; Haeusler, Edward Hermann; vonStaa, Arndt

2004-01-01

To support the development of flexible and reusable MAS, we have built a framework designated MAS-CF. MAS-CF is a component framework that implements a layered architecture based on contextual composition. Interaction rules, controlled by architecture mechanisms, ensure very low coupling, making possible the sharing of distributed services in a transparent, dynamic and independent way. These properties propitiate large-scale reuse, since organizational abstractions can be reused and propagated to all instances created from a framework. The objective is to reduce complexity and development time of multi-agent systems through the reuse of generic organizational abstractions.

Distributed consensus for discrete-time heterogeneous multi-agent systems

NASA Astrophysics Data System (ADS)

Zhao, Huanyu; Fei, Shumin

2018-06-01

This paper studies the consensus problem for a class of discrete-time heterogeneous multi-agent systems. Two kinds of consensus algorithms will be considered. The heterogeneous multi-agent systems considered are converted into equivalent error systems by a model transformation. Then we analyse the consensus problem of the original systems by analysing the stability problem of the error systems. Some sufficient conditions for consensus of heterogeneous multi-agent systems are obtained by applying algebraic graph theory and matrix theory. Simulation examples are presented to show the usefulness of the results.

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

PubMed

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.

Robust consensus algorithm for multi-agent systems with exogenous disturbances under convergence conditions

NASA Astrophysics Data System (ADS)

Jiang, Yulian; Liu, Jianchang; Tan, Shubin; Ming, Pingsong

2014-09-01

In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.

A Mobile Multi-Agent Information System for Ubiquitous Fetal Monitoring

PubMed Central

Su, Chuan-Jun; Chu, Ta-Wei

2014-01-01

Electronic fetal monitoring (EFM) systems integrate many previously separate clinical activities related to fetal monitoring. Promoting the use of ubiquitous fetal monitoring services with real time status assessments requires a robust information platform equipped with an automatic diagnosis engine. This paper presents the design and development of a mobile multi-agent platform-based open information systems (IMAIS) with an automated diagnosis engine to support intensive and distributed ubiquitous fetal monitoring. The automatic diagnosis engine that we developed is capable of analyzing data in both traditional paper-based and digital formats. Issues related to interoperability, scalability, and openness in heterogeneous e-health environments are addressed through the adoption of a FIPA2000 standard compliant agent development platform—the Java Agent Development Environment (JADE). Integrating the IMAIS with light-weight, portable fetal monitor devices allows for continuous long-term monitoring without interfering with a patient’s everyday activities and without restricting her mobility. The system architecture can be also applied to vast monitoring scenarios such as elder care and vital sign monitoring. PMID:24452256

Chronic Heart Failure Follow-up Management Based on Agent Technology.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Human computer interactions in next-generation of aircraft smart navigation management systems: task analysis and architecture under an agent-oriented methodological approach.

PubMed

Canino-Rodríguez, José M; García-Herrero, Jesús; Besada-Portas, Juan; Ravelo-García, Antonio G; Travieso-González, Carlos; Alonso-Hernández, Jesús B

2015-03-04

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.

Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

PubMed Central

Canino-Rodríguez, José M.; García-Herrero, Jesús; Besada-Portas, Juan; Ravelo-García, Antonio G.; Travieso-González, Carlos; Alonso-Hernández, Jesús B.

2015-01-01

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers’ indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications. PMID:25746092

Nondestructive Intervention to Multi-Agent Systems through an Intelligent Agent

PubMed Central

Han, Jing; Wang, Lin

2013-01-01

For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents). However, we add one intelligent agent, called ‘shill’, which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior. PMID:23658695

Multi-Level Cultural Models

DTIC Science & Technology

2014-11-05

usable simulations. This procedure was to be tested using real-world data collected from open-source venues. The final system would support rapid...assess social change. Construct is an agent-based dynamic-network simulation system design to allow the user to assess the spread of information and...protest or violence. Technical Challenges Addressed  Re‐use:    Most agent-based simulation ( ABM ) in use today are one-off. In contrast, we

Multi-Agent Modeling and Simulation Approach for Design and Analysis of MER Mission Operations

NASA Technical Reports Server (NTRS)

Seah, Chin; Sierhuis, Maarten; Clancey, William J.

2005-01-01

A space mission operations system is a complex network of human organizations, information and deep-space network systems and spacecraft hardware. As in other organizations, one of the problems in mission operations is managing the relationship of the mission information systems related to how people actually work (practices). Brahms, a multi-agent modeling and simulation tool, was used to model and simulate NASA's Mars Exploration Rover (MER) mission work practice. The objective was to investigate the value of work practice modeling for mission operations design. From spring 2002 until winter 2003, a Brahms modeler participated in mission systems design sessions and operations testing for the MER mission held at Jet Propulsion Laboratory (JPL). He observed how designers interacted with the Brahms tool. This paper discussed mission system designers' reactions to the simulation output during model validation and the presentation of generated work procedures. This project spurred JPL's interest in the Brahms model, but it was never included as part of the formal mission design process. We discuss why this occurred. Subsequently, we used the MER model to develop a future mission operations concept. Team members were reluctant to use the MER model, even though it appeared to be highly relevant to their effort. We describe some of the tool issues we encountered.

Massive Multi-Agent Systems Control

NASA Technical Reports Server (NTRS)

Campagne, Jean-Charles; Gardon, Alain; Collomb, Etienne; Nishida, Toyoaki

2004-01-01

In order to build massive multi-agent systems, considered as complex and dynamic systems, one needs a method to analyze and control the system. We suggest an approach using morphology to represent and control the state of large organizations composed of a great number of light software agents. Morphology is understood as representing the state of the multi-agent system as shapes in an abstract geometrical space, this notion is close to the notion of phase space in physics.

Verifying Multi-Agent Systems via Unbounded Model Checking

NASA Technical Reports Server (NTRS)

Kacprzak, M.; Lomuscio, A.; Lasica, T.; Penczek, W.; Szreter, M.

2004-01-01

We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

A Multi-Agent System for Intelligent Online Education.

ERIC Educational Resources Information Center

O'Riordan, Colm; Griffith, Josephine

1999-01-01

Describes the system architecture of an intelligent Web-based education system that includes user modeling agents, information filtering agents for automatic information gathering, and the multi-agent interaction. Discusses information management; user interaction; support for collaborative peer-peer learning; implementation; testing; and future…

Conflict resolution in multi-agent hybrid systems

DOT National Transportation Integrated Search

1996-12-01

A conflict resolution architecture for multi-agent hybrid systems with emphasis on Air Traffic Management Systems (ATMS) is presented. In such systems, conflicts arise in the form of potential collisions which are resolved locally by inter-agent coor...

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.

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.

Computational Model for Ethnographically Informed Systems Design

NASA Astrophysics Data System (ADS)

Iqbal, Rahat; James, Anne; Shah, Nazaraf; Terken, Jacuqes

This paper presents a computational model for ethnographically informed systems design that can support complex and distributed cooperative activities. This model is based on an ethnographic framework consisting of three important dimensions (e.g., distributed coordination, awareness of work and plans and procedure), and the BDI (Belief, Desire and Intention) model of intelligent agents. The ethnographic framework is used to conduct ethnographic analysis and to organise ethnographically driven information into three dimensions, whereas the BDI model allows such information to be mapped upon the underlying concepts of multi-agent systems. The advantage of this model is that it is built upon an adaptation of existing mature and well-understood techniques. By the use of this model, we also address the cognitive aspects of systems design.

Research and Implementation of Key Technologies in Multi-Agent System to Support Distributed Workflow

NASA Astrophysics Data System (ADS)

Pan, Tianheng

2018-01-01

In recent years, the combination of workflow management system and Multi-agent technology is a hot research field. The problem of lack of flexibility in workflow management system can be improved by introducing multi-agent collaborative management. The workflow management system adopts distributed structure. It solves the problem that the traditional centralized workflow structure is fragile. In this paper, the agent of Distributed workflow management system is divided according to its function. The execution process of each type of agent is analyzed. The key technologies such as process execution and resource management are analyzed.

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

Economic reasoning and artificial intelligence.

PubMed

Parkes, David C; Wellman, Michael P

2015-07-17

The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

Study on the E-commerce platform based on the agent

NASA Astrophysics Data System (ADS)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

NASA Astrophysics Data System (ADS)

Fard, Amin Milani

Knowledge extraction from distributed database systems, have been investigated during past decade in order to analyze billions of information records. In this work a competitive deduction approach in a heterogeneous data grid environment is proposed using classic data mining and statistical methods. By applying a game theory concept in a multi-agent model, we tried to design a policy for hierarchical knowledge discovery and inference fusion. To show the system run, a sample multi-expert system has also been developed.

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

Content modification attacks on consensus seeking multi-agent system with double-integrator dynamics.

PubMed

Dong, Yimeng; Gupta, Nirupam; Chopra, Nikhil

2016-11-01

In this paper, vulnerability of a distributed consensus seeking multi-agent system (MAS) with double-integrator dynamics against edge-bound content modification cyber attacks is studied. In particular, we define a specific edge-bound content modification cyber attack called malignant content modification attack (MCoMA), which results in unbounded growth of an appropriately defined group disagreement vector. Properties of MCoMA are utilized to design detection and mitigation algorithms so as to impart resilience in the considered MAS against MCoMA. Additionally, the proposed detection mechanism is extended to detect the general edge-bound content modification attacks (not just MCoMA). Finally, the efficacies of the proposed results are illustrated through numerical simulations.

Content modification attacks on consensus seeking multi-agent system with double-integrator dynamics

NASA Astrophysics Data System (ADS)

Dong, Yimeng; Gupta, Nirupam; Chopra, Nikhil

2016-11-01

In this paper, vulnerability of a distributed consensus seeking multi-agent system (MAS) with double-integrator dynamics against edge-bound content modification cyber attacks is studied. In particular, we define a specific edge-bound content modification cyber attack called malignant content modification attack (MCoMA), which results in unbounded growth of an appropriately defined group disagreement vector. Properties of MCoMA are utilized to design detection and mitigation algorithms so as to impart resilience in the considered MAS against MCoMA. Additionally, the proposed detection mechanism is extended to detect the general edge-bound content modification attacks (not just MCoMA). Finally, the efficacies of the proposed results are illustrated through numerical simulations.

Multi-agent simulation of generation expansion in electricity markets.

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

Botterud, A; Mahalik, M. R.; Veselka, T. D.

2007-06-01

We present a new multi-agent model of generation expansion in electricity markets. The model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitors actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We test the model using real data for the Korea power system under different assumptions about market design, market concentration, and GenCo'smore » assumed expectations about their competitors investment decisions.« less

An agent based architecture for high-risk neonate management at neonatal intensive care unit.

PubMed

Malak, Jaleh Shoshtarian; Safdari, Reza; Zeraati, Hojjat; Nayeri, Fatemeh Sadat; Mohammadzadeh, Niloofar; Farajollah, Seide Sedighe Seied

2018-01-01

In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management. This study was a basic research for medical informatics method development that was carried out in 2017. The requirement analysis was done by reviewing articles on NICU Decision Support Systems. PubMed, Science Direct, and IEEE databases were searched. Only English articles published after 1990 were included; also, a needs assessment was done by reviewing the extracted features and current processes at the NICU environment where the research was conducted. We analyzed the requirements and identified the main system roles (agents) and interactions by a comparative study of existing NICU decision support systems. The Universal Multi Agent Platform (UMAP) was applied to implement a prototype of our multi agent based high-risk neonate management architecture. Local environment agents interacted inside a container and each container interacted with external resources, including other NICU systems and consultation centers. In the NICU container, the main identified agents were reception, monitoring, NICU registry, and outcome prediction, which interacted with human agents including nurses and physicians. Managing patients at the NICU units requires online data collection, real-time collaboration, and management of many components. Multi agent systems are applied as a well-known solution for management, coordination, modeling, and control of NICU processes. We are currently working on an outcome prediction module using artificial intelligence techniques for neonatal mortality risk prediction. The full implementation of the proposed architecture and evaluation is considered the future work.

Multi-Wavelength Photomagnetic Imaging for Oral Cancer

NASA Astrophysics Data System (ADS)

Marks, Michael

In this study, a multi-wavelength Photomagnetic Imaging (PMI) system is developed and evaluated with experimental studies.. PMI measures temperature increases in samples illuminated by near-infrared light sources using magnetic resonance thermometry. A multiphysics solver combining light and heat transfer models the spatiotemporal distribution of the temperature change. The PMI system develop in this work uses three lasers of varying wavelength (785 nm, 808 nm, 860 nm) to heat the sample. By using multiple wavelengths, we enable the PMI system to quantify the relative concentrations of optical contrast in turbid media and monitor their distribution, at a higher resolution than conventional diffuse optical imaging. The data collected from agarose phantoms with multiple embedded contrast agents designed to simulate the optical properties of oxy- and deoxy-hemoglobin is presented. The reconstructed images demonstrate that multi-wavelength PMI can resolve this complex inclusion structure with high resolution and recover the concentration of each contrast agent with high quantitative accuracy. The modified multi-wavelength PMI system operates under the maximum skin exposure limits defined by the American National Standards Institute, to enable future clinical applications.

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A cognitive information processing framework for distributed sensor networks

NASA Astrophysics Data System (ADS)

Wang, Feiyi; Qi, Hairong

2004-09-01

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

Agents Control in Intelligent Learning Systems: The Case of Reactive Characteristics

ERIC Educational Resources Information Center

Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; de Arriaga, Fernando; Escarela-Perez, Rafael

2006-01-01

Intelligent learning systems (ILSs) have evolved in the last few years basically because of influences received from multi-agent architectures (MAs). Conflict resolution among agents has been a very important problem for multi-agent systems, with specific features in the case of ILSs. The literature shows that ILSs with cognitive or pedagogical…

Controllability of multi-agent systems with time-delay in state and switching topology

NASA Astrophysics Data System (ADS)

Ji, Zhijian; Wang, Zidong; Lin, Hai; Wang, Zhen

2010-02-01

In this article, the controllability issue is addressed for an interconnected system of multiple agents. The network associated with the system is of the leader-follower structure with some agents taking leader role and others being followers interconnected via the neighbour-based rule. Sufficient conditions are derived for the controllability of multi-agent systems with time-delay in state, as well as a graph-based uncontrollability topology structure is revealed. Both single and double integrator dynamics are considered. For switching topology, two algebraic necessary and sufficient conditions are derived for the controllability of multi-agent systems. Several examples are also presented to illustrate how to control the system to shape into the desired configurations.

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Multi-Agent Framework for Virtual Learning Spaces.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

QUICR-learning for Multi-Agent Coordination

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2006-01-01

Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit must be assigned for an action taken at time step t that results in a reward at time step t > t. Second, credit must be assigned for the contribution of agent i to the overall system performance. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning. The second credit assignment problem is typically addressed by creating custom reward functions. To address both credit assignment problems simultaneously, we propose the "Q Updates with Immediate Counterfactual Rewards-learning" (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. QUICR-learning is based on previous work on single-time-step counterfactual rewards described by the collectives framework. Results on a traffic congestion problem shows that QUICR-learning is significantly better than a Q-learner using collectives-based (single-time-step counterfactual) rewards. In addition QUICR-learning provides significant gains over conventional and local Q-learning. Additional results on a multi-agent grid-world problem show that the improvements due to QUICR-learning are not domain specific and can provide up to a ten fold increase in performance over existing methods.

Research of negotiation in network trade system based on multi-agent

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Guozheng; Wu, Haiyan

2009-07-01

A construction and implementation technology of network trade based on multi-agent is described in this paper. First, we researched the technology of multi-agent, then we discussed the consumer's behaviors and the negotiation between purchaser and bargainer which emerges in the traditional business mode and analysed the key technology to implement the network trade system. Finally, we implement the system.

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

Output Containment Control of Linear Heterogeneous Multi-Agent Systems Using Internal Model Principle.

PubMed

Zuo, Shan; Song, Yongduan; Lewis, Frank L; Davoudi, Ali

2017-01-04

This paper studies the output containment control of linear heterogeneous multi-agent systems, where the system dynamics and even the state dimensions can generally be different. Since the states can have different dimensions, standard results from state containment control do not apply. Therefore, the control objective is to guarantee the convergence of the output of each follower to the dynamic convex hull spanned by the outputs of leaders. This can be achieved by making certain output containment errors go to zero asymptotically. Based on this formulation, two different control protocols, namely, full-state feedback and static output-feedback, are designed based on internal model principles. Sufficient local conditions for the existence of the proposed control protocols are developed in terms of stabilizing the local followers' dynamics and satisfying a certain H∞ criterion. Unified design procedures to solve the proposed two control protocols are presented by formulation and solution of certain local state-feedback and static output-feedback problems, respectively. Numerical simulations are given to validate the proposed control protocols.

[Research of preparation craft of Danshen phenolic acid fast release unit in multi-drug delivery system of Tongmai micro-pellets].

PubMed

Chen, Bin; Xiao, Wei; Jia, Xiao-Bin; Huang, Yang

2012-07-01

To prepare Danshen phenolic acid fast release micro-pellets and study its preparation craft. The factors which could impact yield, extrude shaping, dissolution of Danshen phenolic acid micro-pellets such as wetting agent, drug loading dose, adjuvant, lactose dose, disintegrant, CMS-Na dose and wetting agent dose was investigated. The optimum preparation craft of Danshen phenolic acid fast release micro-pellets was screened out by orhogonal design. Formula of Danshen phenolic acid fast release micro-pellets was calculated as volume dose 50 g. The formula was as follows: principal agent 22.5 g, lactose 5 g, CMS-Na 2 g, MCC 20.5 g, 27 mL 30% ethanol as wetting agent. Extrusion-spheronization was applied. The optimum conditions were screened out as follows: extrusion frequency (25 Hz), spheronization machine frequency (50 Hz), spheronization time (4 min). The process was scientific and rational. The preparation is stable settles basis for multi-drug delivery system of Tongmai micro-pellets.

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.

Self Organized Multi Agent Swarms (SOMAS) for Network Security Control

DTIC Science & Technology

2009-03-01

Normal hierarchy vs entangled hierarchy 2.5.7 Quantifying Entangledness . While self organization means that the swarm develops a consistent structure of...flexibility due to centralization of control and com- munication. Thus, self organized, entangled hierarchy multi-agent swarms are evolved in this study to...technique. The resulting design exhibits a self organized multi-agent swarm (SOMAS) with entangled hierarchical control and communication through the

Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph

NASA Astrophysics Data System (ADS)

Yan, Jing; Guan, Xin-Ping; Luo, Xiao-Yuan

2011-04-01

This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents, and agents will pursue the target once they detect its existence. Since the ability of each agent may be different, we consider the heterogeneous multi-agent systems. According to the topology of the multi-agent systems, a novel consensus-based control law is proposed, where the target and agents are modeled as a leader and followers, respectively. Based on Mason's rule and signal flow graph analysis, the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally, simulation studies are provided to verify the effectiveness of the proposed approach.

Directional Bias and Pheromone for Discovery and Coverage on Networks

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

Fink, Glenn A.; Berenhaut, Kenneth S.; Oehmen, Christopher S.

2012-09-11

Natural multi-agent systems often rely on “correlated random walks” (random walks that are biased toward a current heading) to distribute their agents over a space (e.g., for foraging, search, etc.). Our contribution involves creation of a new movement and pheromone model that applies the concept of heading bias in random walks to a multi-agent, digital-ants system designed for cyber-security monitoring. We examine the relative performance effects of both pheromone and heading bias on speed of discovery of a target and search-area coverage in a two-dimensional network layout. We found that heading bias was unexpectedly helpful in reducing search time andmore » that it was more influential than pheromone for improving coverage. We conclude that while pheromone is very important for rapid discovery, heading bias can also greatly improve both performance metrics.« less

A Quantum Approach to Multi-Agent Systems (MAS), Organizations, and Control

DTIC Science & Technology

2003-06-01

interdependent interactions between individuals represented approximately as vocal harmonic I resonators. Then the growth rate of an organization fits ...A quantum approach to multi-agent systems (MAS), organizations , and control W.F. Lawless Paine College 1235 15th Street Augusta, GA 30901...AND SUBTITLE A quantum approach to multi-agent systems (MAS), organizations , and control 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

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.

Modelling the B2C Marketplace: Evaluation of a Reputation Metric for e-Commerce

NASA Astrophysics Data System (ADS)

Gutowska, Anna; Sloane, Andrew

This paper evaluates recently developed novel and comprehensive reputation metric designed for the distributed multi-agent reputation system for the Business-to-Consumer (B2C) E-commerce applications. To do that an agent-based simulation framework was implemented which models different types of behaviours in the marketplace. The trustworthiness of different types of providers is investigated to establish whether the simulation models behaviour of B2C e-Commerce systems as they are expected to behave in real life.

Metareasoning and Social Evaluations in Cognitive Agents

NASA Astrophysics Data System (ADS)

Pinyol, Isaac; Sabater-Mir, Jordi

Reputation mechanisms have been recognized one of the key technologies when designing multi-agent systems. They are specially relevant in complex open environments, becoming a non-centralized mechanism to control interactions among agents. Cognitive agents tackling such complex societies must use reputation information not only for selecting partners to interact with, but also in metareasoning processes to change reasoning rules. This is the focus of this paper. We argue about the necessity to allow, as a cognitive systems designers, certain degree of freedom in the reasoning rules of the agents. We also describes cognitive approaches of agency that support this idea. Furthermore, taking as a base the computational reputation model Repage, and its integration in a BDI architecture, we use the previous ideas to specify metarules and processes to modify at run-time the reasoning paths of the agent. In concrete we propose a metarule to update the link between Repage and the belief base, and a metarule and a process to update an axiom incorporated in the belief logic of the agent. Regarding this last issue we also provide empirical results that show the evolution of agents that use it.

IMAGE: A Design Integration Framework Applied to the High Speed Civil Transport

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1993-01-01

Effective design of the High Speed Civil Transport requires the systematic application of design resources throughout a product's life-cycle. Information obtained from the use of these resources is used for the decision-making processes of Concurrent Engineering. Integrated computing environments facilitate the acquisition, organization, and use of required information. State-of-the-art computing technologies provide the basis for the Intelligent Multi-disciplinary Aircraft Generation Environment (IMAGE) described in this paper. IMAGE builds upon existing agent technologies by adding a new component called a model. With the addition of a model, the agent can provide accountable resource utilization in the presence of increasing design fidelity. The development of a zeroth-order agent is used to illustrate agent fundamentals. Using a CATIA(TM)-based agent from previous work, a High Speed Civil Transport visualization system linking CATIA, FLOPS, and ASTROS will be shown. These examples illustrate the important role of the agent technologies used to implement IMAGE, and together they demonstrate that IMAGE can provide an integrated computing environment for the design of the High Speed Civil Transport.

Multi-Agent Information Classification Using Dynamic Acquaintance Lists.

ERIC Educational Resources Information Center

Mukhopadhyay, Snehasis; Peng, Shengquan; Raje, Rajeev; Palakal, Mathew; Mostafa, Javed

2003-01-01

Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

Peptide-based protein capture agents with high affinity, selectivity, and stability as antibody replacements in biodetection assays

NASA Astrophysics Data System (ADS)

Coppock, Matthew B.; Farrow, Blake; Warner, Candice; Finch, Amethist S.; Lai, Bert; Sarkes, Deborah A.; Heath, James R.; Stratis-Cullum, Dimitra

2014-05-01

Current biodetection assays that employ monoclonal antibodies as primary capture agents exhibit limited fieldability, shelf life, and performance due to batch-to-batch production variability and restricted thermal stability. In order to improve upon the detection of biological threats in fieldable assays and systems for the Army, we are investigating protein catalyzed capture (PCC) agents as drop-in replacements for the existing antibody technology through iterative in situ click chemistry. The PCC agent oligopeptides are developed against known protein epitopes and can be mass produced using robotic methods. In this work, a PCC agent under development will be discussed. The performance, including affinity, selectivity, and stability of the capture agent technology, is analyzed by immunoprecipitation, western blotting, and ELISA experiments. The oligopeptide demonstrates superb selectivity coupled with high affinity through multi-ligand design, and improved thermal, chemical, and biochemical stability due to non-natural amino acid PCC agent design.

System design in an evolving system-of-systems architecture and concept of operations

NASA Astrophysics Data System (ADS)

Rovekamp, Roger N., Jr.

Proposals for space exploration architectures have increased in complexity and scope. Constituent systems (e.g., rovers, habitats, in-situ resource utilization facilities, transfer vehicles, etc) must meet the needs of these architectures by performing in multiple operational environments and across multiple phases of the architecture's evolution. This thesis proposes an approach for using system-of-systems engineering principles in conjunction with system design methods (e.g., Multi-objective optimization, genetic algorithms, etc) to create system design options that perform effectively at both the system and system-of-systems levels, across multiple concepts of operations, and over multiple architectural phases. The framework is presented by way of an application problem that investigates the design of power systems within a power sharing architecture for use in a human Lunar Surface Exploration Campaign. A computer model has been developed that uses candidate power grid distribution solutions for a notional lunar base. The agent-based model utilizes virtual control agents to manage the interactions of various exploration and infrastructure agents. The philosophy behind the model is based both on lunar power supply strategies proposed in literature, as well as on the author's own approaches for power distribution strategies of future lunar bases. In addition to proposing a framework for system design, further implications of system-of-systems engineering principles are briefly explored, specifically as they relate to producing more robust cross-cultural system-of-systems architecture solutions.

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.

Magnetic Nanoparticles for Multi-Imaging and Drug Delivery

PubMed Central

Lee, Jae-Hyun; Kim, Ji-wook; Cheon, Jinwoo

2013-01-01

Various bio-medical applications of magnetic nanoparticles have been explored during the past few decades. As tools that hold great potential for advancing biological sciences, magnetic nanoparticles have been used as platform materials for enhanced magnetic resonance imaging (MRI) agents, biological separation and magnetic drug delivery systems, and magnetic hyperthermia treatment. Furthermore, approaches that integrate various imaging and bioactive moieties have been used in the design of multi-modality systems, which possess synergistically enhanced properties such as better imaging resolution and sensitivity, molecular recognition capabilities, stimulus responsive drug delivery with on-demand control, and spatio-temporally controlled cell signal activation. Below, recent studies that focus on the design and synthesis of multi-mode magnetic nanoparticles will be briefly reviewed and their potential applications in the imaging and therapy areas will be also discussed. PMID:23579479

Designing multi-targeted agents: An emerging anticancer drug discovery paradigm.

PubMed

Fu, Rong-Geng; Sun, Yuan; Sheng, Wen-Bing; Liao, Duan-Fang

2017-08-18

The dominant paradigm in drug discovery is to design ligands with maximum selectivity to act on individual drug targets. With the target-based approach, many new chemical entities have been discovered, developed, and further approved as drugs. However, there are a large number of complex diseases such as cancer that cannot be effectively treated or cured only with one medicine to modulate the biological function of a single target. As simultaneous intervention of two (or multiple) cancer progression relevant targets has shown improved therapeutic efficacy, the innovation of multi-targeted drugs has become a promising and prevailing research topic and numerous multi-targeted anticancer agents are currently at various developmental stages. However, most multi-pharmacophore scaffolds are usually discovered by serendipity or screening, while rational design by combining existing pharmacophore scaffolds remains an enormous challenge. In this review, four types of multi-pharmacophore modes are discussed, and the examples from literature will be used to introduce attractive lead compounds with the capability of simultaneously interfering with different enzyme or signaling pathway of cancer progression, which will reveal the trends and insights to help the design of the next generation multi-targeted anticancer agents. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Coordination of fractional-order nonlinear multi-agent systems via distributed impulsive control

NASA Astrophysics Data System (ADS)

Ma, Tiedong; Li, Teng; Cui, Bing

2018-01-01

The coordination of fractional-order nonlinear multi-agent systems via distributed impulsive control method is studied in this paper. Based on the theory of impulsive differential equations, algebraic graph theory, Lyapunov stability theory and Mittag-Leffler function, two novel sufficient conditions for achieving the cooperative control of a class of fractional-order nonlinear multi-agent systems are derived. Finally, two numerical simulations are verified to illustrate the effectiveness and feasibility of the proposed method.

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.

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.

Multi-agent cooperation pursuit based on an extension of AALAADIN organisational model

NASA Astrophysics Data System (ADS)

Souidi, Mohammed El Habib; Songhao, Piao; Guo, Li; Lin, Chang

2016-11-01

An approach of cooperative pursuit for multiple mobile targets based on multi-agents system is discussed. In this kind of problem the pursuit process is divided into two kinds of tasks. The first one (coalition problem) is designed to solve the problem of the pursuit team formation. To achieve this mission, we used an innovative method based on a dynamic organisation and reorganisation of the pursuers' groups. We introduce our coalition strategy extended from the organisational agent, group, role model by assigning an access mechanism to the groups inspired by fuzzy logic principles. The second task (motion problem) is the treatment of the pursuers' motion strategy. To manage this problem we applied the principles of the Markov decision process. Simulation results show the feasibility and validity of the given proposal.

Cultural Geography Modeling and Analysis in Helmand Province

DTIC Science & Technology

2010-10-01

the application of an agent-based model called “Cultural Geography” to represent the civilian populace. This project uses a multi-agent system ...represent the civilian populace. This project uses a multi-agent system consisting of an environment, agents, objects (things), operations that can be...environments[1]. The model is patterned after the conflict eco- system described by Kilcullen[2] in an attempt to capture the complexities of irregular

Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

PubMed

Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

2016-08-01

In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

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 flocking algorithm for multi-agent systems with connectivity preservation under hybrid metric-topological interactions.

PubMed

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-01-01

In this paper, we propose a connectivity-preserving flocking algorithm for multi-agent systems in which the neighbor set of each agent is determined by the hybrid metric-topological distance so that the interaction topology can be represented as the range-limited Delaunay graph, which combines the properties of the commonly used disk graph and Delaunay graph. As a result, the proposed flocking algorithm has the following advantages over the existing ones. First, range-limited Delaunay graph is sparser than the disk graph so that the information exchange among agents is reduced significantly. Second, some links irrelevant to the connectivity can be dynamically deleted during the evolution of the system. Thus, the proposed flocking algorithm is more flexible than existing algorithms, where links are not allowed to be disconnected once they are created. Finally, the multi-agent system spontaneously generates a regular quasi-lattice formation without imposing the constraint on the ratio of the sensing range of the agent to the desired distance between two adjacent agents. With the interaction topology induced by the hybrid distance, the proposed flocking algorithm can still be implemented in a distributed manner. We prove that the proposed flocking algorithm can steer the multi-agent system to a stable flocking motion, provided the initial interaction topology of multi-agent systems is connected and the hysteresis in link addition is smaller than a derived upper bound. The correctness and effectiveness of the proposed algorithm are verified by extensive numerical simulations, where the flocking algorithms based on the disk and Delaunay graph are compared.

A flocking algorithm for multi-agent systems with connectivity preservation under hybrid metric-topological interactions

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

In this paper, we propose a connectivity-preserving flocking algorithm for multi-agent systems in which the neighbor set of each agent is determined by the hybrid metric-topological distance so that the interaction topology can be represented as the range-limited Delaunay graph, which combines the properties of the commonly used disk graph and Delaunay graph. As a result, the proposed flocking algorithm has the following advantages over the existing ones. First, range-limited Delaunay graph is sparser than the disk graph so that the information exchange among agents is reduced significantly. Second, some links irrelevant to the connectivity can be dynamically deleted during the evolution of the system. Thus, the proposed flocking algorithm is more flexible than existing algorithms, where links are not allowed to be disconnected once they are created. Finally, the multi-agent system spontaneously generates a regular quasi-lattice formation without imposing the constraint on the ratio of the sensing range of the agent to the desired distance between two adjacent agents. With the interaction topology induced by the hybrid distance, the proposed flocking algorithm can still be implemented in a distributed manner. We prove that the proposed flocking algorithm can steer the multi-agent system to a stable flocking motion, provided the initial interaction topology of multi-agent systems is connected and the hysteresis in link addition is smaller than a derived upper bound. The correctness and effectiveness of the proposed algorithm are verified by extensive numerical simulations, where the flocking algorithms based on the disk and Delaunay graph are compared. PMID:29462217

Technology Review of Multi-Agent Systems and Tools

DTIC Science & Technology

2005-06-01

over a network, including the Internet. A web services architecture is the logical evolution of object-oriented analysis and design coupled with...the logical evolution of components geared towards the architecture, design, implementation, and deployment of e-business solutions. As in object...querying. The Web Services architecture describes the principles behind the next generation of e- business architectures, presenting a logical evolution

Using Work Action Analysis to Identify Web-Portal Requirements for a Professional Development Program

ERIC Educational Resources Information Center

Nickles, George

2007-01-01

This article describes using Work Action Analysis (WAA) as a method for identifying requirements for a web-based portal that supports a professional development program. WAA is a cognitive systems engineering method for modeling multi-agent systems to support design and evaluation. A WAA model of the professional development program of the…

Note-Taking within MetaTutor: Interactions between an Intelligent Tutoring System and Prior Knowledge on Note-Taking and Learning

ERIC Educational Resources Information Center

Trevors, Gregory; Duffy, Melissa; Azevedo, Roger

2014-01-01

Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE--MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and…

Multi-Agent Strategic Modeling in a Specific Environment

NASA Astrophysics Data System (ADS)

Gams, Matjaz; Bezek, Andraz

Multi-agent modeling in ambient intelligence (AmI) is concerned with the following task [19]: How can external observations of multi-agent systems in the ambient be used to analyze, model, and direct agent behavior? The main purpose is to obtain knowledge about acts in the environment thus enabling proper actions of the AmI systems [1]. Analysis of such systems must thus capture complex world state representation and asynchronous agent activities. Instead of studying basic numerical data, researchers often use more complex data structures, such as rules and decision trees. Some methods are extremely useful when characterizing state space, but lack the ability to clearly represent temporal state changes occurred by agent actions. To comprehend simultaneous agent actions and complex changes of state space, most often a combination of graphical and symbolical representation performs better in terms of human understanding and performance.

Modeling the Dynamics of Task Allocation and Specialization in Honeybee Societies

NASA Astrophysics Data System (ADS)

Hoogendoorn, Mark; Schut, Martijn C.; Treur, Jan

The concept of organization has been studied in sciences such as social science and economics, but recently also in artificial intelligence [Furtado 2005, Giorgini 2004, and McCallum 2005]. With the desire to analyze and design more complex systems consisting of larger numbers of agents (e.g., in nature, society, or software), the need arises for a concept of higher abstraction than the concept agent. To this end, organizational modeling is becoming a practiced stage in the analysis and design of multi-agent systems, hereby taking into consideration the environment of the organization. An environment can have a high degree of variability which might require organizations to adapt to the environment's dynamics, to ensure a continuous proper functioning of the organization. Hence, such change processes are a crucial function of the organization and should be part of the organizational model.

Flexibility Support for Homecare Applications Based on Models and Multi-Agent Technology

PubMed Central

Armentia, Aintzane; Gangoiti, Unai; Priego, Rafael; Estévez, Elisabet; Marcos, Marga

2015-01-01

In developed countries, public health systems are under pressure due to the increasing percentage of population over 65. In this context, homecare based on ambient intelligence technology seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and help optimize medical resources. Thus, current technological developments make it possible to build complex homecare applications that demand, among others, flexibility mechanisms for being able to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node failure (availability). The solution proposed in this paper copes with these flexibility requirements through the whole life-cycle of the target applications: from design phase to runtime. The proposed domain modeling approach allows medical staff to design customized applications, taking into account the adaptability needs. It also guides software developers during system implementation. The application execution is managed by a multi-agent based middleware, making it possible to meet adaptation requirements, assuring at the same time the availability of the system even for stateful applications. PMID:26694416

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Rendezvous with connectivity preservation for multi-robot systems with an unknown leader

NASA Astrophysics Data System (ADS)

Dong, Yi

2018-02-01

This paper studies the leader-following rendezvous problem with connectivity preservation for multi-agent systems composed of uncertain multi-robot systems subject to external disturbances and an unknown leader, both of which are generated by a so-called exosystem with parametric uncertainty. By combining internal model design, potential function technique and adaptive control, two distributed control strategies are proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances. It is also worth to mention that the uncertain parameters in the multi-robot systems and exosystem are further allowed to belong to unknown and unbounded sets when applying the second fully distributed control law containing a dynamic gain inspired by high-gain adaptive control or self-tuning regulator.

Coordination between Generation and Transmission Maintenance Scheduling by Means of Multi-agent Technique

NASA Astrophysics Data System (ADS)

Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki

This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.

A Survey of Collective Intelligence

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan

1999-01-01

This chapter presents the science of "COllective INtelligence" (COIN). A COIN is a large multi-agent systems where: i) the agents each run reinforcement learning (RL) algorithms; ii) there is little to no centralized communication or control; iii) there is a provided world utility function that, rates the possible histories of tile full system. Tile conventional approach to designing large distributed systems to optimize a world utility does not use agents running RL algorithms. Rather that approach begins with explicit modeling of the overall system's dynamics, followed by detailed hand-tuning of the interactions between the components to ensure that they "cooperate" as far as the world utility is concerned. This approach is labor-intensive, often results in highly non-robust systems, and usually results in design techniques that, have limited applicability. In contrast, with COINs we wish to solve the system design problems implicitly, via the 'adaptive' character of the RL algorithms of each of the agents. This COIN approach introduces an entirely new, profound design problem: Assuming the RL algorithms are able to achieve high rewards, what reward functions for the individual agents will, when pursued by those agents, result in high world utility? In other words, what reward functions will best ensure that we do not have phenomena like the tragedy of the commons, or Braess's paradox? Although still very young, the science of COINs has already resulted in successes in artificial domains, in particular in packet-routing, the leader-follower problem, and in variants of Arthur's "El Farol bar problem". It is expected that as it matures not only will COIN science expand greatly the range of tasks addressable by human engineers, but it will also provide much insight into already established scientific fields, such as economics, game theory, or population biology.

A Multi-Agent System Architecture for Sensor Networks

PubMed Central

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

A multi-agent system architecture for sensor networks.

PubMed

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

Attitude coordination of multi-HUG formation based on multibody system theory

NASA Astrophysics Data System (ADS)

Xue, Dong-yang; Wu, Zhi-liang; Qi, Er-mai; Wang, Yan-hui; Wang, Shu-xin

2017-04-01

Application of multiple hybrid underwater gliders (HUGs) is a promising method for large scale, long-term ocean survey. Attitude coordination has become a requisite for task execution of multi-HUG formation. In this paper, a multibody model is presented for attitude coordination among agents in the HUG formation. The HUG formation is regarded as a multi-rigid body system. The interaction between agents in the formation is described by artificial potential field (APF) approach. Attitude control torque is composed of a conservative torque generated by orientation potential field and a dissipative term related with angular velocity. Dynamic modeling of the multibody system is presented to analyze the dynamic process of the HUG formation. Numerical calculation is carried out to simulate attitude synchronization with two kinds of formation topologies. Results show that attitude synchronization can be fulfilled based on the multibody method described in this paper. It is also indicated that different topologies affect attitude control quality with respect to energy consumption and adjusting time. Low level topology should be adopted during formation control scheme design to achieve a better control effect.

A Distributed Multi-Agent System for Collaborative Information Management and Learning

NASA Technical Reports Server (NTRS)

Chen, James R.; Wolfe, Shawn R.; Wragg, Stephen D.; Koga, Dennis (Technical Monitor)

2000-01-01

In this paper, we present DIAMS, a system of distributed, collaborative agents to help users access, manage, share and exchange information. A DIAMS personal agent helps its owner find information most relevant to current needs. It provides tools and utilities for users to manage their information repositories with dynamic organization and virtual views. Flexible hierarchical display is integrated with indexed query search-to support effective information access. Automatic indexing methods are employed to support user queries and communication between agents. Contents of a repository are kept in object-oriented storage to facilitate information sharing. Collaboration between users is aided by easy sharing utilities as well as automated information exchange. Matchmaker agents are designed to establish connections between users with similar interests and expertise. DIAMS agents provide needed services for users to share and learn information from one another on the World Wide Web.

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.

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.

Research on monitoring system of water resources in Shiyang River Basin based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhao, T. H.; Yin, Z.; Song, Y. Z.

2012-11-01

The Shiyang River Basin is the most populous, economy relatively develop, the highest degree of development and utilization of water resources, water conflicts the most prominent, ecological environment problems of the worst hit areas in Hexi inland river basin in Gansu province. the contradiction between people and water is aggravated constantly in the basin. This text combines multi-Agent technology with monitoring system of water resource, the establishment of a management center, telemetry Agent Federation, as well as the communication network between the composition of the Shiyang River Basin water resources monitoring system. By taking advantage of multi-agent system intelligence and communications coordination to improve the timeliness of the basin water resources monitoring.

Finite-time and fixed-time leader-following consensus for multi-agent systems with discontinuous inherent dynamics

NASA Astrophysics Data System (ADS)

Ning, Boda; Jin, Jiong; Zheng, Jinchuan; Man, Zhihong

2018-06-01

This paper is concerned with finite-time and fixed-time consensus of multi-agent systems in a leader-following framework. Different from conventional leader-following tracking approaches where inherent dynamics satisfying the Lipschitz continuous condition is required, a more generalised case is investigated: discontinuous inherent dynamics. By nonsmooth techniques, a nonlinear protocol is first proposed to achieve the finite-time leader-following consensus. Then, based on fixed-time stability strategies, the fixed-time leader-following consensus problem is solved. An upper bound of settling time is obtained by using a new protocol, and such a bound is independent of initial states, thereby providing additional options for designers in practical scenarios where initial conditions are unavailable. Finally, numerical simulations are provided to demonstrate the effectiveness of the theoretical results.

Model of load balancing using reliable algorithm with multi-agent system

NASA Astrophysics Data System (ADS)

Afriansyah, M. F.; Somantri, M.; Riyadi, M. A.

2017-04-01

Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable.

Multi-agent systems: effective approach for cancer care information management.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Rahimi, Azin

2013-01-01

Physicians, in order to study the causes of cancer, detect cancer earlier, prevent or determine the effectiveness of treatment, and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive, and timely cancer data. The cancer care environment has become more complex because of the need for coordination and communication among health care professionals with different skills in a variety of roles and the existence of large amounts of data with various formats. The goals of health care systems in such a complex environment are correct health data management, providing appropriate information needs of users to enhance the integrity and quality of health care, timely access to accurate information and reducing medical errors. These roles in new systems with use of agents efficiently perform well. Because of the potential capability of agent systems to solve complex and dynamic health problems, health care system, in order to gain full advantage of E- health, steps must be taken to make use of this technology. Multi-agent systems have effective roles in health service quality improvement especially in telemedicine, emergency situations and management of chronic diseases such as cancer. In the design and implementation of agent based systems, planning items such as information confidentiality and privacy, architecture, communication standards, ethical and legal aspects, identification opportunities and barriers should be considered. It should be noted that usage of agent systems only with a technical view is associated with many problems such as lack of user acceptance. The aim of this commentary is to survey applications, opportunities and barriers of this new artificial intelligence tool for cancer care information as an approach to improve cancer care management.

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.

Direct visualization of gastrointestinal tract with lanthanide-doped BaYbF5 upconversion nanoprobes.

PubMed

Liu, Zhen; Ju, Enguo; Liu, Jianhua; Du, Yingda; Li, Zhengqiang; Yuan, Qinghai; Ren, Jinsong; Qu, Xiaogang

2013-10-01

Nanoparticulate contrast agents have attracted a great deal of attention along with the rapid development of modern medicine. Here, a binary contrast agent based on PAA modified BaYbF5:Tm nanoparticles for direct visualization of gastrointestinal (GI) tract has been designed and developed via a one-pot solvothermal route. By taking advantages of excellent colloidal stability, low cytotoxicity, and neglectable hemolysis of these well-designed nanoparticles, their feasibility as a multi-modal contrast agent for GI tract was intensively investigated. Significant enhancement of contrast efficacy relative to clinical barium meal and iodine-based contrast agent was evaluated via X-ray imaging and CT imaging in vivo. By doping Tm(3+) ions into these nanoprobes, in vivo NIR-NIR imaging was then demonstrated. Unlike some invasive imaging modalities, non-invasive imaging strategy including X-ray imaging, CT imaging, and UCL imaging for GI tract could extremely reduce the painlessness to patients, effectively facilitate imaging procedure, as well as rationality economize diagnostic time. Critical to clinical applications, long-term toxicity of our contrast agent was additionally investigated in detail, indicating their overall safety. Based on our results, PAA-BaYbF5:Tm nanoparticles were the excellent multi-modal contrast agent to integrate X-ray imaging, CT imaging, and UCL imaging for direct visualization of GI tract with low systemic toxicity. Copyright © 2013 Elsevier Ltd. All rights reserved.

The agent-based spatial information semantic grid

NASA Astrophysics Data System (ADS)

Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

2006-10-01

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid management layer establishes a virtual environment that integrates seamlessly all GIS notes. 2) When the resource management system searches data on different spatial information systems, it transfers the meaning of different Local Ontology Agents rather than access data directly. So the ability of search and query can be said to be on the semantic level. 3) The data access procedure is transparent to guests, that is, they could access the information from remote site as current disk because the General Ontology Agent could automatically link data by the Data Agents that link the Ontology concept to GIS data. 4) The capability of processing massive spatial data. Storing, accessing and managing massive spatial data from TB to PB; efficiently analyzing and processing spatial data to produce model, information and knowledge; and providing 3D and multimedia visualization services. 5) The capability of high performance computing and processing on spatial information. Solving spatial problems with high precision, high quality, and on a large scale; and process spatial information in real time or on time, with high-speed and high efficiency. 6) The capability of sharing spatial resources. The distributed heterogeneous spatial information resources are Shared and realizing integrated and inter-operated on semantic level, so as to make best use of spatial information resources,such as computing resources, storage devices, spatial data (integrating from GIS, RS and GPS), spatial applications and services, GIS platforms, 7) The capability of integrating legacy GIS system. A ASISG can not only be used to construct new advanced spatial application systems, but also integrate legacy GIS system, so as to keep extensibility and inheritance and guarantee investment of users. 8) The capability of collaboration. Large-scale spatial information applications and services always involve different departments in different geographic places, so remote and uniform services are needed. 9) The capability of supporting integration of heterogeneous systems. Large-scale spatial information systems are always synthetically applications, so ASISG should provide interoperation and consistency through adopting open and applied technology standards. 10) The capability of adapting dynamic changes. Business requirements, application patterns, management strategies, and IT products always change endlessly for any departments, so ASISG should be self-adaptive. Two examples are provided in this paper, those examples provide a detailed way on how you design your semantic grid based on Multi-Agent systems and Ontology. In conclusion, the semantic grid of spatial information system could improve the ability of the integration and interoperability of spatial information grid.

Distributed Evaluation Functions for Fault Tolerant Multi-Rover Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Turner, Kagan

2005-01-01

The ability to evolve fault tolerant control strategies for large collections of agents is critical to the successful application of evolutionary strategies to domains where failures are common. Furthermore, while evolutionary algorithms have been highly successful in discovering single-agent control strategies, extending such algorithms to multiagent domains has proven to be difficult. In this paper we present a method for shaping evaluation functions for agents that provide control strategies that both are tolerant to different types of failures and lead to coordinated behavior in a multi-agent setting. This method neither relies of a centralized strategy (susceptible to single point of failures) nor a distributed strategy where each agent uses a system wide evaluation function (severe credit assignment problem). In a multi-rover problem, we show that agents using our agent-specific evaluation perform up to 500% better than agents using the system evaluation. In addition we show that agents are still able to maintain a high level of performance when up to 60% of the agents fail due to actuator, communication or controller faults.

Endogenous Price Bubbles in a Multi-Agent System of the Housing Market

PubMed Central

2015-01-01

Economic history shows a large number of boom-bust cycles, with the U.S. real estate market as one of the latest examples. Classical economic models have not been able to provide a full explanation for this type of market dynamics. Therefore, we analyze home prices in the U.S. using an alternative approach, a multi-agent complex system. Instead of the classical assumptions of agent rationality and market efficiency, agents in the model are heterogeneous, adaptive, and boundedly rational. We estimate the multi-agent system with historical house prices for the U.S. market. The model fits the data well and a deterministic version of the model can endogenously produce boom-and-bust cycles on the basis of the estimated coefficients. This implies that trading between agents themselves can create major price swings in absence of fundamental news. PMID:26107740

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.

Finite-time synchronization for second-order nonlinear multi-agent system via pinning exponent sliding mode control.

PubMed

Hou, Huazhou; Zhang, Qingling

2016-11-01

In this paper we investigate the finite-time synchronization for second-order multi-agent system via pinning exponent sliding mode control. Firstly, for the nonlinear multi-agent system, differential mean value theorem is employed to transfer the nonlinear system into linear system, then, by pinning only one node in the system with novel exponent sliding mode control, we can achieve synchronization in finite time. Secondly, considering the 3-DOF helicopter system with nonlinear dynamics and disturbances, the novel exponent sliding mode control protocol is applied to only one node to achieve the synchronization. Finally, the simulation results show the effectiveness and the advantages of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-Agent Architecture with Support to Quality of Service and Quality of Control

NASA Astrophysics Data System (ADS)

Poza-Luján, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, Jose-Enrique

Multi Agent Systems (MAS) are one of the most suitable frameworks for the implementation of intelligent distributed control system. Agents provide suitable flexibility to give support to implied heterogeneity in cyber-physical systems. Quality of Service (QoS) and Quality of Control (QoC) parameters are commonly utilized to evaluate the efficiency of the communications and the control loop. Agents can use the quality measures to take a wide range of decisions, like suitable placement on the control node or to change the workload to save energy. This article describes the architecture of a multi agent system that provides support to QoS and QoC parameters to optimize de system. The architecture uses a Publish-Subscriber model, based on Data Distribution Service (DDS) to send the control messages. Due to the nature of the Publish-Subscribe model, the architecture is suitable to implement event-based control (EBC) systems. The architecture has been called FSACtrl.

Multi-agent cooperation rescue algorithm based on influence degree and state prediction

NASA Astrophysics Data System (ADS)

Zheng, Yanbin; Ma, Guangfu; Wang, Linlin; Xi, Pengxue

2018-04-01

Aiming at the multi-agent cooperative rescue in disaster, a multi-agent cooperative rescue algorithm based on impact degree and state prediction is proposed. Firstly, based on the influence of the information in the scene on the collaborative task, the influence degree function is used to filter the information. Secondly, using the selected information to predict the state of the system and Agent behavior. Finally, according to the result of the forecast, the cooperative behavior of Agent is guided and improved the efficiency of individual collaboration. The simulation results show that this algorithm can effectively solve the cooperative rescue problem of multi-agent and ensure the efficient completion of the task.

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

A Novel Network Attack Audit System based on Multi-Agent Technology

NASA Astrophysics Data System (ADS)

Jianping, Wang; Min, Chen; Xianwen, Wu

A network attack audit system which includes network attack audit Agent, host audit Agent and management control center audit Agent is proposed. And the improved multi-agent technology is carried out in the network attack audit Agent which has achieved satisfactory audit results. The audit system in terms of network attack is just in-depth, and with the function improvement of network attack audit Agent, different attack will be better analyzed and audit. In addition, the management control center Agent should manage and analyze audit results from AA (or HA) and audit data on time. And the history files of network packets and host log data should also be audit to find deeper violations that cannot be found in real time.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

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.

An Approach to Quantify Workload in a System of Agents

NASA Technical Reports Server (NTRS)

Stocker, Richard; Rungta, Neha; Mercer, Eric; Raimondi, Franco; Holbrook, Jon; Cardoza, Colleen; Goodrich, Michael

2015-01-01

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

Bipartite consensus for multi-agent systems with antagonistic interactions and communication delays

NASA Astrophysics Data System (ADS)

Guo, Xing; Lu, Jianquan; Alsaedi, Ahmed; Alsaadi, Fuad E.

2018-04-01

This paper studies the consensus problems over signed digraphs with arbitrary finite communication delays. For the considered system, the information flow is directed and only locally delayed information can be used for each node. We derive that bipartite consensus of this system can be realized when the associated signed digraph is strongly connected. Furthermore, for structurally balanced networks, this paper studies the pinning partite consensus for the considered system. we design a pinning scheme to pin any one agent in the signed network, and obtain that the network achieves pinning bipartite consensus with any initial conditions. Finally, two examples are provided to demonstrate the effectiveness of our main results.

Multi-agent systems and their applications

DOE PAGES

Xie, Jing; Liu, Chen-Ching

2017-07-14

The number of distributed energy components and devices continues to increase globally. As a result, distributed control schemes are desirable for managing and utilizing these devices, together with the large amount of data. In recent years, agent-based technology becomes a powerful tool for engineering applications. As a computational paradigm, multi agent systems (MASs) provide a good solution for distributed control. Here in this paper, MASs and applications are discussed. A state-of-the-art literature survey is conducted on the system architecture, consensus algorithm, and multi-agent platform, framework, and simulator. In addition, a distributed under-frequency load shedding (UFLS) scheme is proposed using themore » MAS. Simulation results for a case study are presented. The future of MASs is discussed in the conclusion.« less

Multi-agent systems and their applications

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

Xie, Jing; Liu, Chen-Ching

The number of distributed energy components and devices continues to increase globally. As a result, distributed control schemes are desirable for managing and utilizing these devices, together with the large amount of data. In recent years, agent-based technology becomes a powerful tool for engineering applications. As a computational paradigm, multi agent systems (MASs) provide a good solution for distributed control. Here in this paper, MASs and applications are discussed. A state-of-the-art literature survey is conducted on the system architecture, consensus algorithm, and multi-agent platform, framework, and simulator. In addition, a distributed under-frequency load shedding (UFLS) scheme is proposed using themore » MAS. Simulation results for a case study are presented. The future of MASs is discussed in the conclusion.« less

Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

NASA Astrophysics Data System (ADS)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.

Designing Realistic Human Behavior into Multi-Agent Systems

DTIC Science & Technology

2001-09-01

different results based on some sort of randomness built into it, a trend can be looked at over time and a success or failure rate can be...simulation remains in that state, very different results can be achieved each simulation run. An analyst can look at success and failure over a long

Impact of immigrants on a multi-agent economical system

PubMed Central

Razakanirina, Ranaivo; Groen, Derek

2018-01-01

We consider a multi-agent model of a simple economical system and study the impacts of a wave of immigrants on the stability of the system. Our model couples a labor market with a goods market. We first create a stable economy with N agents and study the impact of adding n new workers in the system. The time to reach a new equilibrium market is found to obey a power law in n. The new wages and market prices are observed to decrease as 1/n, whereas the wealth of agents remains unchanged. PMID:29795633

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.

Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

PubMed

Wilk, Szymon; Kezadri-Hamiaz, Mounira; Rosu, Daniela; Kuziemsky, Craig; Michalowski, Wojtek; Amyot, Daniel; Carrier, Marc

2016-02-01

In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent system that allows IHTs to manage patients according to presentation-specific clinical workflows. In this paper, we describe a significant extension of the MET4 system that allows for supporting rich team dynamics (understood as team formation, management and task-practitioner allocation), including selection and maintenance of the most responsible physician and more complex rules of selecting practitioners for the workflow tasks. In order to develop this extension, we introduced three semantic components: (1) a revised ontology describing concepts and relations pertinent to IHTs, workflows, and managed patients, (2) a set of behavioral rules describing the team dynamics, and (3) an instance base that stores facts corresponding to instances of concepts from the ontology and to relations between these instances. The semantic components are represented in first-order logic and they can be automatically processed using theorem proving and model finding techniques. We employ these techniques to find models that correspond to specific decisions controlling the dynamics of IHT. In the paper, we present the design of extended MET4 with a special focus on the new semantic components. We then describe its proof-of-concept implementation using the WADE multi-agent platform and the Z3 solver (theorem prover/model finder). We illustrate the main ideas discussed in the paper with a clinical scenario of an IHT managing a patient with chronic kidney disease.

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.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Space/ground systems as cooperating agents

NASA Technical Reports Server (NTRS)

Grant, T. J.

1994-01-01

Within NASA and the European Space Agency (ESA) it is agreed that autonomy is an important goal for the design of future spacecraft and that this requires on-board artificial intelligence. NASA emphasizes deep space and planetary rover missions, while ESA considers on-board autonomy as an enabling technology for missions that must cope with imperfect communications. ESA's attention is on the space/ground system. A major issue is the optimal distribution of intelligent functions within the space/ground system. This paper describes the multi-agent architecture for space/ground systems (MAASGS) which would enable this issue to be investigated. A MAASGS agent may model a complete spacecraft, a spacecraft subsystem or payload, a ground segment, a spacecraft control system, a human operator, or an environment. The MAASGS architecture has evolved through a series of prototypes. The paper recommends that the MAASGS architecture should be implemented in the operational Dutch Utilization Center.

Distributed event-triggered consensus tracking of second-order multi-agent systems with a virtual leader

NASA Astrophysics Data System (ADS)

Jie, Cao; Zhi-Hai, Wu; Li, Peng

2016-05-01

This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy. Project supported by the National Natural Science Foundation of China (Grant Nos. 61203147, 61374047, and 61403168).

Prescribed performance distributed consensus control for nonlinear multi-agent systems with unknown dead-zone input

NASA Astrophysics Data System (ADS)

Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang

2018-05-01

In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Flocking with connectivity preservation for disturbed nonlinear multi-agent systems by output feedback

NASA Astrophysics Data System (ADS)

Li, Ping; Zhang, Baoyong; Ma, Qian; Xu, Shengyuan; Chen, Weimin; Zhang, Zhengqiang

2018-05-01

This paper considers the problem of flocking with connectivity preservation for a class of disturbed nonlinear multi-agent systems. In order to deal with the nonlinearities in the dynamic of all agents, some auxiliary variables are introduced into the state observer for stability analysis. By proposing a bounded potential function and using adaptive theory, a novel output feedback consensus algorithm is developed to guarantee that the states of all agents achieve flocking with connectivity preservation.

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

NASA Technical Reports Server (NTRS)

Tumer, Kagan

2005-01-01

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

Knowledge Management in Role Based Agents

NASA Astrophysics Data System (ADS)

Kır, Hüseyin; Ekinci, Erdem Eser; Dikenelli, Oguz

In multi-agent system literature, the role concept is getting increasingly researched to provide an abstraction to scope beliefs, norms, goals of agents and to shape relationships of the agents in the organization. In this research, we propose a knowledgebase architecture to increase applicability of roles in MAS domain by drawing inspiration from the self concept in the role theory of sociology. The proposed knowledgebase architecture has granulated structure that is dynamically organized according to the agent's identification in a social environment. Thanks to this dynamic structure, agents are enabled to work on consistent knowledge in spite of inevitable conflicts between roles and the agent. The knowledgebase architecture is also implemented and incorporated into the SEAGENT multi-agent system development framework.

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.

Robust Feedback Control of Reconfigurable Multi-Agent Systems in Uncertain Adversarial Environments

DTIC Science & Technology

2015-07-09

R. G., Optimal Lunar Landing and Retargeting using a Hybrid Control Strategy. Proceedings of the 2013 AAS/AIAA Space Flight Mechanics Meeting (AAS...Furfaro, R. & Sanfelice, R. G., Switching System Model for Pinpoint Lunar Landing Guidance Using a Hybrid Control Strategy. Proceedings of the AIAA...methods in distributed settings and the design of numerical methods to properly compute their trajectories . We have generate results showing that

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.

An Agent-Based Model for the Role of Short-Term Memory Enhancement in the Emergence of Grammatical Agreement.

PubMed

Vera, Javier

2018-01-01

What is the influence of short-term memory enhancement on the emergence of grammatical agreement systems in multi-agent language games? Agreement systems suppose that at least two words share some features with each other, such as gender, number, or case. Previous work, within the multi-agent language-game framework, has recently proposed models stressing the hypothesis that the emergence of a grammatical agreement system arises from the minimization of semantic ambiguity. On the other hand, neurobiological evidence argues for the hypothesis that language evolution has mainly related to an increasing of short-term memory capacity, which has allowed the online manipulation of words and meanings participating particularly in grammatical agreement systems. Here, the main aim is to propose a multi-agent language game for the emergence of a grammatical agreement system, under measurable long-range relations depending on the short-term memory capacity. Computer simulations, based on a parameter that measures the amount of short-term memory capacity, suggest that agreement marker systems arise in a population of agents equipped at least with a critical short-term memory capacity.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

ERIC Educational Resources Information Center

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Towards Symbolic Model Checking for Multi-Agent Systems via OBDDs

NASA Technical Reports Server (NTRS)

Raimondi, Franco; Lomunscio, Alessio

2004-01-01

We present an algorithm for model checking temporal-epistemic properties of multi-agent systems, expressed in the formalism of interpreted systems. We first introduce a technique for the translation of interpreted systems into boolean formulae, and then present a model-checking algorithm based on this translation. The algorithm is based on OBDD's, as they offer a compact and efficient representation for boolean formulae.

Faithful teleportation of multi-particle states involving multi spatially remote agents via probabilistic channels

NASA Astrophysics Data System (ADS)

Jiang, Min; Li, Hui; Zhang, Zeng-ke; Zeng, Jia

2011-02-01

We present an approach to faithfully teleport an unknown quantum state of entangled particles in a multi-particle system involving multi spatially remote agents via probabilistic channels. In our scheme, the integrity of an entangled multi-particle state can be maintained even when the construction of a faithful channel fails. Furthermore, in a quantum teleportation network, there are generally multi spatially remote agents which play the role of relay nodes between a sender and a distant receiver. Hence, we propose two schemes for directly and indirectly constructing a faithful channel between the sender and the distant receiver with the assistance of relay agents, respectively. Our results show that the required auxiliary particle resources, local operations and classical communications are considerably reduced for the present purpose.

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.

Optimal Reward Functions in Distributed Reinforcement Learning

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan

2000-01-01

We consider the design of multi-agent systems so as to optimize an overall world utility function when (1) those systems lack centralized communication and control, and (2) each agents runs a distinct Reinforcement Learning (RL) algorithm. A crucial issue in such design problems is to initialize/update each agent's private utility function, so as to induce best possible world utility. Traditional 'team game' solutions to this problem sidestep this issue and simply assign to each agent the world utility as its private utility function. In previous work we used the 'Collective Intelligence' framework to derive a better choice of private utility functions, one that results in world utility performance up to orders of magnitude superior to that ensuing from use of the team game utility. In this paper we extend these results. We derive the general class of private utility functions that both are easy for the individual agents to learn and that, if learned well, result in high world utility. We demonstrate experimentally that using these new utility functions can result in significantly improved performance over that of our previously proposed utility, over and above that previous utility's superiority to the conventional team game utility.

Parallel Agent-Based Simulations on Clusters of GPUs and Multi-Core Processors

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

Aaby, Brandon G; Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Messagemore » Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.« less

Design of a Two-level Adaptive Multi-Agent System for Malaria Vectors driven by an ontology

PubMed Central

Koum, Guillaume; Yekel, Augustin; Ndifon, Bengyella; Etang, Josiane; Simard, Frédéric

2007-01-01

Background The understanding of heterogeneities in disease transmission dynamics as far as malaria vectors are concerned is a big challenge. Many studies while tackling this problem don't find exact models to explain the malaria vectors propagation. Methods To solve the problem we define an Adaptive Multi-Agent System (AMAS) which has the property to be elastic and is a two-level system as well. This AMAS is a dynamic system where the two levels are linked by an Ontology which allows it to function as a reduced system and as an extended system. In a primary level, the AMAS comprises organization agents and in a secondary level, it is constituted of analysis agents. Its entry point, a User Interface Agent, can reproduce itself because it is given a minimum of background knowledge and it learns appropriate "behavior" from the user in the presence of ambiguous queries and from other agents of the AMAS in other situations. Results Some of the outputs of our system present a series of tables, diagrams showing some factors like Entomological parameters of malaria transmission, Percentages of malaria transmission per malaria vectors, Entomological inoculation rate. Many others parameters can be produced by the system depending on the inputted data. Conclusion Our approach is an intelligent one which differs from statistical approaches that are sometimes used in the field. This intelligent approach aligns itself with the distributed artificial intelligence. In terms of fight against malaria disease our system offers opportunities of reducing efforts of human resources who are not obliged to cover the entire territory while conducting surveys. Secondly the AMAS can determine the presence or the absence of malaria vectors even when specific data have not been collected in the geographical area. In the difference of a statistical technique, in our case the projection of the results in the field can sometimes appeared to be more general. PMID:17605778

Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

NASA Technical Reports Server (NTRS)

Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

2004-01-01

These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

Solving "Smart City" Transport Problems by Designing Carpooling Gamification Schemes with Multi-Agent Systems: The Case of the So-Called "Mordor of Warsaw".

PubMed

Olszewski, Robert; Pałka, Piotr; Turek, Agnieszka

2018-01-06

To reduce energy consumption and improve residents' quality of life, "smart cities" should use not only modern technologies, but also the social innovations of the "Internet of Things" (IoT) era. This article attempts to solve transport problems in a smart city's office district by utilizing gamification that incentivizes the carpooling system. The goal of the devised system is to significantly reduce the number of cars, and, consequently, to alleviate traffic jams, as well as to curb pollution and energy consumption. A representative sample of the statistical population of people working in one of the biggest office hubs in Poland (the so-called "Mordor of Warsaw") was surveyed. The collected data were processed using spatial data mining methods, and the results were a set of parameters for the multi-agent system. This approach made it possible to run a series of simulations on a set of 100,000 agents and to select an effective gamification methodology that supports the carpooling process. The implementation of the proposed solutions (a "serious game" variation of urban games) would help to reduce the number of cars by several dozen percent, significantly reduce energy consumption, eliminate traffic jams, and increase the activity of the smart city residents.

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

Distributed containment control of heterogeneous fractional-order multi-agent systems with communication delays

NASA Astrophysics Data System (ADS)

Yang, Hongyong; Han, Fujun; Zhao, Mei; Zhang, Shuning; Yue, Jun

2017-08-01

Because many networked systems can only be characterized with fractional-order dynamics in complex environments, fractional-order calculus has been studied deeply recently. When diverse individual features are shown in different agents of networked systems, heterogeneous fractional-order dynamics will be used to describe the complex systems. Based on the distinguishing properties of agents, heterogeneous fractional-order multi-agent systems (FOMAS) are presented. With the supposition of multiple leader agents in FOMAS, distributed containment control of FOMAS is studied in directed weighted topologies. By applying Laplace transformation and frequency domain theory of the fractional-order operator, an upper bound of delays is obtained to ensure containment consensus of delayed heterogenous FOMAS. Consensus results of delayed FOMAS in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.

A Distributed Intelligent E-Learning System

ERIC Educational Resources Information Center

Kristensen, Terje

2016-01-01

An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

Adaptivity in Agent-Based Routing for Data Networks

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Kirshner, Sergey; Merz, Chris J.; Turner, Kagan

2000-01-01

Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.

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.

Scare Tactics: Evaluating Problem Decompositions Using Failure Scenarios

NASA Technical Reports Server (NTRS)

Helm, B. Robert; Fickas, Stephen

1992-01-01

Our interest is in the design of multi-agent problem-solving systems, which we refer to as composite systems. We have proposed an approach to composite system design by decomposition of problem statements. An automated assistant called Critter provides a library of reusable design transformations which allow a human analyst to search the space of decompositions for a problem. In this paper we describe a method for evaluating and critiquing problem decompositions generated by this search process. The method uses knowledge stored in the form of failure decompositions attached to design transformations. We suggest the benefits of our critiquing method by showing how it could re-derive steps of a published development example. We then identify several open issues for the method.

A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures

NASA Astrophysics Data System (ADS)

Kaveh, A.; Ilchi Ghazaan, M.

2018-02-01

In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.

TACtic- A Multi Behavioral Agent for Trading Agent Competition

NASA Astrophysics Data System (ADS)

Khosravi, Hassan; Shiri, Mohammad E.; Khosravi, Hamid; Iranmanesh, Ehsan; Davoodi, Alireza

Software agents are increasingly being used to represent humans in online auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what auctions. They can do this continuously and repetitively without losing concentration. To provide a means of evaluating and comparing (benchmarking) research methods in this area the trading agent competition (TAC) was established. This paper describes the design, of TACtic. Our agent uses multi behavioral techniques at the heart of its decision making to make bidding decisions in the face of uncertainty, to make predictions about the likely outcomes of auctions, and to alter the agent's bidding strategy in response to the prevailing market conditions.

Modelling and multi-parametric control for delivery of anaesthetic agents.

PubMed

Dua, Pinky; Dua, Vivek; Pistikopoulos, Efstratios N

2010-06-01

This article presents model predictive controllers (MPCs) and multi-parametric model-based controllers for delivery of anaesthetic agents. The MPC can take into account constraints on drug delivery rates and state of the patient but requires solving an optimization problem at regular time intervals. The multi-parametric controller has all the advantages of the MPC and does not require repetitive solution of optimization problem for its implementation. This is achieved by obtaining the optimal drug delivery rates as a set of explicit functions of the state of the patient. The derivation of the controllers relies on using detailed models of the system. A compartmental model for the delivery of three drugs for anaesthesia is developed. The key feature of this model is that mean arterial pressure, cardiac output and unconsciousness of the patient can be simultaneously regulated. This is achieved by using three drugs: dopamine (DP), sodium nitroprusside (SNP) and isoflurane. A number of dynamic simulation experiments are carried out for the validation of the model. The model is then used for the design of model predictive and multi-parametric controllers, and the performance of the controllers is analyzed.

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.

Application of a Genetic Algorithm and Multi Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the Workplace

DTIC Science & Technology

2008-06-01

postponed the fulfillment of her own Masters Degree by at least 18 months so that I would have the opportunity to earn mine. She is smart , lovely...GENETIC ALGORITHM AND MULTI AGENT SYSTEM TO EXPLORE EMERGENT PATTERNS OF SOCIAL RATIONALITY AND A DISTRESS-BASED MODEL FOR DECEIT IN THE WORKPLACE...of a Genetic Algorithm and Mutli Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Robust Architectures for Complex Multi-Agent Heterogeneous Systems

DTIC Science & Technology

2014-07-23

establish the tradeoff between the control performance and the QoS of the communications network . We also derived the performance bound on the difference...accomplished within this time period leveraged the prior accomplishments in the area of networked multi-agent systems. The past work (prior to 2011...distributed control of uncertain networked systems [3]. Additionally, a preliminary collision avoidance algorithm has been developed for a team of

Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems.

PubMed

Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan

2015-11-01

This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis of the Pricing Process in Electricity Market using Multi-Agent Model

NASA Astrophysics Data System (ADS)

Shimomura, Takahiro; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji

Many electric utilities world-wide have been forced to change their ways of doing business, from vertically integrated mechanisms to open market systems. We are facing urgent issues about how we design the structures of power market systems. In order to settle down these issues, many studies have been made with market models of various characteristics and regulations. The goal of modeling analysis is to enrich our understanding of fundamental process that may appear. However, there are many kinds of modeling methods. Each has drawback and advantage about validity and versatility. This paper presents two kinds of methods to construct multi-agent market models. One is based on game theory and another is based on reinforcement learning. By comparing the results of the two methods, they can advance in validity and help us figure out potential problems in electricity markets which have oligopolistic generators, demand fluctuation and inelastic demand. Moreover, this model based on reinforcement learning enables us to consider characteristics peculiar to electricity markets which have plant unit characteristics, seasonable and hourly demand fluctuation, real-time regulation market and operating reserve market. This model figures out importance of the share of peak-load-plants and the way of designing operating reserve market.

Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.

PubMed

Liu, Shiyong; Triantis, Konstantinos P; Zhao, Li; Wang, Youfa

2018-01-01

In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.

Developing Access Control Model of Web OLAP over Trusted and Collaborative Data Warehouses

NASA Astrophysics Data System (ADS)

Fugkeaw, Somchart; Mitrpanont, Jarernsri L.; Manpanpanich, Piyawit; Juntapremjitt, Sekpon

This paper proposes the design and development of Role- based Access Control (RBAC) model for the Single Sign-On (SSO) Web-OLAP query spanning over multiple data warehouses (DWs). The model is based on PKI Authentication and Privilege Management Infrastructure (PMI); it presents a binding model of RBAC authorization based on dimension privilege specified in attribute certificate (AC) and user identification. Particularly, the way of attribute mapping between DW user authentication and privilege of dimensional access is illustrated. In our approach, we apply the multi-agent system to automate flexible and effective management of user authentication, role delegation as well as system accountability. Finally, the paper culminates in the prototype system A-COLD (Access Control of web-OLAP over multiple DWs) that incorporates the OLAP features and authentication and authorization enforcement in the multi-user and multi-data warehouse environment.

A stochastic multi-agent optimization model for energy infrastructure planning under uncertainty and competition.

DOT National Transportation Integrated Search

2017-07-04

This paper presents a stochastic multi-agent optimization model that supports energy infrastruc- : ture planning under uncertainty. The interdependence between dierent decision entities in the : system is captured in an energy supply chain network, w...

Multi-functional liposomes showing radiofrequency-triggered release and magnetic resonance imaging for tumor multi-mechanism therapy.

PubMed

Du, Bin; Han, Shuping; Li, Hongyan; Zhao, Feifei; Su, Xiangjie; Cao, Xiaohui; Zhang, Zhenzhong

2015-03-12

Recently, nanoplatforms with multiple functions, such as tumor-targeting drug carriers, MRI, optical imaging, thermal therapy etc., have become popular in the field of cancer research. The present study reports a novel multi-functional liposome for cancer theranostics. A dual targeted drug delivery with radiofrequency-triggered drug release and imaging based on the magnetic field influence was used advantageously for tumor multi-mechanism therapy. In this system, the surface of fullerene (C60) was decorated with iron oxide nanoparticles, and PEGylation formed a hybrid nanosystem (C60-Fe3O4-PEG2000). Thermosensitive liposomes (dipalmitoylphosphatidylcholine, DPPC) with DSPE-PEG2000-folate wrapped up the hybrid nanosystem and docetaxel (DTX), which were designed to combine features of biological and physical (magnetic) drug targeting for fullerene radiofrequency-triggered drug release. The magnetic liposomes not only served as powerful tumor diagnostic magnetic resonance imaging (MRI) contrast agents, but also as powerful agents for photothermal ablation of tumors. Furthermore, a remarkable thermal therapy combined chemotherapy multi-functional liposome nanoplatform converted radiofrequency energy into thermal energy to release drugs from thermosensitive liposomes, which was also observed during both in vitro and in vivo treatment. The multi-functional liposomes also could selectively kill cancer cells in highly localized regions via their excellent active tumor targeting and magnetic targeted abilities.

A Decentralized Framework for Multi-Agent Robotic Systems

PubMed Central

2018-01-01

Over the past few years, decentralization of multi-agent robotic systems has become an important research area. These systems do not depend on a central control unit, which enables the control and assignment of distributed, asynchronous and robust tasks. However, in some cases, the network communication process between robotic agents is overlooked, and this creates a dependency for each agent to maintain a permanent link with nearby units to be able to fulfill its goals. This article describes a communication framework, where each agent in the system can leave the network or accept new connections, sending its information based on the transfer history of all nodes in the network. To this end, each agent needs to comply with four processes to participate in the system, plus a fifth process for data transfer to the nearest nodes that is based on Received Signal Strength Indicator (RSSI) and data history. To validate this framework, we use differential robotic agents and a monitoring agent to generate a topological map of an environment with the presence of obstacles. PMID:29389849

Pharmacophore based design of some multi-targeted compounds targeted against pathways of diabetic complications.

PubMed

Chadha, Navriti; Silakari, Om

2017-09-01

Diabetic complications is a complex metabolic disorder developed primarily due to prolonged hyperglycemia in the body. The complexity of the disease state as well as the unifying pathophysiology discussed in the literature reports exhibited that the use of multi-targeted agents with multiple complementary biological activities may offer promising therapy for the intervention of the disease over the single-target drugs. In the present study, novel thiazolidine-2,4-dione analogues were designed as multi-targeted agents implicated against the molecular pathways involved in diabetic complications using knowledge based as well as in-silico approaches such as pharmacophore mapping, molecular docking etc. The hit molecules were duly synthesized and biochemical estimation of these molecules against aldose reductase (ALR2), protein kinase Cβ (PKCβ) and poly (ADP-ribose) polymerase 1 (PARP-1) led to identification of compound 2 that showed good potency against PARP-1 and ALR2 enzymes. These positive results support the progress of a low cost multi-targeted agent with putative roles in diabetic complications. Copyright © 2017 Elsevier Inc. All rights reserved.

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Cultural Geography Model Validation

DTIC Science & Technology

2010-03-01

the Cultural Geography Model (CGM), a government owned, open source multi - agent system utilizing Bayesian networks, queuing systems, the Theory of...referent determined either from theory or SME opinion. 4. CGM Overview The CGM is a government-owned, open source, data driven multi - agent social...HSCB, validation, social network analysis ABSTRACT: In the current warfighting environment , the military needs robust modeling and simulation (M&S

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Software Framework for Remote Patient Monitoring by Using Multi-Agent Systems Support

PubMed Central

2017-01-01

Background Although there have been significant advances in network, hardware, and software technologies, the health care environment has not taken advantage of these developments to solve many of its inherent problems. Research activities in these 3 areas make it possible to apply advanced technologies to address many of these issues such as real-time monitoring of a large number of patients, particularly where a timely response is critical. Objective The objective of this research was to design and develop innovative technological solutions to offer a more proactive and reliable medical care environment. The short-term and primary goal was to construct IoT4Health, a flexible software framework to generate a range of Internet of things (IoT) applications, containing components such as multi-agent systems that are designed to perform Remote Patient Monitoring (RPM) activities autonomously. An investigation into its full potential to conduct such patient monitoring activities in a more proactive way is an expected future step. Methods A framework methodology was selected to evaluate whether the RPM domain had the potential to generate customized applications that could achieve the stated goal of being responsive and flexible within the RPM domain. As a proof of concept of the software framework’s flexibility, 3 applications were developed with different implementations for each framework hot spot to demonstrate potential. Agents4Health was selected to illustrate the instantiation process and IoT4Health’s operation. To develop more concrete indicators of the responsiveness of the simulated care environment, an experiment was conducted while Agents4Health was operating, to measure the number of delays incurred in monitoring the tasks performed by agents. Results IoT4Health’s construction can be highlighted as our contribution to the development of eHealth solutions. As a software framework, IoT4Health offers extensibility points for the generation of applications. Applications can extend the framework in the following ways: identification, collection, storage, recovery, visualization, monitoring, anomalies detection, resource notification, and dynamic reconfiguration. Based on other outcomes involving observation of the resulting applications, it was noted that its design contributed toward more proactive patient monitoring. Through these experimental systems, anomalies were detected in real time, with agents sending notifications instantly to the health providers. Conclusions We conclude that the cost-benefit of the construction of a more generic and complex system instead of a custom-made software system demonstrated the worth of the approach, making it possible to generate applications in this domain in a more timely fashion. PMID:28347973

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

NASA Astrophysics Data System (ADS)

Huang, Chen; Chen, Long; Yun, Chaochun; Jiang, Haobin; Chen, Yuexia

2014-03-01

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention(BDI)-agent model framework, the TYRE agent, electric power steering(EPS) agent and active suspension system(ASS) agent are proposed. In the system(SYS) agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system(MAS) controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.

A nonlinear merging protocol for consensus in multi-agent systems on signed and weighted graphs

NASA Astrophysics Data System (ADS)

Feng, Shasha; Wang, Li; Li, Yijia; Sun, Shiwen; Xia, Chengyi

2018-01-01

In this paper, we investigate the multi-agent consensus for networks with undirected graphs which are not connected, especially for the signed graph in which some edge weights are positive and some edges have negative weights, and the negative-weight graph whose edge weights are negative. We propose a novel nonlinear merging consensus protocol to drive the states of all agents to converge to the same state zero which is not dependent upon the initial states of agents. If the undirected graph whose edge weights are positive is connected, then the states of all agents converge to the same state more quickly when compared to most other protocols. While the undirected graph whose edge weights might be positive or negative is unconnected, the states of all agents can still converge to the same state zero under the premise that the undirected graph can be divided into several connected subgraphs with more than one node. Furthermore, we also discuss the impact of parameter r presented in our protocol. Current results can further deepen the understanding of consensus processes for multi-agent systems.

Solving “Smart City” Transport Problems by Designing Carpooling Gamification Schemes with Multi-Agent Systems: The Case of the So-Called “Mordor of Warsaw”

PubMed Central

Turek, Agnieszka

2018-01-01

To reduce energy consumption and improve residents’ quality of life, “smart cities” should use not only modern technologies, but also the social innovations of the “Internet of Things” (IoT) era. This article attempts to solve transport problems in a smart city’s office district by utilizing gamification that incentivizes the carpooling system. The goal of the devised system is to significantly reduce the number of cars, and, consequently, to alleviate traffic jams, as well as to curb pollution and energy consumption. A representative sample of the statistical population of people working in one of the biggest office hubs in Poland (the so-called “Mordor of Warsaw”) was surveyed. The collected data were processed using spatial data mining methods, and the results were a set of parameters for the multi-agent system. This approach made it possible to run a series of simulations on a set of 100,000 agents and to select an effective gamification methodology that supports the carpooling process. The implementation of the proposed solutions (a “serious game” variation of urban games) would help to reduce the number of cars by several dozen percent, significantly reduce energy consumption, eliminate traffic jams, and increase the activity of the smart city residents. PMID:29316643

On the use of multi-agent systems for the monitoring of industrial systems

NASA Astrophysics Data System (ADS)

Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil

2016-03-01

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

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.

Multi-Agent Simulation of Allocating and Routing Ambulances Under Condition of Street Blockage after Natural Disaster

NASA Astrophysics Data System (ADS)

Azimi, S.; Delavar, M. R.; Rajabifard, A.

2017-09-01

In response to natural disasters, efficient planning for optimum allocation of the medical assistance to wounded as fast as possible and wayfinding of first responders immediately to minimize the risk of natural disasters are of prime importance. This paper aims to propose a multi-agent based modeling for optimum allocation of space to emergency centers according to the population, street network and number of ambulances in emergency centers by constraint network Voronoi diagrams, wayfinding of ambulances from emergency centers to the wounded locations and return based on the minimum ambulances travel time and path length implemented by NSGA and the use of smart city facilities to accelerate the rescue operation. Simulated annealing algorithm has been used for minimizing the difference between demands and supplies of the constrained network Voronoi diagrams. In the proposed multi-agent system, after delivering the location of the wounded and their symptoms, the constraint network Voronoi diagram for each emergency center is determined. This process was performed simultaneously for the multi-injuries in different Voronoi diagrams. In the proposed multi-agent system, the priority of the injuries for receiving medical assistance and facilities of the smart city for reporting the blocked streets was considered. Tehran Municipality District 5 was considered as the study area and during 3 minutes intervals, the volunteers reported the blocked street. The difference between the supply and the demand divided to the supply in each Voronoi diagram decreased to 0.1601. In the proposed multi-agent system, the response time of the ambulances is decreased about 36.7%.

TSI-Enhanced Pedagogical Agents to Engage Learners in Virtual Worlds

ERIC Educational Resources Information Center

Leung, Steve; Virwaney, Sandeep; Lin, Fuhua; Armstrong, AJ; Dubbelboer, Adien

2013-01-01

Building pedagogical applications in virtual worlds is a multi-disciplinary endeavor that involves learning theories, application development framework, and mediated communication theories. This paper presents a project that integrates game-based learning, multi-agent system architecture (MAS), and the theory of Transformed Social Interaction…

A Multi-Agent Approach to the Simulation of Robotized Manufacturing Systems

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The recent years of eventful industry development, brought many competing products, addressed to the same market segment. The shortening of a development cycle became a necessity if the company would like to be competitive. Because of switching to the Intelligent Manufacturing model the industry search for new scheduling algorithms, while the traditional ones do not meet the current requirements. The agent-based approach has been considered by many researchers as an important way of evolution of modern manufacturing systems. Due to the properties of the multi-agent systems, this methodology is very helpful during creation of the model of production system, allowing depicting both processing and informational part. The complexity of such approach makes the analysis impossible without the computer assistance. Computer simulation still uses a mathematical model to recreate a real situation, but nowadays the 2D or 3D virtual environments or even virtual reality have been used for realistic illustration of the considered systems. This paper will focus on robotized manufacturing system and will present the one of possible approaches to the simulation of such systems. The selection of multi-agent approach is motivated by the flexibility of this solution that offers the modularity, robustness and autonomy.

Finite-time consensus for multi-agent systems with globally bounded convergence time under directed communication graphs

NASA Astrophysics Data System (ADS)

Fu, Junjie; Wang, Jin-zhi

2017-09-01

In this paper, we study the finite-time consensus problems with globally bounded convergence time also known as fixed-time consensus problems for multi-agent systems subject to directed communication graphs. Two new distributed control strategies are proposed such that leaderless and leader-follower consensus are achieved with convergence time independent on the initial conditions of the agents. Fixed-time formation generation and formation tracking problems are also solved as the generalizations. Simulation examples are provided to demonstrate the performance of the new controllers.

Multi-agent electricity market modeling with EMCAS.

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

North, M.; Macal, C.; Conzelmann, G.

2002-09-05

Electricity systems are a central component of modern economies. Many electricity markets are transitioning from centrally regulated systems to decentralized markets. Furthermore, several electricity markets that have recently undergone this transition have exhibited extremely unsatisfactory results, most notably in California. These high stakes transformations require the introduction of largely untested regulatory structures. Suitable tools that can be used to test these regulatory structures before they are applied to real systems are required. Multi-agent models can provide such tools. To better understand the requirements such as tool, a live electricity market simulation was created. This experience helped to shape the developmentmore » of the multi-agent Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices.« less

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.

Grounding language in action and perception: From cognitive agents to humanoid robots

NASA Astrophysics Data System (ADS)

Cangelosi, Angelo

2010-06-01

In this review we concentrate on a grounded approach to the modeling of cognition through the methodologies of cognitive agents and developmental robotics. This work will focus on the modeling of the evolutionary and developmental acquisition of linguistic capabilities based on the principles of symbol grounding. We review cognitive agent and developmental robotics models of the grounding of language to demonstrate their consistency with the empirical and theoretical evidence on language grounding and embodiment, and to reveal the benefits of such an approach in the design of linguistic capabilities in cognitive robotic agents. In particular, three different models will be discussed, where the complexity of the agent's sensorimotor and cognitive system gradually increases: from a multi-agent simulation of language evolution, to a simulated robotic agent model for symbol grounding transfer, to a model of language comprehension in the humanoid robot iCub. The review also discusses the benefits of the use of humanoid robotic platform, and specifically of the open source iCub platform, for the study of embodied cognition.

Application of SNMP on CATV

NASA Astrophysics Data System (ADS)

Huang, Hong-bin; Liu, Wei-ping; Chen, Shun-er; Zheng, Liming

2005-02-01

A new type of CATV network management system developed by universal MCU, which supports SNMP, is proposed in this paper. From the point of view in both hardware and software, the function and method of every modules inside the system, which include communications in the physical layer, protocol process, data process, and etc, are analyzed. In our design, the management system takes IP MAN as data transmission channel and every controlled object in the management structure has a SNMP agent. In the SNMP agent developed, there are four function modules, including physical layer communication module, protocol process module, internal data process module and MIB management module. In the paper, the structure and function of every module are designed and demonstrated while the related hardware circuit, software flow as well as the experimental results are tested. Furthermore, by introducing RTOS into the software programming, the universal MCU procedure can conducts such multi-thread management as fast Ethernet controller driving, TCP/IP process, serial port signal monitoring and so on, which greatly improves efficiency of CPU.

Deterministic Teleportation of Multi-qudit States in a Network via Various Probabilistic Channels

NASA Astrophysics Data System (ADS)

Zhang, Ti-Hang; Jiang, Min; Huang, Xu; Wan, Min

2014-04-01

In this paper, we present a generalized approach to faithfully teleport an unknown state of a multi-qudit system involving multi spatially remote agents via various probabilistic channels. In a quantum teleportation network, there are generally multi spatially remote relay agents between a sender and a distant receiver. With the assistance of the relay agents, it is possible to directly construct a deterministic channel between the sender and the distant receiver. In our scheme, different from previous probabilistic teleportation protocols, the integrity of the unknown multi-qudit state could be maintained even when the construction of faithful channel fails. Our results also show that the required auxiliary particle resources, local operations and classical communications are considerably reduced for the present purpose.

Multi-Agent simulation of generation capacity expansion decisions.

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

Botterud, A.; Mahalik, M.; Conzelmann, G.

2008-01-01

In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenariomore » analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.« less

Combining engineered cell-sensors with multi-agent systems to realize smart environment

NASA Astrophysics Data System (ADS)

Chen, Mei

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

NASA Astrophysics Data System (ADS)

Yang, Hong-Yong; Lu, Lan; Cao, Ke-Cai; Zhang, Si-Ying

2010-04-01

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Efficient Evaluation Functions for Multi-Rover Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2004-01-01

Evolutionary computation can be a powerful tool in cresting a control policy for a single agent receiving local continuous input. This paper extends single-agent evolutionary computation to multi-agent systems, where a collection of agents strives to maximize a global fitness evaluation function that rates the performance of the entire system. This problem is solved in a distributed manner, where each agent evolves its own population of neural networks that are used as the control policies for the agent. Each agent evolves its population using its own agent-specific fitness evaluation function. We propose to create these agent-specific evaluation functions using the theory of collectives to avoid the coordination problem where each agent evolves a population that maximizes its own fitness function, yet the system has a whole achieves low values of the global fitness function. Instead we will ensure that each fitness evaluation function is both "aligned" with the global evaluation function and is "learnable," i.e., the agents can readily see how their behavior affects their evaluation function. We then show how these agent-specific evaluation functions outperform global evaluation methods by up to 600% in a domain where a set of rovers attempt to maximize the amount of information observed while navigating through a simulated environment.

Learning Activity Models for Multiple Agents in a Smart Space

NASA Astrophysics Data System (ADS)

Crandall, Aaron; Cook, Diane J.

With the introduction of more complex intelligent environment systems, the possibilities for customizing system behavior have increased dramatically. Significant headway has been made in tracking individuals through spaces using wireless devices [1, 18, 26] and in recognizing activities within the space based on video data (see chapter by Brubaker et al. and [6, 8, 23]), motion sensor data [9, 25], wearable sensors [13] or other sources of information [14, 15, 22]. However, much of the theory and most of the algorithms are designed to handle one individual in the space at a time. Resident tracking, activity recognition, event prediction, and behavior automation becomes significantly more difficult for multi-agent situations, when there are multiple residents in the environment.

Consensus for second-order multi-agent systems with position sampled data

NASA Astrophysics Data System (ADS)

Wang, Rusheng; Gao, Lixin; Chen, Wenhai; Dai, Dameng

2016-10-01

In this paper, the consensus problem with position sampled data for second-order multi-agent systems is investigated. The interaction topology among the agents is depicted by a directed graph. The full-order and reduced-order observers with position sampled data are proposed, by which two kinds of sampled data-based consensus protocols are constructed. With the provided sampled protocols, the consensus convergence analysis of a continuous-time multi-agent system is equivalently transformed into that of a discrete-time system. Then, by using matrix theory and a sampled control analysis method, some sufficient and necessary consensus conditions based on the coupling parameters, spectrum of the Laplacian matrix and sampling period are obtained. While the sampling period tends to zero, our established necessary and sufficient conditions are degenerated to the continuous-time protocol case, which are consistent with the existing result for the continuous-time case. Finally, the effectiveness of our established results is illustrated by a simple simulation example. Project supported by the Natural Science Foundation of Zhejiang Province, China (Grant No. LY13F030005) and the National Natural Science Foundation of China (Grant No. 61501331).

Suitability of Agent Technology for Military Command and Control in the Future Combat System Environment

DTIC Science & Technology

2003-06-01

and Multi-Agent Systems 1 no. 1 (1998): 7-38. [23] K. Sycara, A. Pannu , M. Williamson, and D. Zeng, “Distributed Intelligent Agents,” IEEE Expert 11...services that include support for mobility, security, management, persistence, and naming of agents. [i] K. Sycara, A. Pannu , M. Williamson, and D

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

Multi-Agent Flight Simulation with Robust Situation Generation

NASA Technical Reports Server (NTRS)

Johnson, Eric N.; Hansman, R. John, Jr.

1994-01-01

A robust situation generation architecture has been developed that generates multi-agent situations for human subjects. An implementation of this architecture was developed to support flight simulation tests of air transport cockpit systems. This system maneuvers pseudo-aircraft relative to the human subject's aircraft, generating specific situations for the subject to respond to. These pseudo-aircraft maneuver within reasonable performance constraints, interact in a realistic manner, and make pre-recorded voice radio communications. Use of this system minimizes the need for human experimenters to control the pseudo-agents and provides consistent interactions between the subject and the pseudo-agents. The achieved robustness of this system to typical variations in the subject's flight path was explored. It was found to successfully generate specific situations within the performance limitations of the subject-aircraft, pseudo-aircraft, and the script used.

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 4 - Phase 1 Implementation of the Concept Demonstrator

NASA Technical Reports Server (NTRS)

Abbott, David; Batten, Adam; Carpenter, David; Dunlop, John; Edwards, Graeme; Farmer, Tony; Gaffney, Bruce; Hedley, Mark; Hoschke, Nigel; Isaacs, Peter;

Experience Using Formal Methods for Specifying a Multi-Agent System

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Rash, James; Hinchey, Michael; Szczur, Martha R. (Technical Monitor)

2000-01-01

The process and results of using formal methods to specify the Lights Out Ground Operations System (LOGOS) is presented in this paper. LOGOS is a prototype multi-agent system developed to show the feasibility of providing autonomy to satellite ground operations functions at NASA Goddard Space Flight Center (GSFC). After the initial implementation of LOGOS the development team decided to use formal methods to check for race conditions, deadlocks and omissions. The specification exercise revealed several omissions as well as race conditions. After completing the specification, the team concluded that certain tools would have made the specification process easier. This paper gives a sample specification of two of the agents in the LOGOS system and examples of omissions and race conditions found. It concludes with describing an architecture of tools that would better support the future specification of agents and other concurrent systems.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

NASA Astrophysics Data System (ADS)

Rahman, M. S.; Pota, H. R.; Mahmud, M. A.; Hossain, M. J.

2016-05-01

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Stationary average consensus protocol for a class of heterogeneous high-order multi-agent systems with application for aircraft

NASA Astrophysics Data System (ADS)

Rezaei, Mohammad Hadi; Menhaj, Mohammad Bagher

2018-01-01

This paper investigates the stationary average consensus problem for a class of heterogeneous-order multi-agent systems. The goal is to bring the positions of agents to the average of their initial positions while letting the other states converge to zero. To this end, three different consensus protocols are proposed. First, based on the auxiliary variables information among the agents under switching directed networks and state-feedback control, a protocol is proposed whereby all the agents achieve stationary average consensus. In the second and third protocols, by resorting to only measurements of relative positions of neighbouring agents under fixed balanced directed networks, two control frameworks are presented with two strategies based on state-feedback and output-feedback control. Finally, simulation results are given to illustrate the effectiveness of the proposed protocols.

Distributed Planning in a Mixed-Initiative Environment: Collaborative Technologies for Network Centric Operations

DTIC Science & Technology

2008-10-01

Agents in the DEEP architecture extend and use the Java Agent Development (JADE) framework. DEEP requires a distributed multi-agent system and a...framework to help simplify the implementation of this system. JADE was chosen because it is fully implemented in Java , and supports these requirements

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

NASA Astrophysics Data System (ADS)

Chen, Jiaxi; Li, Junmin

2018-02-01

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T-S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Agent Reward Shaping for Alleviating Traffic Congestion

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian

2006-01-01

Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

Evaluation of water security in Jordan using a multi-agent, hydroeconomic model: Initial model results from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Medellin-Azuara, J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.; Zhang, H.

2016-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for water policy evaluation in Jordan. Jordan ranks among the most water-scarce countries in the world, a situation exacerbated due to a recent influx of refugees escaping the ongoing civil war in neighboring Syria. The modular, multi-agent model is used to evaluate interventions for enhancing Jordan's water security, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the multi-agent model, we explicitly account for human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. Human agents are implemented as autonomous entities in the model that make decisions in relation to one another and in response to hydrologic and socioeconomic conditions. The integrated model is programmed in Python using Pynsim, a generalizable, open-source object-oriented software framework for modeling network-based water resource systems. The modeling time periods include historical (2006-2014) and future (present-2050) time spans. For the historical runs, the model performance is validated against historical data for several observations that reflect the interacting dynamics of both the hydrologic and human components of the system. A historical counterfactual scenario is also constructed to isolate and identify the impacts of the recent Syrian civil war and refugee crisis on Jordan's water system. For the future period, model runs are conducted to evaluate potential supply, demand, and institutional interventions over a wide range of plausible climate and socioeconomic scenarios. In addition, model sensitivity analysis is conducted revealing the hydrologic and human aspects of the system that most strongly influence water security outcomes, providing insight into coupled human-water system dynamics as well as priority areas of focus for continued model improvement.

Hybrid optical security system using photonic crystals and MEMS devices

NASA Astrophysics Data System (ADS)

Ciosek, Jerzy; Ostrowski, Roman

2017-10-01

An important issue in security systems is that of selection of the appropriate detectors or sensors, whose sensitivity guarantees functional reliability whilst avoiding false alarms. Modern technology enables the optimization of sensor systems, tailored to specific risk factors. In optical security systems, one of the safety parameters considered is the spectral range in which the excitation signal is associated with a risk factor. Advanced safety systems should be designed taking into consideration the possible occurrence of, often multiple, complex risk factors, which can be identified individually. The hazards of concern in this work are chemical warfare agents and toxic industrial compounds present in the forms of gases and aerosols. The proposed sensor solution is a hybrid optical system consisting of a multi-spectral structure of photonic crystals associated with a MEMS (Micro Electro-Mechanical System) resonator. The crystallographic structures of carbon present in graphene rings and graphenecarbon nanotube nanocomposites have properties which make them desirable for use in detectors. The advantage of this system is a multi-spectral sensitivity at the same time as narrow-band selectivity for the identification of risk factors. It is possible to design a system optimized for detecting specified types of risk factor from very complex signals.

Synchronization of multi-agent systems with metric-topological interactions.

PubMed

Wang, Lin; Chen, Guanrong

2016-09-01

A hybrid multi-agent systems model integrating the advantages of both metric interaction and topological interaction rules, called the metric-topological model, is developed. This model describes planar motions of mobile agents, where each agent can interact with all the agents within a circle of a constant radius, and can furthermore interact with some distant agents to reach a pre-assigned number of neighbors, if needed. Some sufficient conditions imposed only on system parameters and agent initial states are presented, which ensure achieving synchronization of the whole group of agents. It reveals the intrinsic relationships among the interaction range, the speed, the initial heading, and the density of the group. Moreover, robustness against variations of interaction range, density, and speed are investigated by comparing the motion patterns and performances of the hybrid metric-topological interaction model with the conventional metric-only and topological-only interaction models. Practically in all cases, the hybrid metric-topological interaction model has the best performance in the sense of achieving highest frequency of synchronization, fastest convergent rate, and smallest heading difference.

Bipartite flocking for multi-agent systems

NASA Astrophysics Data System (ADS)

Fan, Ming-Can; Zhang, Hai-Tao; Wang, Miaomiao

2014-09-01

This paper addresses the bipartite flock control problem where a multi-agent system splits into two clusters upon internal or external excitations. Using structurally balanced signed graph theory, LaSalle's invariance principle and Barbalat's Lemma, we prove that the proposed algorithm guarantees a bipartite flocking behavior. In each of the two disjoint clusters, all individuals move with the same direction. Meanwhile, every pair of agents in different clusters moves with opposite directions. Moreover, all agents in the two separated clusters approach a common velocity magnitude, and collision avoidance among all agents is ensured as well. Finally, the proposed bipartite flock control method is examined by numerical simulations. The bipartite flocking motion addressed by this paper has its references in both natural collective motions and human group behaviors such as predator-prey and panic escaping scenarios.

Swarming behaviors in multi-agent systems with nonlinear dynamics

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

Yu, Wenwu, E-mail: wenwuyu@gmail.com; School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001; Chen, Guanrong

2013-12-15

The dynamic analysis of a continuous-time multi-agent swarm model with nonlinear profiles is investigated in this paper. It is shown that, under mild conditions, all agents in a swarm can reach cohesion within a finite time, where the upper bounds of the cohesion are derived in terms of the parameters of the swarm model. The results are then generalized by considering stochastic noise and switching between nonlinear profiles. Furthermore, swarm models with limited sensing range inducing changing communication topologies and unbounded repulsive interactions between agents are studied by switching system and nonsmooth analysis. Here, the sensing range of each agentmore » is limited and the possibility of collision among nearby agents is high. Finally, simulation results are presented to demonstrate the validity of the theoretical analysis.« less

On deception detection in multi-agent systems and deception intent

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Li, Deqing; Yuan, Xiuqing

2008-04-01

Deception detection plays an important role in the military decision-making process, but detecting deception is a challenging task. The deception planning process involves a number of human factors. It is intent-driven where intentions are usually hidden or not easily observable. As a result, in order to detect deception, any adversary model must have the capability to capture the adversary's intent. This paper discusses deception detection in multi-agent systems and in adversary modeling. We examined psychological and cognitive science research on deception and implemented various theories of deception within our approach. First, in multi-agent expert systems, one detection method uses correlations between agents to predict reasonable opinions/responses of other agents (Santos & Johnson, 2004). We further explore this idea and present studies that show the impact of different factors on detection success rate. Second, from adversary modeling, our detection method focuses on inferring adversary intent. By combining deception "branches" with intent inference models, we can estimate an adversary's deceptive activities and at the same time enhance intent inference. Two major kinds of deceptions are developed in this approach in different fashions. Simulative deception attempts to find inconsistency in observables, while dissimulative deception emphasizes the inference of enemy intentions.

Finite-time containment control of perturbed multi-agent systems based on sliding-mode control

NASA Astrophysics Data System (ADS)

Yu, Di; Ji, Xiang Yang

2018-01-01

Aimed at faster convergence rate, this paper investigates finite-time containment control problem for second-order multi-agent systems with norm-bounded non-linear perturbation. When topology between the followers are strongly connected, the nonsingular fast terminal sliding-mode error is defined, corresponding discontinuous control protocol is designed and the appropriate value range of control parameter is obtained by applying finite-time stability analysis, so that the followers converge to and move along the desired trajectories within the convex hull formed by the leaders in finite time. Furthermore, on the basis of the sliding-mode error defined, the corresponding distributed continuous control protocols are investigated with fast exponential reaching law and double exponential reaching law, so as to make the followers move to the small neighbourhoods of their desired locations and keep within the dynamic convex hull formed by the leaders in finite time to achieve practical finite-time containment control. Meanwhile, we develop the faster control scheme according to comparison of the convergence rate of these two different reaching laws. Simulation examples are given to verify the correctness of theoretical results.

The sampled-data consensus of multi-agent systems with probabilistic time-varying delays and packet losses

NASA Astrophysics Data System (ADS)

Sui, Xin; Yang, Yongqing; Xu, Xianyun; Zhang, Shuai; Zhang, Lingzhong

2018-02-01

This paper investigates the consensus of multi-agent systems with probabilistic time-varying delays and packet losses via sampled-data control. On the one hand, a Bernoulli-distributed white sequence is employed to model random packet losses among agents. On the other hand, a switched system is used to describe packet dropouts in a deterministic way. Based on the special property of the Laplacian matrix, the consensus problem can be converted into a stabilization problem of a switched system with lower dimensions. Some mean square consensus criteria are derived in terms of constructing an appropriate Lyapunov function and using linear matrix inequalities (LMIs). Finally, two numerical examples are given to show the effectiveness of the proposed method.

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Efficient Agent-Based Models for Non-Genomic Evolution

NASA Technical Reports Server (NTRS)

Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

2006-01-01

Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

Formal Modeling of Multi-Agent Systems using the Pi-Calculus and Epistemic Logic

NASA Technical Reports Server (NTRS)

Rorie, Toinette; Esterline, Albert

1998-01-01

Multi-agent systems have become important recently in computer science, especially in artificial intelligence (AI). We allow a broad sense of agent, but require at least that an agent has some measure of autonomy and interacts with other agents via some kind of agent communication language. We are concerned in this paper with formal modeling of multi-agent systems, with emphasis on communication. We propose for this purpose to use the pi-calculus, an extension of the process algebra CCS. Although the literature on the pi-calculus refers to agents, the term is used there in the sense of a process in general. It is our contention, however, that viewing agents in the AI sense as agents in the pi-calculus sense affords significant formal insight. One formalism that has been applied to agents in the AI sense is epistemic logic, the logic of knowledge. The success of epistemic logic in computer science in general has come in large part from its ability to handle concepts of knowledge that apply to groups. We maintain that the pi-calculus affords a natural yet rigorous means by which groups that are significant to epistemic logic may be identified, encapsulated, structured into hierarchies, and restructured in a principled way. This paper is organized as follows: Section 2 introduces the pi-calculus; Section 3 takes a scenario from the classical paper on agent-oriented programming [Sh93] and translates it into a very simple subset of the n-calculus; Section 4 then shows how more sophisticated features of the pi-calculus may bc brought into play; Section 5 discusses how the pi-calculus may be used to define groups for epistemic logic; and Section 6 is the conclusion.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

PubMed Central

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

Team Formation in Partially Observable Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2004-01-01

Sets of multi-agent teams often need to maximize a global utility rating the performance of the entire system where a team cannot fully observe other teams agents. Such limited observability hinders team-members trying to pursue their team utilities to take actions that also help maximize the global utility. In this article, we show how team utilities can be used in partially observable systems. Furthermore, we show how team sizes can be manipulated to provide the best compromise between having easy to learn team utilities and having them aligned with the global utility, The results show that optimally sized teams in a partially observable environments outperform one team in a fully observable environment, by up to 30%.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

PubMed

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Performance Evaluation and Adaptability Research of Flowing Gel System Prepared with Re-injected Waste Water

NASA Astrophysics Data System (ADS)

Shi, Lei; You, Jing; Liu, Na; Liu, Xinmin; Wang, Zhiqiang; Zhang, Tiantian; Gu, Yi; Guo, Suzhen; Gao, Shanshan

2017-12-01

The crosslinking intensity and stability of flowing gel system prepared with re-injected waste water are seriously affected as the high salinity waste water contains a high concentration of Na+, Fe2+, S2-, Ca2+, etc. The influence of various ions on the flowing gel system can be reduced by increasing polymer concentration, adding new ferric ion stabilizing agent (MQ) and calcium ion eliminating agent (CW). The technique of profile controlling and oil-displacing is carried out in Chanan multi-purpose station, Chabei multi-purpose station and Chayi multi-purpose station of Huabei Oilfield. The flowing gel system is injected from 10 downflow wells and the 15 offsetting production wells have increased the yield by 1770 tons.

Towards a first implementation of the WLIMES approach in living system studies advancing the diagnostics and therapy in augmented personalized medicine.

PubMed

Simeonov, Plamen L

2017-12-01

The goal of this paper is to advance an extensible theory of living systems using an approach to biomathematics and biocomputation that suitably addresses self-organized, self-referential and anticipatory systems with multi-temporal multi-agents. Our first step is to provide foundations for modelling of emergent and evolving dynamic multi-level organic complexes and their sustentative processes in artificial and natural life systems. Main applications are in life sciences, medicine, ecology and astrobiology, as well as robotics, industrial automation, man-machine interface and creative design. Since 2011 over 100 scientists from a number of disciplines have been exploring a substantial set of theoretical frameworks for a comprehensive theory of life known as Integral Biomathics. That effort identified the need for a robust core model of organisms as dynamic wholes, using advanced and adequately computable mathematics. The work described here for that core combines the advantages of a situation and context aware multivalent computational logic for active self-organizing networks, Wandering Logic Intelligence (WLI), and a multi-scale dynamic category theory, Memory Evolutive Systems (MES), hence WLIMES. This is presented to the modeller via a formal augmented reality language as a first step towards practical modelling and simulation of multi-level living systems. Initial work focuses on the design and implementation of this visual language and calculus (VLC) and its graphical user interface. The results will be integrated within the current methodology and practices of theoretical biology and (personalized) medicine to deepen and to enhance the holistic understanding of life. Copyright © 2017 Elsevier B.V. All rights reserved.

Conserving analyst attention units: use of multi-agent software and CEP methods to assist information analysis

NASA Astrophysics Data System (ADS)

Rimland, Jeffrey; McNeese, Michael; Hall, David

2013-05-01

Although the capability of computer-based artificial intelligence techniques for decision-making and situational awareness has seen notable improvement over the last several decades, the current state-of-the-art still falls short of creating computer systems capable of autonomously making complex decisions and judgments in many domains where data is nuanced and accountability is high. However, there is a great deal of potential for hybrid systems in which software applications augment human capabilities by focusing the analyst's attention to relevant information elements based on both a priori knowledge of the analyst's goals and the processing/correlation of a series of data streams too numerous and heterogeneous for the analyst to digest without assistance. Researchers at Penn State University are exploring ways in which an information framework influenced by Klein's (Recognition Primed Decision) RPD model, Endsley's model of situational awareness, and the Joint Directors of Laboratories (JDL) data fusion process model can be implemented through a novel combination of Complex Event Processing (CEP) and Multi-Agent Software (MAS). Though originally designed for stock market and financial applications, the high performance data-driven nature of CEP techniques provide a natural compliment to the proven capabilities of MAS systems for modeling naturalistic decision-making, performing process adjudication, and optimizing networked processing and cognition via the use of "mobile agents." This paper addresses the challenges and opportunities of such a framework for augmenting human observational capability as well as enabling the ability to perform collaborative context-aware reasoning in both human teams and hybrid human / software agent teams.

Pricing strategy in a dual-channel and remanufacturing supply chain system

NASA Astrophysics Data System (ADS)

Jiang, Chengzhi; Xu, Feng; Sheng, Zhaohan

2010-07-01

This article addresses the pricing strategy problems in a supply chain system where the manufacturer sells original products and remanufactured products via indirect retailer channels and direct Internet channels. Due to the complexity of that system, agent technologies that provide a new way for analysing complex systems are used for modelling. Meanwhile, in order to reduce the computational load of searching procedure for optimal prices and profits, a learning search algorithm is designed and implemented within the multi-agent supply chain model. The simulation results show that the proposed model can find out optimal prices of original products and remanufactured products in both channels, which lead to optimal profits of the manufacturer and the retailer. It is also found that the optimal profits are increased by introducing direct channel and remanufacturing. Furthermore, the effect of customer preference, direct channel cost and remanufactured unit cost on optimal prices and profits are examined.

Convoy Protection under Multi-Threat Scenario

DTIC Science & Technology

2017-06-01

14. SUBJECT TERMS antisubmarine warfare, convoy protection, screening, design of experiments, agent-based simulation 15. NUMBER OF...46 5. Scenarios 33–36 (Red Submarine Tactic-2) ...............................46 IV. DESIGN OF EXPERIMENT...47 C. NEARLY ORTHOGONAL LATIN HYPERCUBE DESIGN ............51 V. DATA ANALYSIS

A Software Framework for Remote Patient Monitoring by Using Multi-Agent Systems Support.

PubMed

Fernandes, Chrystinne Oliveira; Lucena, Carlos José Pereira De

2017-03-27

Although there have been significant advances in network, hardware, and software technologies, the health care environment has not taken advantage of these developments to solve many of its inherent problems. Research activities in these 3 areas make it possible to apply advanced technologies to address many of these issues such as real-time monitoring of a large number of patients, particularly where a timely response is critical. The objective of this research was to design and develop innovative technological solutions to offer a more proactive and reliable medical care environment. The short-term and primary goal was to construct IoT4Health, a flexible software framework to generate a range of Internet of things (IoT) applications, containing components such as multi-agent systems that are designed to perform Remote Patient Monitoring (RPM) activities autonomously. An investigation into its full potential to conduct such patient monitoring activities in a more proactive way is an expected future step. A framework methodology was selected to evaluate whether the RPM domain had the potential to generate customized applications that could achieve the stated goal of being responsive and flexible within the RPM domain. As a proof of concept of the software framework's flexibility, 3 applications were developed with different implementations for each framework hot spot to demonstrate potential. Agents4Health was selected to illustrate the instantiation process and IoT4Health's operation. To develop more concrete indicators of the responsiveness of the simulated care environment, an experiment was conducted while Agents4Health was operating, to measure the number of delays incurred in monitoring the tasks performed by agents. IoT4Health's construction can be highlighted as our contribution to the development of eHealth solutions. As a software framework, IoT4Health offers extensibility points for the generation of applications. Applications can extend the framework in the following ways: identification, collection, storage, recovery, visualization, monitoring, anomalies detection, resource notification, and dynamic reconfiguration. Based on other outcomes involving observation of the resulting applications, it was noted that its design contributed toward more proactive patient monitoring. Through these experimental systems, anomalies were detected in real time, with agents sending notifications instantly to the health providers. We conclude that the cost-benefit of the construction of a more generic and complex system instead of a custom-made software system demonstrated the worth of the approach, making it possible to generate applications in this domain in a more timely fashion. ©Chrystinne Oliveira Fernandes, Carlos José Pereira De Lucena. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.03.2017.

Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

NASA Astrophysics Data System (ADS)

Patkin, M. L.; Rogachev, G. N.

2018-02-01

A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

DTIC Science & Technology

2010-06-01

artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning.

PubMed

Fernandez-Gauna, Borja; Etxeberria-Agiriano, Ismael; Graña, Manuel

2015-01-01

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.

Distributed optimization system and method

DOEpatents

Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.

2003-06-10

A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.

Distributed Optimization System

DOEpatents

Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.

2004-11-30

A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Integrated Biological Warfare Technology Platform (IBWTP). Intelligent Software Supporting Situation Awareness, Response, and Operations

DTIC Science & Technology

2007-01-01

15 4.2.3. Users of Systems for Combating Biological Warfare ................................ 16 4.2.4...21 4.3.1. Existing Biosurveillance Systems .............................................................. 22 4.3.2. Automatic Integration...74 6.4.4. Multi-Agent System Management System (MMS).................................... 75 6.4.5. Agent Glossary

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

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.

Adaptive consensus of scale-free multi-agent system by randomly selecting links

NASA Astrophysics Data System (ADS)

Mou, Jinping; Ge, Huafeng

2016-06-01

This paper investigates an adaptive consensus problem for distributed scale-free multi-agent systems (SFMASs) by randomly selecting links, where the degree of each node follows a power-law distribution. The randomly selecting links are based on the assumption that every agent decides to select links among its neighbours according to the received data with a certain probability. Accordingly, a novel consensus protocol with the range of the received data is developed, and each node updates its state according to the protocol. By the iterative method and Cauchy inequality, the theoretical analysis shows that all errors among agents converge to zero, and in the meanwhile, several criteria of consensus are obtained. One numerical example shows the reliability of the proposed methods.

Multi-Scale Behavioral Modeling and Analysis Promoting a Fundamental Understanding of Agent-Based System Design and Operation

DTIC Science & Technology

2007-03-01

Chains," Mathematics of Control, Signals, and Systems, vol. 3(1), pp. 1-29, 1990. [4] A . Arnold, J . A . Carrillo, and I. Gamba, "Low and High Field...Aronson, C. L. A ., and J . L. Vázquez, "Interfaces with a corner point in one- dimensional porous medium flow," Comm. Pure Appl. Math, vol. 38(4), pp. 375...K. Levin, "Damage analysis of fiber composites," Computer Methods in Applied Mechanics and Engineering. [10] K. S. Barber, A . Goel, T. J . Graser, T

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.

UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis

DTIC Science & Technology

2013-06-01

CRN Common Random Numbers CSV Comma Separated Values DoE Design of Experiment GLM Generalized Linear Model HVT High Value Target JAR Java ARchive JMF... Java Media Framework JRE Java runtime environment Mason Multi-Agent Simulator Of Networks MOE Measure Of Effectiveness MOP Measures Of Performance...with every set several times, and to write a CSV file with the results. Rather than scripting the agent behavior deterministically, the agents should

Output Consensus of Heterogeneous Linear Multi-Agent Systems by Distributed Event-Triggered/Self-Triggered Strategy.

PubMed

Hu, Wenfeng; Liu, Lu; Feng, Gang

2016-09-02

This paper addresses the output consensus problem of heterogeneous linear multi-agent systems. We first propose a novel distributed event-triggered control scheme. It is shown that, with the proposed control scheme, the output consensus problem can be solved if two matrix equations are satisfied. Then, we further propose a novel self-triggered control scheme, with which continuous monitoring is avoided. By introducing a fixed timer into both event- and self-triggered control schemes, Zeno behavior can be ruled out for each agent. The effectiveness of the event- and self-triggered control schemes is illustrated by an example.

Computation of the target state and feedback controls for time optimal consensus in multi-agent systems

NASA Astrophysics Data System (ADS)

Mulla, Ameer K.; Patil, Deepak U.; Chakraborty, Debraj

2018-02-01

N identical agents with bounded inputs aim to reach a common target state (consensus) in the minimum possible time. Algorithms for computing this time-optimal consensus point, the control law to be used by each agent and the time taken for the consensus to occur, are proposed. Two types of multi-agent systems are considered, namely (1) coupled single-integrator agents on a plane and, (2) double-integrator agents on a line. At the initial time instant, each agent is assumed to have access to the state information of all the other agents. An algorithm, using convexity of attainable sets and Helly's theorem, is proposed, to compute the final consensus target state and the minimum time to achieve this consensus. Further, parts of the computation are parallelised amongst the agents such that each agent has to perform computations of O(N2) run time complexity. Finally, local feedback time-optimal control laws are synthesised to drive each agent to the target point in minimum time. During this part of the operation, the controller for each agent uses measurements of only its own states and does not need to communicate with any neighbouring agents.

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

NASA Technical Reports Server (NTRS)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Grounding language in action and perception: from cognitive agents to humanoid robots.

PubMed

Cangelosi, Angelo

2010-06-01

In this review we concentrate on a grounded approach to the modeling of cognition through the methodologies of cognitive agents and developmental robotics. This work will focus on the modeling of the evolutionary and developmental acquisition of linguistic capabilities based on the principles of symbol grounding. We review cognitive agent and developmental robotics models of the grounding of language to demonstrate their consistency with the empirical and theoretical evidence on language grounding and embodiment, and to reveal the benefits of such an approach in the design of linguistic capabilities in cognitive robotic agents. In particular, three different models will be discussed, where the complexity of the agent's sensorimotor and cognitive system gradually increases: from a multi-agent simulation of language evolution, to a simulated robotic agent model for symbol grounding transfer, to a model of language comprehension in the humanoid robot iCub. The review also discusses the benefits of the use of humanoid robotic platform, and specifically of the open source iCub platform, for the study of embodied cognition. Copyright 2010 Elsevier B.V. All rights reserved.

Designing collective behavior in a termite-inspired robot construction team.

PubMed

Werfel, Justin; Petersen, Kirstin; Nagpal, Radhika

2014-02-14

Complex systems are characterized by many independent components whose low-level actions produce collective high-level results. Predicting high-level results given low-level rules is a key open challenge; the inverse problem, finding low-level rules that give specific outcomes, is in general still less understood. We present a multi-agent construction system inspired by mound-building termites, solving such an inverse problem. A user specifies a desired structure, and the system automatically generates low-level rules for independent climbing robots that guarantee production of that structure. Robots use only local sensing and coordinate their activity via the shared environment. We demonstrate the approach via a physical realization with three autonomous climbing robots limited to onboard sensing. This work advances the aim of engineering complex systems that achieve specific human-designed goals.

Application of agent-based system for bioprocess description and process improvement.

PubMed

Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

2010-01-01

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. Copyright 2009 American Institute of Chemical Engineers

pH-Sensitive stimulus-responsive nanocarriers for targeted delivery of therapeutic agents

PubMed Central

Karimi, Mahdi; Eslami, Masoud; Sahandi-Zangabad, Parham; Mirab, Fereshteh; Farajisafiloo, Negar; Shafaei, Zahra; Ghosh, Deepanjan; Bozorgomid, Mahnaz; Dashkhaneh, Fariba; Hamblin, Michael R.

2016-01-01

In recent years miscellaneous smart micro/nanosystems that respond to various exogenous/endogenous stimuli including temperature, magnetic/electric field, mechanical force, ultrasound/light irradiation, redox potentials, and biomolecule concentration have been developed for targeted delivery and release of encapsulated therapeutic agents such as drugs, genes, proteins, and metal ions specifically at their required site of action. Owing to physiological differences between malignant and normal cells, or between tumors and normal tissues, pH-sensitive nanosystems represent promising smart delivery vehicles for transport and delivery of anticancer agents. Furthermore, pH-sensitive systems possess applications in delivery of metal ions and biomolecules such as proteins, insulin, etc., as well as co-delivery of cargos, dual pH-sensitive nanocarriers, dual/multi stimuli-responsive nanosystems, and even in the search for new solutions for therapy of diseases such as Alzheimer’s. In order to design an optimized system, it is necessary to understand the various pH-responsive micro/nanoparticles and the different mechanisms of pH-sensitive drug release. This should be accompanied by an assessment of the theoretical and practical challenges in the design and use of these carriers. PMID:26762467

UPM: unified policy-based network management

NASA Astrophysics Data System (ADS)

Law, Eddie; Saxena, Achint

2001-07-01

Besides providing network management to the Internet, it has become essential to offer different Quality of Service (QoS) to users. Policy-based management provides control on network routers to achieve this goal. The Internet Engineering Task Force (IETF) has proposed a two-tier architecture whose implementation is based on the Common Open Policy Service (COPS) protocol and Lightweight Directory Access Protocol (LDAP). However, there are several limitations to this design such as scalability and cross-vendor hardware compatibility. To address these issues, we present a functionally enhanced multi-tier policy management architecture design in this paper. Several extensions are introduced thereby adding flexibility and scalability. In particular, an intermediate entity between the policy server and policy rule database called the Policy Enforcement Agent (PEA) is introduced. By keeping internal data in a common format, using a standard protocol, and by interpreting and translating request and decision messages from multi-vendor hardware, this agent allows a dynamic Unified Information Model throughout the architecture. We have tailor-made this unique information system to save policy rules in the directory server and allow executions of policy rules with dynamic addition of new equipment during run-time.

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.

Market-Based Coordination and Auditing Mechanisms for Self-Interested Multi-Robot Systems

ERIC Educational Resources Information Center

Ham, MyungJoo

2009-01-01

We propose market-based coordinated task allocation mechanisms, which allocate complex tasks that require synchronized and collaborated services of multiple robot agents to robot agents, and an auditing mechanism, which ensures proper behaviors of robot agents by verifying inter-agent activities, for self-interested, fully-distributed, and…

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.

Consensus for multi-agent systems with time-varying input delays

NASA Astrophysics Data System (ADS)

Yuan, Chengzhi; Wu, Fen

2017-10-01

This paper addresses the consensus control problem for linear multi-agent systems subject to uniform time-varying input delays and external disturbance. A novel state-feedback consensus protocol is proposed under the integral quadratic constraint (IQC) framework, which utilises not only the relative state information from neighbouring agents but also the real-time information of delays by means of the dynamic IQC system states for feedback control. Based on this new consensus protocol, the associated IQC-based control synthesis conditions are established and fully characterised as linear matrix inequalities (LMIs), such that the consensus control solution with optimal ? disturbance attenuation performance can be synthesised efficiently via convex optimisation. A numerical example is used to demonstrate the proposed approach.

A problem of optimal control and observation for distributed homogeneous multi-agent system

NASA Astrophysics Data System (ADS)

Kruglikov, Sergey V.

2017-12-01

The paper considers the implementation of a algorithm for controlling a distributed complex of several mobile multi-robots. The concept of a unified information space of the controlling system is applied. The presented information and mathematical models of participants and obstacles, as real agents, and goals and scenarios, as virtual agents, create the base forming the algorithmic and software background for computer decision support system. The controlling scheme assumes the indirect management of the robotic team on the basis of optimal control and observation problem predicting intellectual behavior in a dynamic, hostile environment. A basic content problem is a compound cargo transportation by a group of participants in the case of a distributed control scheme in the terrain with multiple obstacles.

Multi-agent planning and scheduling, execution monitoring and incremental rescheduling: Application to motorway traffic

NASA Technical Reports Server (NTRS)

Mourou, Pascal; Fade, Bernard

1992-01-01

This article describes a planning method applicable to agents with great perception and decision-making capabilities and the ability to communicate with other agents. Each agent has a task to fulfill allowing for the actions of other agents in its vicinity. Certain simultaneous actions may cause conflicts because they require the same resource. The agent plans each of its actions and simultaneously transmits these to its neighbors. In a similar way, it receives plans from the other agents and must take account of these plans. The planning method allows us to build a distributed scheduling system. Here, these agents are robot vehicles on a highway communicating by radio. In this environment, conflicts between agents concern the allocation of space in time and are connected with the inertia of the vehicles. Each vehicle made a temporal, spatial, and situated reasoning in order to drive without collision. The flexibility and reactivity of the method presented here allows the agent to generate its plan based on assumptions concerning the other agents and then check these assumptions progressively as plans are received from the other agents. A multi-agent execution monitoring of these plans can be done, using data generated during planning and the multi-agent decision-making algorithm described here. A selective backtrack allows us to perform incremental rescheduling.

Remote Data Retrieval for Bioinformatics Applications: An Agent Migration Approach

PubMed Central

Gao, Lei; Dai, Hua; Zhang, Tong-Liang; Chou, Kuo-Chen

2011-01-01

Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach. PMID:21701677

Towards Optimal Design of Cancer Nanomedicines: Multi-stage Nanoparticles for the Treatment of Solid Tumors.

PubMed

Stylianopoulos, Triantafyllos; Economides, Eva-Athena; Baish, James W; Fukumura, Dai; Jain, Rakesh K

2015-09-01

Conventional drug delivery systems for solid tumors are composed of a nano-carrier that releases its therapeutic load. These two-stage nanoparticles utilize the enhanced permeability and retention (EPR) effect to enable preferential delivery to tumor tissue. However, the size-dependency of the EPR, the limited penetration of nanoparticles into the tumor as well as the rapid binding of the particles or the released cytotoxic agents to cancer cells and stromal components inhibit the uniform distribution of the drug and the efficacy of the treatment. Here, we employ mathematical modeling to study the effect of particle size, drug release rate and binding affinity on the distribution and efficacy of nanoparticles to derive optimal design rules. Furthermore, we introduce a new multi-stage delivery system. The system consists of a 20-nm primary nanoparticle, which releases 5-nm secondary particles, which in turn release the chemotherapeutic drug. We found that tuning the drug release kinetics and binding affinities leads to improved delivery of the drug. Our results also indicate that multi-stage nanoparticles are superior over two-stage nano-carriers provided they have a faster drug release rate and for high binding affinity drugs. Furthermore, our results suggest that smaller nanoparticles achieve better treatment outcome.

Who acquires infection from whom and how? Disentangling multi-host and multi-mode transmission dynamics in the ‘elimination’ era

PubMed Central

Borlase, Anna; Rudge, James W.

2017-01-01

Multi-host infectious agents challenge our abilities to understand, predict and manage disease dynamics. Within this, many infectious agents are also able to use, simultaneously or sequentially, multiple modes of transmission. Furthermore, the relative importance of different host species and modes can itself be dynamic, with potential for switches and shifts in host range and/or transmission mode in response to changing selective pressures, such as those imposed by disease control interventions. The epidemiology of such multi-host, multi-mode infectious agents thereby can involve a multi-faceted community of definitive and intermediate/secondary hosts or vectors, often together with infectious stages in the environment, all of which may represent potential targets, as well as specific challenges, particularly where disease elimination is proposed. Here, we explore, focusing on examples from both human and animal pathogen systems, why and how we should aim to disentangle and quantify the relative importance of multi-host multi-mode infectious agent transmission dynamics under contrasting conditions, and ultimately, how this can be used to help achieve efficient and effective disease control. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289259

Devices development and techniques research for space life sciences

NASA Astrophysics Data System (ADS)

Zhang, A.; Liu, B.; Zheng, C.

The development process and the status quo of the devices and techniques for space life science in China and the main research results in this field achieved by Shanghai Institute of Technical Physics SITP CAS are reviewed concisely in this paper On the base of analyzing the requirements of devices and techniques for supporting space life science experiments and researches one designment idea of developing different intelligent modules with professional function standard interface and easy to be integrated into system is put forward and the realization method of the experiment system with intelligent distributed control based on the field bus are discussed in three hierarchies Typical sensing or control function cells with certain self-determination control data management and communication abilities are designed and developed which are called Intelligent Agents Digital hardware network system which are consisted of the distributed Agents as the intelligent node is constructed with the normative opening field bus technology The multitask and real-time control application softwares are developed in the embedded RTOS circumstance which is implanted into the system hardware and space life science experiment system platform with characteristic of multitasks multi-courses professional and instant integration will be constructed

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.

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

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.

Exchanging large data object in multi-agent systems

NASA Astrophysics Data System (ADS)

Al-Yaseen, Wathiq Laftah; Othman, Zulaiha Ali; Nazri, Mohd Zakree Ahmad

2016-08-01

One of the Business Intelligent solutions that is currently in use is the Multi-Agent System (MAS). Communication is one of the most important elements in MAS, especially for exchanging large low level data between distributed agents (physically). The Agent Communication Language in JADE has been offered as a secure method for sending data, whereby the data is defined as an object. However, the object cannot be used to send data to another agent in a different location. Therefore, the aim of this paper was to propose a method for the exchange of large low level data as an object by creating a proxy agent known as a Delivery Agent, which temporarily imitates the Receiver Agent. The results showed that the proposed method is able to send large-sized data. The experiments were conducted using 16 datasets ranging from 100,000 to 7 million instances. However, for the proposed method, the RAM and the CPU machine had to be slightly increased for the Receiver Agent, but the latency time was not significantly different compared to the use of the Java Socket method (non-agent and less secure). With such results, it was concluded that the proposed method can be used to securely send large data between agents.

Teamwork Reasoning and Multi-Satellite Missions

NASA Technical Reports Server (NTRS)

Marsella, Stacy C.; Plaunt, Christian (Technical Monitor)

2002-01-01

NASA is rapidly moving towards the use of spatially distributed multiple satellites operating in near Earth orbit and Deep Space. Effective operation of such multi-satellite constellations raises many key research issues. In particular, the satellites will be required to cooperate with each other as a team that must achieve common objectives with a high degree of autonomy from ground based operations. The multi-agent research community has made considerable progress in investigating the challenges of realizing such teamwork. In this report, we discuss some of the teamwork issues that will be faced by multi-satellite operations. The basis of the discussion is a particular proposed mission, the Magnetospheric MultiScale mission to explore Earth's magnetosphere. We describe this mission and then consider how multi-agent technologies might be applied in the design and operation of these missions. We consider the potential benefits of these technologies as well as the research challenges that will be raised in applying them to NASA multi-satellite missions. We conclude with some recommendations for future work.

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

PubMed

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

Decentralized Opportunistic Spectrum Resources Access Model and Algorithm toward Cooperative Ad-Hoc Networks.

PubMed

Liu, Ming; Xu, Yang; Mohammed, Abdul-Wahid

2016-01-01

Limited communication resources have gradually become a critical factor toward efficiency of decentralized large scale multi-agent coordination when both system scales up and tasks become more complex. In current researches, due to the agent's limited communication and observational capability, an agent in a decentralized setting can only choose a part of channels to access, but cannot perceive or share global information. Each agent's cooperative decision is based on the partial observation of the system state, and as such, uncertainty in the communication network is unavoidable. In this situation, it is a major challenge working out cooperative decision-making under uncertainty with only a partial observation of the environment. In this paper, we propose a decentralized approach that allows agents cooperatively search and independently choose channels. The key to our design is to build an up-to-date observation for each agent's view so that a local decision model is achievable in a large scale team coordination. We simplify the Dec-POMDP model problem, and each agent can jointly work out its communication policy in order to improve its local decision utilities for the choice of communication resources. Finally, we discuss an implicate resource competition game, and show that, there exists an approximate resources access tradeoff balance between agents. Based on this discovery, the tradeoff between real-time decision-making and the efficiency of cooperation using these channels can be well improved.

In vivo tumor characterization using both MR and optical contrast agents with a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Lin, Yuting; Ghijsen, Michael; Thayer, David; Nalcioglu, Orhan; Gulsen, Gultekin

2011-03-01

Dynamic contrast enhanced MRI (DCE-MRI) has been proven to be the most sensitive modality in detecting breast lesions. Currently available MR contrast agent, Gd-DTPA, is a low molecular weight extracellular agent and can diffuse freely from the vascular space into interstitial space. Due to this reason, DCE-MRI has low sensitivity in differentiating benign and malignant tumors. Meanwhile, diffuse optical tomography (DOT) can be used to provide enhancement kinetics of an FDA approved optical contrast agent, ICG, which behaves like a large molecular weight optical agent due to its binding to albumin. The enhancement kinetics of ICG may have a potential to distinguish between the malignant and benign tumors and hence improve the specificity. Our group has developed a high speed hybrid MRI-DOT system. The DOT is a fully automated, MR-compatible, multi-frequency and multi-spectral imaging system. Fischer-344 rats bearing subcutaneous R3230 tumor are injected simultaneously with Gd-DTPA (0.1nmol/kg) and IC-Green (2.5mg/kg). The enhancement kinetics of both contrast agents are recorded simultaneously with this hybrid MRI-DOT system and evaluated for different tumors.

Application of multi-agent coordination methods to the design of space debris mitigation tours

NASA Astrophysics Data System (ADS)

Stuart, Jeffrey; Howell, Kathleen; Wilson, Roby

2016-04-01

The growth in the number of defunct and fragmented objects near to the Earth poses a growing hazard to launch operations as well as existing on-orbit assets. Numerous studies have demonstrated the positive impact of active debris mitigation campaigns upon the growth of debris populations, but comparatively fewer investigations incorporate specific mission scenarios. Furthermore, while many active mitigation methods have been proposed, certain classes of debris objects are amenable to mitigation campaigns employing chaser spacecraft with existing chemical and low-thrust propulsive technologies. This investigation incorporates an ant colony optimization routing algorithm and multi-agent coordination via auctions into a debris mitigation tour scheme suitable for preliminary mission design and analysis as well as spacecraft flight operations.

Utilization and viability of biologically-inspired algorithms in a dynamic multiagent camera surveillance system

NASA Astrophysics Data System (ADS)

Mundhenk, Terrell N.; Dhavale, Nitin; Marmol, Salvador; Calleja, Elizabeth; Navalpakkam, Vidhya; Bellman, Kirstie; Landauer, Chris; Arbib, Michael A.; Itti, Laurent

2003-10-01

In view of the growing complexity of computational tasks and their design, we propose that certain interactive systems may be better designed by utilizing computational strategies based on the study of the human brain. Compared with current engineering paradigms, brain theory offers the promise of improved self-organization and adaptation to the current environment, freeing the programmer from having to address those issues in a procedural manner when designing and implementing large-scale complex systems. To advance this hypothesis, we discus a multi-agent surveillance system where 12 agent CPUs each with its own camera, compete and cooperate to monitor a large room. To cope with the overload of image data streaming from 12 cameras, we take inspiration from the primate"s visual system, which allows the animal to operate a real-time selection of the few most conspicuous locations in visual input. This is accomplished by having each camera agent utilize the bottom-up, saliency-based visual attention algorithm of Itti and Koch (Vision Research 2000;40(10-12):1489-1506) to scan the scene for objects of interest. Real time operation is achieved using a distributed version that runs on a 16-CPU Beowulf cluster composed of the agent computers. The algorithm guides cameras to track and monitor salient objects based on maps of color, orientation, intensity, and motion. To spread camera view points or create cooperation in monitoring highly salient targets, camera agents bias each other by increasing or decreasing the weight of different feature vectors in other cameras, using mechanisms similar to excitation and suppression that have been documented in electrophysiology, psychophysics and imaging studies of low-level visual processing. In addition, if cameras need to compete for computing resources, allocation of computational time is weighed based upon the history of each camera. A camera agent that has a history of seeing more salient targets is more likely to obtain computational resources. The system demonstrates the viability of biologically inspired systems in a real time tracking. In future work we plan on implementing additional biological mechanisms for cooperative management of both the sensor and processing resources in this system that include top down biasing for target specificity as well as novelty and the activity of the tracked object in relation to sensitive features of the environment.

Scientific and industrial challenges of developing nanoparticle-based theranostics and multiple-modality contrast agents for clinical application

NASA Astrophysics Data System (ADS)

Wáng, Yì Xiáng J.; Idée, Jean-Marc; Corot, Claire

2015-10-01

Designing of theranostics and dual or multi-modality contrast agents are currently two of the hottest topics in biotechnology and biomaterials science. However, for single entity theranostics, a right ratio of their diagnostic component and their therapeutic component may not always be realized in a composite suitable for clinical application. For dual/multiple modality molecular imaging agents, after in vivo administration, there is an optimal time window for imaging, when an agent is imaged by one modality, the pharmacokinetics of this agent may not allow imaging by another modality. Due to reticuloendothelial system clearance, efficient in vivo delivery of nanoparticles to the lesion site is sometimes difficult. The toxicity of these entities also remains poorly understood. While the medical need of theranostics is admitted, the business model remains to be established. There is an urgent need for a global and internationally harmonized re-evaluation of the approval and marketing processes of theranostics. However, a reasonable expectation exists that, in the near future, the current obstacles will be removed, thus allowing the wide use of these very promising agents.

A simplified building airflow model for agent concentration prediction.

PubMed

Jacques, David R; Smith, David A

2010-11-01

A simplified building airflow model is presented that can be used to predict the spread of a contaminant agent from a chemical or biological attack. If the dominant means of agent transport throughout the building is an air-handling system operating at steady-state, a linear time-invariant (LTI) model can be constructed to predict the concentration in any room of the building as a result of either an internal or external release. While the model does not capture weather-driven and other temperature-driven effects, it is suitable for concentration predictions under average daily conditions. The model is easily constructed using information that should be accessible to a building manager, supplemented with assumptions based on building codes and standard air-handling system design practices. The results of the model are compared with a popular multi-zone model for a simple building and are demonstrated for building examples containing one or more air-handling systems. The model can be used for rapid concentration prediction to support low-cost placement strategies for chemical and biological detection sensors.

Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Lewis, Michael; Sadik, Omowunmi; Wong, Lut; Wanekaya, Adam; Gonzalez, Richard J.; Balan, Arun

2004-04-01

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

Trivalent galactosyl-functionalized mesoporous silica nanoparticles as a target-specific delivery system for boron neutron capture therapy

NASA Astrophysics Data System (ADS)

Lai, Chian-Hui; Lai, Nien-Chu; Chuang, Yung-Jen; Chou, Fong-In; Yang, Chia-Min; Lin, Chun-Cheng

2013-09-01

A multi-functional mesoporous silica nanoparticle (MSN)-based boron neutron capture therapy (BNCT) agent, designated as T-Gal-B-Cy3@MSN, was synthesized with hydrophobic mesopores for incorporating a large amount of o-carborane (almost 60% (w/w) boron atoms per MSN), and the amines on the external surface were conjugated with trivalent galactosyl ligands and fluorescent dyes for cell targeting and imaging, respectively. The polar and hydrophilic galactosyl ligands enhance the water dispersibility of the BNCT agent and inhibit the possible leakage of o-carborane loaded in the MSN. Confocal microscopic images showed that T-Gal-B-Cy3@MSNs were endocytosed by cells and were then released from lysosomes into the cytoplasm of cells. Moreover, in comparison with the commonly used clinical BNCT agent, sodium borocaptate (BSH), T-Gal-B-Cy3@MSN provides a higher delivery efficiency (over 40-50 fold) of boron atoms and a better effect of BNCT in neutron irradiation experiments. MTT assays show a very low cytotoxicity for T-Gal-B-Cy3@MSN over a 2 h incubation time. The results are promising for the design of multifunctional MSNs as potential BNCT agents for clinical use.A multi-functional mesoporous silica nanoparticle (MSN)-based boron neutron capture therapy (BNCT) agent, designated as T-Gal-B-Cy3@MSN, was synthesized with hydrophobic mesopores for incorporating a large amount of o-carborane (almost 60% (w/w) boron atoms per MSN), and the amines on the external surface were conjugated with trivalent galactosyl ligands and fluorescent dyes for cell targeting and imaging, respectively. The polar and hydrophilic galactosyl ligands enhance the water dispersibility of the BNCT agent and inhibit the possible leakage of o-carborane loaded in the MSN. Confocal microscopic images showed that T-Gal-B-Cy3@MSNs were endocytosed by cells and were then released from lysosomes into the cytoplasm of cells. Moreover, in comparison with the commonly used clinical BNCT agent, sodium borocaptate (BSH), T-Gal-B-Cy3@MSN provides a higher delivery efficiency (over 40-50 fold) of boron atoms and a better effect of BNCT in neutron irradiation experiments. MTT assays show a very low cytotoxicity for T-Gal-B-Cy3@MSN over a 2 h incubation time. The results are promising for the design of multifunctional MSNs as potential BNCT agents for clinical use. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr02594b

Design and Engineering of a Multi-Target (Multiplex) DNA Simulant to Evaluate Nulceic Acid Based Assays for Detection of Biological Threat Agents

DTIC Science & Technology

2006-11-01

mallei , Burkholderia pseudomallei and Variola virus (smallpox virus). A chimera of 2040 bp was engineered to produce PCR amplicons of different sizes...potential bio-warfare use have been completely sequenced, B. mallei , the etiologic agent of glanders , and B. pseudomallei, causative agent of... Burkholderia mallei Nierman et al, 2004 Burkholderia pseudomallei Holden et al, 2004 Burkholderia thailandensis

Fault-tolerant Control of a Cyber-physical System

NASA Astrophysics Data System (ADS)

Roxana, Rusu-Both; Eva-Henrietta, Dulf

2017-10-01

Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

Distributed optimisation problem with communication delay and external disturbance

NASA Astrophysics Data System (ADS)

Tran, Ngoc-Tu; Xiao, Jiang-Wen; Wang, Yan-Wu; Yang, Wu

2017-12-01

This paper investigates the distributed optimisation problem for the multi-agent systems (MASs) with the simultaneous presence of external disturbance and the communication delay. To solve this problem, a two-step design scheme is introduced. In the first step, based on the internal model principle, the internal model term is constructed to compensate the disturbance asymptotically. In the second step, a distributed optimisation algorithm is designed to solve the distributed optimisation problem based on the MASs with the simultaneous presence of disturbance and communication delay. Moreover, in the proposed algorithm, each agent interacts with its neighbours through the connected topology and the delay occurs during the information exchange. By utilising Lyapunov-Krasovskii functional, the delay-dependent conditions are derived for both slowly and fast time-varying delay, respectively, to ensure the convergence of the algorithm to the optimal solution of the optimisation problem. Several numerical simulation examples are provided to illustrate the effectiveness of the theoretical results.

Contract Monitoring in Agent-Based Systems: Case Study

NASA Astrophysics Data System (ADS)

Hodík, Jiří; Vokřínek, Jiří; Jakob, Michal

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents’ actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

NASA Astrophysics Data System (ADS)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

Implementation of a Web-Based Collaborative Process Planning System

NASA Astrophysics Data System (ADS)

Wang, Huifen; Liu, Tingting; Qiao, Li; Huang, Shuangxi

Under the networked manufacturing environment, all phases of product manufacturing involving design, process planning, machining and assembling may be accomplished collaboratively by different enterprises, even different manufacturing stages of the same part may be finished collaboratively by different enterprises. Based on the self-developed networked manufacturing platform eCWS(e-Cooperative Work System), a multi-agent-based system framework for collaborative process planning is proposed. In accordance with requirements of collaborative process planning, share resources provided by cooperative enterprises in the course of collaboration are classified into seven classes. Then a reconfigurable and extendable resource object model is built. Decision-making strategy is also studied in this paper. Finally a collaborative process planning system e-CAPP is developed and applied. It provides strong support for distributed designers to collaboratively plan and optimize product process though network.

MIDAS: a practical Bayesian design for platform trials with molecularly targeted agents.

PubMed

Yuan, Ying; Guo, Beibei; Munsell, Mark; Lu, Karen; Jazaeri, Amir

2016-09-30

Recent success of immunotherapy and other targeted therapies in cancer treatment has led to an unprecedented surge in the number of novel therapeutic agents that need to be evaluated in clinical trials. Traditional phase II clinical trial designs were developed for evaluating one candidate treatment at a time and thus not efficient for this task. We propose a Bayesian phase II platform design, the multi-candidate iterative design with adaptive selection (MIDAS), which allows investigators to continuously screen a large number of candidate agents in an efficient and seamless fashion. MIDAS consists of one control arm, which contains a standard therapy as the control, and several experimental arms, which contain the experimental agents. Patients are adaptively randomized to the control and experimental agents based on their estimated efficacy. During the trial, we adaptively drop inefficacious or overly toxic agents and 'graduate' the promising agents from the trial to the next stage of development. Whenever an experimental agent graduates or is dropped, the corresponding arm opens immediately for testing the next available new agent. Simulation studies show that MIDAS substantially outperforms the conventional approach. The proposed design yields a significantly higher probability for identifying the promising agents and dropping the futile agents. In addition, MIDAS requires only one master protocol, which streamlines trial conduct and substantially decreases the overhead burden. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

MIDAS: A Practical Bayesian Design for Platform Trials with Molecularly Targeted Agents

PubMed Central

Yuan, Ying; Guo, Beibei; Munsell, Mark; Lu, Karen; Jazaeri, Amir

2016-01-01

Recent success of immunotherapy and other targeted therapies in cancer treatment has led to an unprecedented surge in the number of novel therapeutic agents that need to be evaluated in clinical trials. Traditional phase II clinical trial designs were developed for evaluating one candidate treatment at a time, and thus not efficient for this task. We propose a Bayesian phase II platform design, the Multi-candidate Iterative Design with Adaptive Selection (MIDAS), which allows investigators to continuously screen a large number of candidate agents in an efficient and seamless fashion. MIDAS consists of one control arm, which contains a standard therapy as the control, and several experimental arms, which contain the experimental agents. Patients are adaptively randomized to the control and experimental agents based on their estimated efficacy. During the trial, we adaptively drop inefficacious or overly toxic agents and “graduate” the promising agents from the trial to the next stage of development. Whenever an experimental agent graduates or is dropped, the corresponding arm opens immediately for testing the next available new agent. Simulation studies show that MIDAS substantially outperforms the conventional approach. The proposed design yields a significantly higher probability for identifying the promising agents and dropping the futile agents. In addition, MIDAS requires only one master protocol, which streamlines trial conduct and substantially decreases the overhead burden. PMID:27112322

Open Source Service Agent (OSSA) in the intelligence community's Open Source Architecture

NASA Technical Reports Server (NTRS)

Fiene, Bruce F.

1994-01-01

The Community Open Source Program Office (COSPO) has developed an architecture for the intelligence community's new Open Source Information System (OSIS). The architecture is a multi-phased program featuring connectivity, interoperability, and functionality. OSIS is based on a distributed architecture concept. The system is designed to function as a virtual entity. OSIS will be a restricted (non-public), user configured network employing Internet communications. Privacy and authentication will be provided through firewall protection. Connection to OSIS can be made through any server on the Internet or through dial-up modems provided the appropriate firewall authentication system is installed on the client.

Agent-based model for rural-urban migration: A dynamic consideration

NASA Astrophysics Data System (ADS)

Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

2015-10-01

This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Strategy Space Exploration of a Multi-Agent Model for the Labor Market

NASA Astrophysics Data System (ADS)

de Grande, Pablo; Eguia, Manuel

We present a multi-agent system where typical labor market mechanisms emerge. Based on a few simple rules, our model allows for different interpretative paradigms to be represented and for different scenarios to be tried out. We thoroughly explore the space of possible strategies both for those unemployed and for companies and analyze the trade-off between these strategies regarding global social and economical indicators.

Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

Non-fragile consensus algorithms for a network of diffusion PDEs with boundary local interaction

NASA Astrophysics Data System (ADS)

Xiong, Jun; Li, Junmin

2017-07-01

In this study, non-fragile consensus algorithm is proposed to solve the average consensus problem of a network of diffusion PDEs, modelled by boundary controlled heat equations. The problem deals with the case where the Neumann-type boundary controllers are corrupted by additive persistent disturbances. To achieve consensus between agents, a linear local interaction rule addressing this requirement is given. The proposed local interaction rules are analysed by applying a Lyapunov-based approach. The multiplicative and additive non-fragile feedback control algorithms are designed and sufficient conditions for the consensus of the multi-agent systems are presented in terms of linear matrix inequalities, respectively. Simulation results are presented to support the effectiveness of the proposed algorithms.

Optimal consensus algorithm integrated with obstacle avoidance

NASA Astrophysics Data System (ADS)

Wang, Jianan; Xin, Ming

2013-01-01

This article proposes a new consensus algorithm for the networked single-integrator systems in an obstacle-laden environment. A novel optimal control approach is utilised to achieve not only multi-agent consensus but also obstacle avoidance capability with minimised control efforts. Three cost functional components are defined to fulfil the respective tasks. In particular, an innovative nonquadratic obstacle avoidance cost function is constructed from an inverse optimal control perspective. The other two components are designed to ensure consensus and constrain the control effort. The asymptotic stability and optimality are proven. In addition, the distributed and analytical optimal control law only requires local information based on the communication topology to guarantee the proposed behaviours, rather than all agents' information. The consensus and obstacle avoidance are validated through simulations.

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Learning in engineered multi-agent systems

NASA Astrophysics Data System (ADS)

Menon, Anup

Consider the problem of maximizing the total power produced by a wind farm. Due to aerodynamic interactions between wind turbines, each turbine maximizing its individual power---as is the case in present-day wind farms---does not lead to optimal farm-level power capture. Further, there are no good models to capture the said aerodynamic interactions, rendering model based optimization techniques ineffective. Thus, model-free distributed algorithms are needed that help turbines adapt their power production on-line so as to maximize farm-level power capture. Motivated by such problems, the main focus of this dissertation is a distributed model-free optimization problem in the context of multi-agent systems. The set-up comprises of a fixed number of agents, each of which can pick an action and observe the value of its individual utility function. An individual's utility function may depend on the collective action taken by all agents. The exact functional form (or model) of the agent utility functions, however, are unknown; an agent can only measure the numeric value of its utility. The objective of the multi-agent system is to optimize the welfare function (i.e. sum of the individual utility functions). Such a collaborative task requires communications between agents and we allow for the possibility of such inter-agent communications. We also pay attention to the role played by the pattern of such information exchange on certain aspects of performance. We develop two algorithms to solve this problem. The first one, engineered Interactive Trial and Error Learning (eITEL) algorithm, is based on a line of work in the Learning in Games literature and applies when agent actions are drawn from finite sets. While in a model-free setting, we introduce a novel qualitative graph-theoretic framework to encode known directed interactions of the form "which agents' action affect which others' payoff" (interaction graph). We encode explicit inter-agent communications in a directed graph (communication graph) and, under certain conditions, prove convergence of agent joint action (under eITEL) to the welfare optimizing set. The main condition requires that the union of interaction and communication graphs be strongly connected; thus the algorithm combines an implicit form of communication (via interactions through utility functions) with explicit inter-agent communications to achieve the given collaborative goal. This work has kinship with certain evolutionary computation techniques such as Simulated Annealing; the algorithm steps are carefully designed such that it describes an ergodic Markov chain with a stationary distribution that has support over states where agent joint actions optimize the welfare function. The main analysis tool is perturbed Markov chains and results of broader interest regarding these are derived as well. The other algorithm, Collaborative Extremum Seeking (CES), uses techniques from extremum seeking control to solve the problem when agent actions are drawn from the set of real numbers. In this case, under the assumption of existence of a local minimizer for the welfare function and a connected undirected communication graph between agents, a result regarding convergence of joint action to a small neighborhood of a local optimizer of the welfare function is proved. Since extremum seeking control uses a simultaneous gradient estimation-descent scheme, gradient information available in the continuous action space formulation is exploited by the CES algorithm to yield improved convergence speeds. The effectiveness of this algorithm for the wind farm power maximization problem is evaluated via simulations. Lastly, we turn to a different question regarding role of the information exchange pattern on performance of distributed control systems by means of a case study for the vehicle platooning problem. In the vehicle platoon control problem, the objective is to design distributed control laws for individual vehicles in a platoon (or a road-train) that regulate inter-vehicle distances at a specified safe value while the entire platoon follows a leader-vehicle. While most of the literature on the problem deals with some inadequacy in control performance when the information exchange is of the nearest neighbor-type, we consider an arbitrary graph serving as information exchange pattern and derive a relationship between how a certain indicator of control performance is related to the information pattern. Such analysis helps in understanding qualitative features of the `right' information pattern for this problem.

A robotic system for researching social integration in honeybees.

PubMed

Griparić, Karlo; Haus, Tomislav; Miklić, Damjan; Polić, Marsela; Bogdan, Stjepan

2017-01-01

In this paper, we present a novel robotic system developed for researching collective social mechanisms in a biohybrid society of robots and honeybees. The potential for distributed coordination, as observed in nature in many different animal species, has caused an increased interest in collective behaviour research in recent years because of its applicability to a broad spectrum of technical systems requiring robust multi-agent control. One of the main problems is understanding the mechanisms driving the emergence of collective behaviour of social animals. With the aim of deepening the knowledge in this field, we have designed a multi-robot system capable of interacting with honeybees within an experimental arena. The final product, stationary autonomous robot units, designed by specificaly considering the physical, sensorimotor and behavioral characteristics of the honeybees (lat. Apis mallifera), are equipped with sensing, actuating, computation, and communication capabilities that enable the measurement of relevant environmental states, such as honeybee presence, and adequate response to the measurements by generating heat, vibration and airflow. The coordination among robots in the developed system is established using distributed controllers. The cooperation between the two different types of collective systems is realized by means of a consensus algorithm, enabling the honeybees and the robots to achieve a common objective. Presented results, obtained within ASSISIbf project, show successful cooperation indicating its potential for future applications.

Synthesis and evaluation of multi-wall carbon nanotube-paclitaxel complex as an anti-cancer agent.

PubMed

Ghasemvand, Fariba; Biazar, Esmaeil; Tavakolifard, Sara; Khaledian, Mohammad; Rahmanzadeh, Saeid; Momenzadeh, Daruosh; Afroosheh, Roshanak; Zarkalami, Faezeh; Shabannezhad, Marjan; Hesami Tackallou, Saeed; Massoudi, Nilofar; Heidari Keshel, Saeed

2016-01-01

The aim of this study was to design multi-walled carbon nanotubes (MWCNTs) loaded with paclitaxel (PTX) anti-cancer drug and investigate its anti-cancerous efficacy of human gastric cancer. Carbon nanotubes (CNTs) represent a novel nano-materials applied in various fields such as drug delivery due to their unique chemical properties and high drug loading. In this study, multi-walled carbon nanotubes (MWCNTs) pre-functionalized covalently with a paclitaxel (PTX) as an anti-cancer drug and evaluated by different analyses including, scanning electron microscope (SEM), particle size analyzer and cellular analyses. A well conjugated of anti-cancer drug on the carbon nanotube surfaces was shown. This study demonstrates that the MWCN-PTX complex is a potentially useful system for delivery of anti-cancer drugs. The flow cytometry, CFU and MTT assay results have disclosed that MWCNT/PTXs might promote apoptosis in MKN-45 gastric adenocarcinoma cell line. According to results, our simple method can be designed a candidate material for chemotherapy. It has presented a few bio-related applications including, their successful use as a nano-carriers for drug transport.

Distributed MPC based consensus for single-integrator multi-agent systems.

PubMed

Cheng, Zhaomeng; Fan, Ming-Can; Zhang, Hai-Tao

2015-09-01

This paper addresses model predictive control schemes for consensus in multi-agent systems (MASs) with discrete-time single-integrator dynamics under switching directed interaction graphs. The control horizon is extended to be greater than one which endows the closed-loop system with extra degree of freedom. We derive sufficient conditions on the sampling period and the interaction graph to achieve consensus by using the property of infinite products of stochastic matrices. Consensus can be achieved asymptotically if the sampling period is selected such that the interaction graph among agents has a directed spanning tree jointly. Significantly, if the interaction graph always has a spanning tree, one can select an arbitrary large sampling period to guarantee consensus. Finally, several simulations are conducted to illustrate the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Product Distribution Theory for Control of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Lee, Chia Fan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

HERA: A New Platform for Embedding Agents in Heterogeneous Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Alonso, Ricardo S.; de Paz, Juan F.; García, Óscar; Gil, Óscar; González, Angélica

Ambient Intelligence (AmI) based systems require the development of innovative solutions that integrate distributed intelligent systems with context-aware technologies. In this sense, Multi-Agent Systems (MAS) and Wireless Sensor Networks (WSN) are two key technologies for developing distributed systems based on AmI scenarios. This paper presents the new HERA (Hardware-Embedded Reactive Agents) platform, that allows using dynamic and self-adaptable heterogeneous WSNs on which agents are directly embedded on the wireless nodes This approach facilitates the inclusion of context-aware capabilities in AmI systems to gather data from their surrounding environments, achieving a higher level of ubiquitous and pervasive computing.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Multi-agent integrated password management (MIPM) application secured with encryption

NASA Astrophysics Data System (ADS)

Awang, Norkhushaini; Zukri, Nurul Hidayah Ahmad; Rashid, Nor Aimuni Md; Zulkifli, Zuhri Arafah; Nazri, Nor Afifah Mohd

2017-10-01

Users use weak passwords and reuse them on different websites and applications. Password managers are a solution to store login information for websites and help users log in automatically. This project developed a system that acts as an agent managing passwords. Multi-Agent Integrated Password Management (MIPM) is an application using encryption that provides users with secure storage of their login account information such as their username, emails and passwords. This project was developed on an Android platform with an encryption agent using Java Agent Development Environment (JADE). The purpose of the embedded agents is to act as a third-party software to ease the encryption process, and in the future, the developed encryption agents can form part of the security system. This application can be used by the computer and mobile users. Currently, users log into many applications causing them to use unique passwords to prevent password leaking. The crypto agent handles the encryption process using an Advanced Encryption Standard (AES) 128-bit encryption algorithm. As a whole, MIPM is developed on the Android application to provide a secure platform to store passwords and has high potential to be commercialised for public use.

A distributed model predictive control scheme for leader-follower multi-agent systems

NASA Astrophysics Data System (ADS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2018-02-01

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader-follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the 'better' control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.

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.

A Formal Characterization of Relevant Information in Multi-Agent Systems

DTIC Science & Technology

2009-10-01

Conference iTrust. (2004) [17] Sadek, D.: Le dialogue homme-machine : de l’ ergonomie des interfaces à l’ agent intelligent dia- loguant. In: Nouvelles interfaces hommemachine, Lavoisier Editeur, Arago 18 (1996) 277–321

Polysaccharide based nanogels in the drug delivery system: Application as the carrier of pharmaceutical agents.

PubMed

Debele, Tilahun Ayane; Mekuria, Shewaye Lakew; Tsai, Hsieh-Chih

2016-11-01

Polysaccharide-based nanoparticles have fascinated attention as a vesicle of different pharmaceutical agents due to their unique multi-functional groups in addition to their physicochemical properties, including biocompatibility and biodegradability. The existence of multi-functional groups on the polysaccharide backbone permits facile chemical or biochemical modification to synthesize polysaccharide based nanoparticles with miscellaneous structures. Polysaccharide-based nanogels have high water content, large surface area for multivalent bioconjugation, tunable size, and interior network for the incorporation of different pharmaceutical agents. These unique properties offer great potential for the utilization of polysaccharide-based nanogels in the drug delivery systems. Hence, this review describes chemistry of certain common polysaccharides, several methodologies used to synthesize polysaccharide nanoparticles and primarily focused on the polysaccharide (or polysaccharide derivative) based nanogels as the carrier of pharmaceutical agents. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Ultra-fast consensus of discrete-time multi-agent systems with multi-step predictive output feedback

NASA Astrophysics Data System (ADS)

Zhang, Wenle; Liu, Jianchang

2016-04-01

This article addresses the ultra-fast consensus problem of high-order discrete-time multi-agent systems based on a unified consensus framework. A novel multi-step predictive output mechanism is proposed under a directed communication topology containing a spanning tree. By predicting the outputs of a network several steps ahead and adding this information into the consensus protocol, it is shown that the asymptotic convergence factor is improved by a power of q + 1 compared to the routine consensus. The difficult problem of selecting the optimal control gain is solved well by introducing a variable called convergence step. In addition, the ultra-fast formation achievement is studied on the basis of this new consensus protocol. Finally, the ultra-fast consensus with respect to a reference model and robust consensus is discussed. Some simulations are performed to illustrate the effectiveness of the theoretical results.

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.

The distributed agent-based approach in the e-manufacturing environment

NASA Astrophysics Data System (ADS)

Sękala, A.; Kost, G.; Dobrzańska-Danikiewicz, A.; Banaś, W.; Foit, K.

2015-11-01

The deficiency of a coherent flow of information from a production department causes unplanned downtime and failures of machines and their equipment, which in turn results in production planning process based on incorrect and out-of-date information. All of these factors entail, as the consequence, the additional difficulties associated with the process of decision-making. They concern, among other, the coordination of components of a distributed system and providing the access to the required information, thereby generating unnecessary costs. The use of agent technology significantly speeds up the flow of information within the virtual enterprise. This paper includes the proposal of a multi-agent approach for the integration of processes within the virtual enterprise concept. The presented concept was elaborated to investigate the possible solutions of the ways of transmission of information in the production system taking into account the self-organization of constituent components. Thus it implicated the linking of the concept of multi-agent system with the system of managing the production information, based on the idea of e-manufacturing. The paper presents resulting scheme that should be the base for elaborating an informatics model of the target virtual system. The computer system itself is intended to be developed next.

Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

DTIC Science & Technology

2017-11-01

Finite State Machine ............................................... 21 9 Main Ontological Concepts for Representing Structure of a Multi -Agent...19 NetLogo Simulation of persistent surveillance of circular plume by 4 UAVs ........................36 20 Flocking Emergent Behaviors in Multi -UAV...Region) - Undesirable Group Formation ................................................................................... 40 24 Two UAVs Moving in

Layered Learning in Multi-Agent Systems

DTIC Science & Technology

1998-12-15

project almost from the beginning has tirelessly experimented with different robot architectures, always managing to pull things together and create...TEAM MEMBER AGENT ARCHITECTURE I " ! Midfielder, Left : • i ) ( ^ J Goalie , Center Home Coordinates Home Range Max Range Figure

Hybrid Compounds as Anti-infective Agents.

PubMed

Sbaraglini, María Laura; Talevi, Alan

2017-01-01

Hybrid drugs are multi-target chimeric chemicals combining two or more drugs or pharmacophores covalently linked in a single molecule. In the field of anti-infective agents, they have been proposed as a possible solution to drug resistance issues, presumably having a broader spectrum of activity and less probability of eliciting high level resistance linked to single gene product. Although less frequently explored, they could also be useful in the treatment of frequently occurring co-infections. Here, we overview recent advances in the field of hybrid antimicrobials. Furthermore, we discuss some cutting-edge approaches to face the development of designed multi-target agents in the era of omics and big data, namely analysis of gene signatures and multitask QSAR models. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

Biomedical data integration in computational drug design and bioinformatics.

PubMed

Seoane, Jose A; Aguiar-Pulido, Vanessa; Munteanu, Cristian R; Rivero, Daniel; Rabunal, Juan R; Dorado, Julian; Pazos, Alejandro

2013-03-01

In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.

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.

Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2016-05-01

We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.

Controllability of multi-agent systems with periodically switching topologies and switching leaders

NASA Astrophysics Data System (ADS)

Tian, Lingling; Zhao, Bin; Wang, Long

2018-05-01

This paper considers controllability of multi-agent systems with periodically switching topologies and switching leaders. The concept of m-periodic controllability is proposed, and a criterion for m-periodic controllability is established. The effect of the duration of subsystems on controllability is analysed by utilising a property of analytic functions. In addition, the influence of switching periods on controllability is investigated, and an algorithm is proposed to search for the fewest periods to ensure controllability. A necessary condition for m-periodic controllability is obtained from the perspective of eigenvectors of the subsystems' Laplacian matrices. For a system with switching leaders, it is proved that switching-leader controllability is equivalent to multiple-leader controllability. Furthermore, both the switching order and the tenure of agents being leaders have no effect on the controllability. Some examples are provided to illustrate the theoretical results.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

Event-triggered consensus tracking of multi-agent systems with Lur'e nonlinear dynamics

NASA Astrophysics Data System (ADS)

Huang, Na; Duan, Zhisheng; Wen, Guanghui; Zhao, Yu

2016-05-01

In this paper, distributed consensus tracking problem for networked Lur'e systems is investigated based on event-triggered information interactions. An event-triggered control algorithm is designed with the advantages of reducing controller update frequency and sensor energy consumption. By using tools of ?-procedure and Lyapunov functional method, some sufficient conditions are derived to guarantee that consensus tracking is achieved under a directed communication topology. Meanwhile, it is shown that Zeno behaviour of triggering time sequences is excluded for the proposed event-triggered rule. Finally, some numerical simulations on coupled Chua's circuits are performed to illustrate the effectiveness of the theoretical algorithms.

A game theory-reinforcement learning (GT-RL) method to develop optimal operation policies for multi-operator reservoir systems

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Hooshyar, Milad

2014-11-01

Reservoir systems with multiple operators can benefit from coordination of operation policies. To maximize the total benefit of these systems the literature has normally used the social planner's approach. Based on this approach operation decisions are optimized using a multi-objective optimization model with a compound system's objective. While the utility of the system can be increased this way, fair allocation of benefits among the operators remains challenging for the social planner who has to assign controversial weights to the system's beneficiaries and their objectives. Cooperative game theory provides an alternative framework for fair and efficient allocation of the incremental benefits of cooperation. To determine the fair and efficient utility shares of the beneficiaries, cooperative game theory solution methods consider the gains of each party in the status quo (non-cooperation) as well as what can be gained through the grand coalition (social planner's solution or full cooperation) and partial coalitions. Nevertheless, estimation of the benefits of different coalitions can be challenging in complex multi-beneficiary systems. Reinforcement learning can be used to address this challenge and determine the gains of the beneficiaries for different levels of cooperation, i.e., non-cooperation, partial cooperation, and full cooperation, providing the essential input for allocation based on cooperative game theory. This paper develops a game theory-reinforcement learning (GT-RL) method for determining the optimal operation policies in multi-operator multi-reservoir systems with respect to fairness and efficiency criteria. As the first step to underline the utility of the GT-RL method in solving complex multi-agent multi-reservoir problems without a need for developing compound objectives and weight assignment, the proposed method is applied to a hypothetical three-agent three-reservoir system.

Exploration of Force Transition in Stability Operations Using Multi-Agent Simulation

DTIC Science & Technology

2006-09-01

risk, mission failure risk, and time in the context of the operational threat environment. The Pythagoras Multi-Agent Simulation and Data Farming...NUMBER OF PAGES 173 14. SUBJECT TERMS Stability Operations, Peace Operations, Data Farming, Pythagoras , Agent- Based Model, Multi-Agent Simulation...the operational threat environment. The Pythagoras Multi-Agent Simulation and Data Farming techniques are used to investigate force-level

BTFS: The Border Trade Facilitation System

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

Phillips, L.R.

The author demonstrates the Border Trade Facilitation System (BTFS), an agent-based bilingual e-commerce system built to expedite the regulation, control, and execution of commercial trans-border shipments during the delivery phase. The system was built to serve maquila industries at the US/Mexican border. The BTFS uses foundation technology developed here at Sandia Laboratories' Advanced Information Systems Lab (AISL), including a distributed object substrate, a general-purpose agent development framework, dynamically generated agent-human interaction via the World-Wide Web, and a collaborative agent architecture. This technology is also the substrate for the Multi-Agent Simulation Management System (MASMAS) proposed for demonstration at this conference. Themore » BTFS executes authenticated transactions among agents performing open trading over the Internet. With the BTFS in place, one could conduct secure international transactions from any site with an Internet connection and a web browser. The BTFS is currently being evaluated for commercialization.« less

Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

PubMed Central

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

2007-01-01

The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

Agents in bioinformatics, computational and systems biology.

PubMed

Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael

2007-01-01

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Multi-Agent System for Recruiting Patients for Clinical Trials

DTIC Science & Technology

2014-05-01

between agents, i.e. the flow of information. To provide greater insight, the links are also anno - tated with example operations that occur through these...then to achieve a full system evaluation that explores the intricacies of the agents in in wild. 8. REFERENCES [1] L. B. Afrin, J . C. Oates, C. K...2003:16–20. [2] A. J . Butte, D. A. Weinstein, and I. S. Kohane. Enrolling patients into clinical trials faster using realtime recuiting. Proceedings

Distributed Processing System for Restoration of Electric Power Distribution Network Using Two-Layered Contract Net Protocol

NASA Astrophysics Data System (ADS)

Kodama, Yu; Hamagami, Tomoki

Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.

Data Aggregation in Multi-Agent Systems in the Presence of Hybrid Faults

ERIC Educational Resources Information Center

Srinivasan, Satish Mahadevan

2010-01-01

Data Aggregation (DA) is a set of functions that provide components of a distributed system access to global information for purposes of network management and user services. With the diverse new capabilities that networks can provide, applicability of DA is growing. DA is useful in dealing with multi-value domain information and often requires…

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Mean square consensus of leader-following multi-agent systems with measurement noises and time delays.

PubMed

Ren, Hongwei; Deng, Feiqi

2017-11-01

This paper investigates the mean square consensus problem of dynamical networks of leader-following multi-agent systems with measurement noises and time-varying delays. We consider that the fixed undirected communication topologies are connected. A neighbor-based tracking algorithm together with distributed estimators are presented. Using tools of algebraic graph theory and the Gronwall-Bellman-Halanay type inequality, we establish sufficient conditions to reach consensus in mean square sense via the proposed consensus protocols. Finally, a numerical simulation is provided to demonstrate the effectiveness of the obtained theoretical result. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Adaptive Multi-Agent Systems for Constrained Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Systems, methods and apparatus for developing and maintaining evolving systems with software product lines

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Rash, James L. (Inventor); Pena, Joaquin (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which an evolutionary system is managed and viewed as a software product line. In some embodiments, the core architecture is a relatively unchanging part of the system, and each version of the system is viewed as a product from the product line. Each software product is generated from the core architecture with some agent-based additions. The result may be a multi-agent system software product line.

A Mode of Combined ERP and KMS Knowledge Management System Construction

NASA Astrophysics Data System (ADS)

Yuena, Kang; Yangeng, Wen; Qun, Zhou

The core of ERP and knowledge management is quite similar; both will send appropriate knowledge (goods, funds) to the right people (position) at the right time. It is reasonable to believe that increase the knowledge management system in ERP will help companies achieve their goals better. This paper compares the concept of logical point of hall three-dimensional structure of the knowledge management system and the ERP in methodology level. And found they are very similar in the time dimension, logic dimension and knowledge dimension. This laid the basis of methodology in the simultaneous planning, implementation and applications. And then proposed a knowledge-based ERP Multi-Agent Management System Model. Finally, the paper described the process from planning to implementation of knowledge management ERP system with multi-Agent interaction and impact from three concepts, management thinking, software and system.

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

Hao, He; Lian, Jianming; Kalsi, Karanjit

The HVAC (Heating, Ventilation, and Air- Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of the neighboring zones. In this paper, we study a multi-agent based approach to model and control commercial building HVAC system for providing grid services. In the multi-agent system (MAS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregated airflow (and thus fan power)more » flexibility that the HVAC system can provide to the ancillary service market. Then, we propose a Nash-bargaining based airflow allocation strategy to track a dispatch signal (that is within the offered flexibility limit) while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition and average consensus. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than the centralized approaches especially when the system becomes larger and more complex.« less

Resolving Multi-Stakeholder Robustness Asymmetries in Coupled Agricultural and Urban Systems

NASA Astrophysics Data System (ADS)

Li, Yu; Giuliani, Matteo; Castelletti, Andrea; Reed, Patrick

2016-04-01

The evolving pressures from a changing climate and society are increasingly motivating decision support frameworks that consider the robustness of management actions across many possible futures. Focusing on robustness is helpful for investigating key vulnerabilities within current water systems and for identifying potential tradeoffs across candidate adaptation responses. To date, most robustness studies assume a social planner perspective by evaluating highly aggregated measures of system performance. This aggregate treatment of stakeholders does not explore the equity or intrinsic multi-stakeholder conflicts implicit to the system-wide measures of performance benefits and costs. The commonly present heterogeneity across complex management interests, however, may produce strong asymmetries for alternative adaptation options, designed to satisfy system-level targets. In this work, we advance traditional robustness decision frameworks by replacing the centralized social planner with a bottom-up, agent-based approach, where stakeholders are modeled as individuals, and represented as potentially self-interested agents. This agent-based model enables a more explicit exploration of the potential inequities and asymmetries in the distribution of the system-wide benefit. The approach is demonstrated by exploring the potential conflicts between urban flooding and agricultural production in the Lake Como system (Italy). Lake Como is a regulated lake that is operated to supply water to the downstream agricultural district (Muzza as the pilot study area in this work) composed of a set of farmers with heterogeneous characteristics in terms of water allocation, cropping patterns, and land properties. Supplying water to farmers increases the risk of floods along the lakeshore and therefore the system is operated based on the tradeoff between these two objectives. We generated an ensemble of co-varying climate and socio-economic conditions and evaluated the robustness of the current Lake Como system management as well as of possible adaptation options (e.g., improved irrigation efficiency or changes in the dam operating rules). Numerical results show that crops prices and costs are the main drivers of the simulated system failures when evaluated in terms of system-level expected profitability. Analysis conducted at the farmer-agent scale highlights alternatively that temperature and inflows are the critical drivers leading to failures. Finally, we show that the robustness of the considered adaptation options varies spatially, strongly influenced by stakeholders' context, the metrics used to define success, and the assumed preferences for reservoir operations in balancing urban flooding and agricultural productivity.

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.

Preparation and evaluation of novel metronidazole sustained release and floating matrix tablets.

PubMed

Asnaashari, Solmaz; Khoei, Nazaninossadat Seyed; Zarrintan, Mohammad Hosein; Adibkia, Khosro; Javadzadeh, Yousef

2011-08-01

In the present study, metronidazole was used for preparing floating dosage forms that are designed to retain in the stomach for a long time and have developed as a drug delivery system for better eradication of Helicobacter Pylori in peptic ulcer diseases. For this means, various formulations were designed using multi-factorial design. HPMC, psyllium and carbopol in different concentrations were used as floating agents, and sodium bicarbonate was added as a gas-forming agent. Hardness, friability, drug loading, floating ability and release profiles as well as kinetics of release were assessed. Formulations containing HPMC as filler showed prolonged lag times for buoyancy. Adding psyllium to these formulations had reduced relative lag times. Overall, selected formulations were able to float immediately and showed buoyancy for at least 8?h. Meanwhile, sustained profiles of drug release were also obtained. Kinetically, among the 10 assessed models, the release pattern of metronidazole from the tablets fitted best to Power law, Weibull and Higuchi models in respect overall to mean percentage error values of 3.8, 4.73 and 5.77, respectively, for calcium carbonate-based tablets and, 2.95, 6.39 and 3.9, respectively, for calcium silicate-based tablets. In general, these systems can float in the gastric condition and control the drug release from the tablets.

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.

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Formal Assurance for Cognitive Architecture Based Autonomous Agent

NASA Technical Reports Server (NTRS)

Bhattacharyya, Siddhartha; Eskridge, Thomas; Neogi, Natasha; Carvalho, Marco

2017-01-01

Autonomous systems are designed and deployed in different modeling paradigms. These environments focus on specific concepts in designing the system. We focus our effort in the use of cognitive architectures to design autonomous agents to collaborate with humans to accomplish tasks in a mission. Our research focuses on introducing formal assurance methods to verify the behavior of agents designed in Soar, by translating the agent to the formal verification environment Uppaal.

MFIRE-2: A Multi Agent System for Flow-Based Intrusion Detection Using Stochastic Search

DTIC Science & Technology

2012-03-01

attacks that are distributed in nature , but may not protect individual systems effectively without incurring large bandwidth penalties while collecting...system-level information to help prepare for more significant attacks. The type of information potentially revealed by footprinting includes account...key areas where MAS may be appropriate: • The environment is open, highly dynamic, uncertain, or complex • Agents are a natural metaphor—Many

The multi-queue model applied to random access protocol

NASA Astrophysics Data System (ADS)

Fan, Xinlong

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS)

NASA Astrophysics Data System (ADS)

Zhang, Zhong

In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.

Role of time in symbiotic systems

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

Agrawala, A.K.

1996-12-31

All systems have a dynamics which reflects the changes in the system in time and, therefore, have to maintain a notion of time, either explicitly or implicitly. Traditionally, the notion of time in constructed systems has been implicitly specified at design time through rigid structures such as sampled data systems which operate with a fixed time tick, feedback systems which are designed reflecting a fixed time scale for the dynamics of the system as well as the controller responses, etc. In biological systems, the sense of time is a key element but it is not rigidly structured, even though allmore » such systems have a clear notion of time. We define the notion of time in systems in terms of temporal locality, time scale and time horizon. Temporal locality gives the notion of the accuracy with which the system knows about the current time. Time scale reflects the scale indicating the smallest and the largest granularity considered. It also reflects the reaction time. The time horizon indicates the time beyond which the system considers to be distant future and may not take it into account in its actions. Note that the temporal locality, time scale and the time horizon may be different for different types of actions of a system, thereby permitting the system to use multiple notions of time concurrently. In multi agent systems each subsystem may have its own notion of time but when intentions take place a coordination is necessary. Such coordination requires that the notions of time for different agents of the system be consistent. Clearly, the consistency requirement in this case does not mean exactly identical but implies that different agents can coordinate their actions which must take place in time. When the actions only require a determinate ordering the required coordination is much less severe than the case requiring actions to take place at the same time.« less

Power system voltage stability and agent based distribution automation in smart grid

NASA Astrophysics Data System (ADS)

Nguyen, Cuong Phuc

2011-12-01

Our interconnected electric power system is presently facing many challenges that it was not originally designed and engineered to handle. The increased inter-area power transfers, aging infrastructure, and old technologies, have caused many problems including voltage instability, widespread blackouts, slow control response, among others. These problems have created an urgent need to transform the present electric power system to a highly stable, reliable, efficient, and self-healing electric power system of the future, which has been termed "smart grid". This dissertation begins with an investigation of voltage stability in bulk transmission networks. A new continuation power flow tool for studying the impacts of generator merit order based dispatch on inter-area transfer capability and static voltage stability is presented. The load demands are represented by lumped load models on the transmission system. While this representation is acceptable in traditional power system analysis, it may not be valid in the future smart grid where the distribution system will be integrated with intelligent and quick control capabilities to mitigate voltage problems before they propagate into the entire system. Therefore, before analyzing the operation of the whole smart grid, it is important to understand the distribution system first. The second part of this dissertation presents a new platform for studying and testing emerging technologies in advanced Distribution Automation (DA) within smart grids. Due to the key benefits over the traditional centralized approach, namely flexible deployment, scalability, and avoidance of single-point-of-failure, a new distributed approach is employed to design and develop all elements of the platform. A multi-agent system (MAS), which has the three key characteristics of autonomy, local view, and decentralization, is selected to implement the advanced DA functions. The intelligent agents utilize a communication network for cooperation and negotiation. Communication latency is modeled using a user-defined probability density function. Failure-tolerant communication strategies are developed for agent communications. Major elements of advanced DA are developed in a completely distributed way and successfully tested for several IEEE standard systems, including: Fault Detection, Location, Isolation, and Service Restoration (FLISR); Coordination of Distributed Energy Storage Systems (DES); Distributed Power Flow (DPF); Volt-VAR Control (VVC); and Loss Reduction (LR).

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

Giuliani, M.; Castelletti, A.; Reed, P. M.

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a synthetic case study, representing a Y-shaped system composed by two regulated lakes, whose releases merge just upstream of a city. Each reservoir is operated by an agent in order to prevent floods along the lake shores (local objective). However, the optimal operation of the reservoirs with respect to the local objectives is conflicting with the minimization of floods in the city (global objective). The evolution of the Agent-based Model from individualistic management strategies of the reservoirs toward a global compromise that reduces the costs for the city is analysed.

Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

ERIC Educational Resources Information Center

Solomos, Konstantinos; Avouris, Nikolaos

1999-01-01

Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

Low Energy Technology. A Unit of Instruction in Housing and Home Environment. Single Family Homes--Multi-Family Homes--Mobile Homes.

ERIC Educational Resources Information Center

Beaulieu, Barbara; And Others

This unit of instruction on selection and living styles for energy conservation in single-family and multi-family housing and mobile homes was designed for use by home economics teachers in Florida high schools and by home economics extension agents as they work with their clientele. It is one of a series of 11 instructional units (see note)…

Multi-level functionality of social media in the aftermath of the Great East Japan Earthquake.

PubMed

Jung, Joo-Young; Moro, Munehito

2014-07-01

This study examines the multi-level functionalities of social media in the aftermath of the Great East Japan Earthquake of 11 March 2011. Based on a conceptual model of multi-level story flows of social media (Jung and Moro, 2012), the study analyses the multiple functionalities that were ascribed to social media by individuals, organisations, and macro-level social systems (government and the mass media) after the earthquake. Based on survey data, a review of Twitter timelines and secondary sources, the authors derive five functionalities of social media: interpersonal communications with others (micro level); channels for local governments; organisations and local media (meso level); channels for mass media (macro level); information sharing and gathering (cross level); and direct channels between micro-/meso- and macro-level agents. The study sheds light on the future potential of social media in disaster situations and suggests how to design an effective communication network to prepare for emergency situations. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

PubMed

Belem, Mahamadou; Saqalli, Mehdi

2017-11-01

This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

The Next Generation of Interoperability Agents in Healthcare

PubMed Central

Cardoso, Luciana; Marins, Fernando; Portela, Filipe; Santos, Manuel ; Abelha, António; Machado, José

2014-01-01

Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA. PMID:24840351

A New Multi-Agent Approach to Adaptive E-Education

NASA Astrophysics Data System (ADS)

Chen, Jing; Cheng, Peng

Improving customer satisfaction degree is important in e-Education. This paper describes a new approach to adaptive e-Education taking into account the full spectrum of Web service techniques and activities. It presents a multi-agents architecture based on artificial psychology techniques, which makes the e-Education process both adaptable and dynamic, and hence up-to-date. Knowledge base techniques are used to support the e-Education process, and artificial psychology techniques to deal with user psychology, which makes the e-Education system more effective and satisfying.

An architecture and protocol for communications satellite constellations regarded as multi-agent systems

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1995-01-01

This paper presents an architecture for satellites regarded as intercommunicating agents. The architecture is based upon a postmodern paradigm of artificial intelligence in which represented knowledge is regarded as text, inference procedures are regarded as social discourse and decision making conventions and the semantics of representations are grounded in the situated behaviour and activity of agents. A particular protocol is described for agent participation in distributed search and retrieval operations conducted as joint activities.

Physical insights into the blood-brain barrier translocation mechanisms

NASA Astrophysics Data System (ADS)

Theodorakis, Panagiotis E.; Müller, Erich A.; Craster, Richard V.; Matar, Omar K.

2017-08-01

The number of individuals suffering from diseases of the central nervous system (CNS) is growing with an aging population. While candidate drugs for many of these diseases are available, most of these pharmaceutical agents cannot reach the brain rendering most of the drug therapies that target the CNS inefficient. The reason is the blood-brain barrier (BBB), a complex and dynamic interface that controls the influx and efflux of substances through a number of different translocation mechanisms. Here, we present these mechanisms providing, also, the necessary background related to the morphology and various characteristics of the BBB. Moreover, we discuss various numerical and simulation approaches used to study the BBB, and possible future directions based on multi-scale methods. We anticipate that this review will motivate multi-disciplinary research on the BBB aiming at the design of effective drug therapies.

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.

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

PubMed

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.

Design, synthesis, and biological evaluation of a novel series of quercetin diacylglucosides as potent anti-MRSA and anti-VRE agents.

PubMed

Hossion, Abugafar M L; Otsuka, Nao; Kandahary, Rafiya K; Tsuchiya, Tomofusa; Ogawa, Wakano; Iwado, Akimasa; Zamami, Yoshito; Sasaki, Kenji

2010-09-01

A series of novel quercetin diacylglucosides were designed and first synthesized by Steglich esterification on the basis of MRSA strains inhibiting natural compound A. The in vitro inhibition of different multi-drug resistant bacterial strains and Escherichia coli DNA gyrase B was investigated. In the series, compound 10h was up to 128-fold more potent against vancomycin-resistant enterococci and more effective than A, which represents a promising new candidate as a potent anti-MRSA and anti-VRE agent. Copyright 2010. Published by Elsevier Ltd.

Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Clustering recommendations to compute agent reputation

NASA Astrophysics Data System (ADS)

Bedi, Punam; Kaur, Harmeet

2005-03-01

Traditional centralized approaches to security are difficult to apply to multi-agent systems which are used nowadays in e-commerce applications. Developing a notion of trust that is based on the reputation of an agent can provide a softer notion of security that is sufficient for many multi-agent applications. Our paper proposes a mechanism for computing reputation of the trustee agent for use by the trustier agent. The trustier agent computes the reputation based on its own experience as well as the experience the peer agents have with the trustee agents. The trustier agents intentionally interact with the peer agents to get their experience information in the form of recommendations. We have also considered the case of unintentional encounters between the referee agents and the trustee agent, which can be directly between them or indirectly through a set of interacting agents. The clustering is done to filter off the noise in the recommendations in the form of outliers. The trustier agent clusters the recommendations received from referee agents on the basis of the distances between recommendations using the hierarchical agglomerative method. The dendogram hence obtained is cut at the required similarity level which restricts the maximum distance between any two recommendations within a cluster. The cluster with maximum number of elements denotes the views of the majority of recommenders. The center of this cluster represents the reputation of the trustee agent which can be computed using c-means algorithm.

Heterogeneous Multi-Robot Cooperation

DTIC Science & Technology

1994-02-01

1992a) Maja Mataric. Designing emergent behaviors: From local interac- tions to collective intelligence. In J. Meyer, H. Roitblat , and S. Wilson, editors...1992] Lynne E. Parker. Adaptive action selection for cooperative agent teams. In Jean-Arcady Meyer, Herbert Roitblat . and Stewart Wilson. editors

A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization.

PubMed

Zhai, Zhaoyu; Martínez Ortega, José-Fernán; Lucas Martínez, Néstor; Rodríguez-Molina, Jesús

2018-06-02

As the demand for food grows continuously, intelligent agriculture has drawn much attention due to its capability of producing great quantities of food efficiently. The main purpose of intelligent agriculture is to plan agricultural missions properly and use limited resources reasonably with minor human intervention. This paper proposes a Precision Farming System (PFS) as a Multi-Agent System (MAS). Components of PFS are treated as agents with different functionalities. These agents could form several coalitions to complete the complex agricultural missions cooperatively. In PFS, mission planning should consider several criteria, like expected benefit, energy consumption or equipment loss. Hence, mission planning could be treated as a Multi-objective Optimization Problem (MOP). In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. A simulation, called precise pesticide spraying mission, is performed to verify the feasibility of the proposed approach. Simulation results illustrate that the proposed approach works properly. This approach enables the PFS to plan missions and allocate scarce resources efficiently. The theoretical analysis and simulation is a good foundation for the future study. Once the proposed approach is applied to a real scenario, it is expected to bring significant economic improvement.

Indirect synthesis of multi-degree of freedom transient systems. [linear programming for a kinematically linear system

NASA Technical Reports Server (NTRS)

Pilkey, W. D.; Chen, Y. H.

1974-01-01

An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.

Multi-sensor Navigation System Design

DOT National Transportation Integrated Search

1971-03-01

This report treats the design of naviggation systems that collect data from two or more on-board measurement subsystems and precess this data in an on-board computer. Such systems are called Multi-sensor Navigation Systems. : The design begins with t...

Networked Guidance and Control for Mobile Multi-Agent Systems: A Multi-terminal (Network) Information Theoretic Approach

DTIC Science & Technology

2012-01-19

time , i.e., the state of the system is the input delayed by one time unit. In contrast with classical approaches, here the control action must be a...Transactions on Automatic Control , Vol. 56, No. 9, September 2011, Pages 2013-2025 Consider a first order linear time -invariant discrete time system driven by...1, January 2010, Pages 175-179 Consider a discrete- time networked control system , in which the controller has direct access to noisy

Changing drug users' risk environments: peer health advocates as multi-level community change agents.

PubMed

Weeks, Margaret R; Convey, Mark; Dickson-Gomez, Julia; Li, Jianghong; Radda, Kim; Martinez, Maria; Robles, Eduardo

2009-06-01

Peer delivered, social oriented HIV prevention intervention designs are increasingly popular for addressing broader contexts of health risk beyond a focus on individual factors. Such interventions have the potential to affect multiple social levels of risk and change, including at the individual, network, and community levels, and reflect social ecological principles of interaction across social levels over time. The iterative and feedback dynamic generated by this multi-level effect increases the likelihood for sustained health improvement initiated by those trained to deliver the peer intervention. The Risk Avoidance Partnership (RAP), conducted with heroin and cocaine/crack users in Hartford, Connecticut, exemplified this intervention design and illustrated the multi-level effect on drug users' risk and harm reduction at the individual level, the social network level, and the larger community level. Implications of the RAP program for designing effective prevention programs and for analyzing long-term change to reduce HIV transmission among high-risk groups are discussed from this ecological and multi-level intervention perspective.

Design, Characterization, and Optimization of Controlled Drug Delivery System Containing Antibiotic Drug/s

PubMed Central

Shelate, Pragna; Dave, Divyang

2016-01-01

The objective of this work was design, characterization, and optimization of controlled drug delivery system containing antibiotic drug/s. Osmotic drug delivery system was chosen as controlled drug delivery system. The porous osmotic pump tablets were designed using Plackett-Burman and Box-Behnken factorial design to find out the best formulation. For screening of three categories of polymers, six independent variables were chosen for Plackett-Burman design. Osmotic agent sodium chloride and microcrystalline cellulose, pore forming agent sodium lauryl sulphate and sucrose, and coating agent ethyl cellulose and cellulose acetate were chosen as independent variables. Optimization of osmotic tablets was done by Box-Behnken design by selecting three independent variables. Osmotic agent sodium chloride, pore forming agent sodium lauryl sulphate, and coating agent cellulose acetate were chosen as independent variables. The result of Plackett-Burman and Box-Behnken design and ANOVA studies revealed that osmotic agent and pore former had significant effect on the drug release up to 12 hr. The observed independent variables were found to be very close to predicted values of most satisfactory formulation which demonstrates the feasibility of the optimization procedure in successful development of porous osmotic pump tablets containing antibiotic drug/s by using sodium chloride, sodium lauryl sulphate, and cellulose acetate as key excipients. PMID:27610247

Misreporting behaviour in iterated prisoner's dilemma game with combined trust strategy

NASA Astrophysics Data System (ADS)

Chen, Bo; Zhang, Bin; Wu, Hua-qing

2015-01-01

Effects of agents' misreporting behaviour on system cooperation are studied in a multi-agent iterated prisoner's dilemma game. Agents, adopting combined trust strategy (denoted by CTS) are classified into three groups, i.e., honest CTS, positive-reporting CTS and negative-reporting CTS. The differences of cooperation frequency and pay-off under three different systems, i.e., system only with honest CTS, system with honest CTS and positive-reporting CTS and system with honest CTS and negative-reporting CTS, are compared. Furthermore, we also investigate the effects of misreporting behaviour on an exploiter who adopts an exploiting strategy (denoted by EXPL) in a system with two CTSs and one EXPL. At last, numerical simulations are performed for understanding the effects of misreporting behaviour on CTS. The results reveal that positive-reporting behaviour can strengthen system cooperation, while negative-reporting behaviour cannot. When EXPL exists in a system, positive-reporting behaviour helps the exploiter in reducing its exploiting cost and encourages agents to adopt exploiting strategy, but hurts other agents' interests.

Multi-disciplinary coupling effects for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions which govern the accurate response of propulsion systems. Results are presented for propulsion system responses including multi-disciplinary coupling effects using coupled multi-discipline thermal, structural, and acoustic tailoring; an integrated system of multi-disciplinary simulators; coupled material behavior/fabrication process tailoring; sensitivities using a probabilistic simulator; and coupled materials, structures, fracture, and probabilistic behavior simulator. The results demonstrate that superior designs can be achieved if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated coupled multi-discipline numerical propulsion system simulator.

Argumentation and Game Theory

NASA Astrophysics Data System (ADS)

Rahwan, Iyad; Larson, Kate

In a large class of multi-agent systems, agents are self-interested in the sense that each agent is interested only in furthering its individual goals, which may or may not coincide with others’ goals. When such agents engage in argument, they would be expected to argue strategically in such a way that makes it more likely for their argumentative goals to be achieved. What we mean by arguing strategically is that instead of making arbitrary arguments, an agent would carefully choose its argumentative moves in order to further its own objectives.

Multi-Agent Patrolling under Uncertainty and Threats.

PubMed

Chen, Shaofei; Wu, Feng; Shen, Lincheng; Chen, Jing; Ramchurn, Sarvapali D

2015-01-01

We investigate a multi-agent patrolling problem where information is distributed alongside threats in environments with uncertainties. Specifically, the information and threat at each location are independently modelled as multi-state Markov chains, whose states are not observed until the location is visited by an agent. While agents will obtain information at a location, they may also suffer damage from the threat at that location. Therefore, the goal of the agents is to gather as much information as possible while mitigating the damage incurred. To address this challenge, we formulate the single-agent patrolling problem as a Partially Observable Markov Decision Process (POMDP) and propose a computationally efficient algorithm to solve this model. Building upon this, to compute patrols for multiple agents, the single-agent algorithm is extended for each agent with the aim of maximising its marginal contribution to the team. We empirically evaluate our algorithm on problems of multi-agent patrolling and show that it outperforms a baseline algorithm up to 44% for 10 agents and by 21% for 15 agents in large domains.

Modelling Agent-Environment Interaction in Multi-Agent Simulations with Affordances

DTIC Science & Technology

2010-04-01

allow operations analysts to conduct statistical studies comparing the effectiveness of different systems or tactics in different scenarios. 11 Instead of...in a Monte-Carlo batch mode, producing statistical outcomes for particular measures of effectiveness. They typically also run at many times faster...Combined with annotated signs, the affordances allowed the traveller agents to find their way around the virtual airport and to conduct their business

Open multi-agent control architecture to support virtual-reality-based man-machine interfaces

NASA Astrophysics Data System (ADS)

Freund, Eckhard; Rossmann, Juergen; Brasch, Marcel

2001-10-01

Projective Virtual Reality is a new and promising approach to intuitively operable man machine interfaces for the commanding and supervision of complex automation systems. The user interface part of Projective Virtual Reality heavily builds on latest Virtual Reality techniques, a task deduction component and automatic action planning capabilities. In order to realize man machine interfaces for complex applications, not only the Virtual Reality part has to be considered but also the capabilities of the underlying robot and automation controller are of great importance. This paper presents a control architecture that has proved to be an ideal basis for the realization of complex robotic and automation systems that are controlled by Virtual Reality based man machine interfaces. The architecture does not just provide a well suited framework for the real-time control of a multi robot system but also supports Virtual Reality metaphors and augmentations which facilitate the user's job to command and supervise a complex system. The developed control architecture has already been used for a number of applications. Its capability to integrate sensor information from sensors of different levels of abstraction in real-time helps to make the realized automation system very responsive to real world changes. In this paper, the architecture will be described comprehensively, its main building blocks will be discussed and one realization that is built based on an open source real-time operating system will be presented. The software design and the features of the architecture which make it generally applicable to the distributed control of automation agents in real world applications will be explained. Furthermore its application to the commanding and control of experiments in the Columbus space laboratory, the European contribution to the International Space Station (ISS), is only one example which will be described.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Apoptosis and Self-Destruct: A Contribution to Autonomic Agents?

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2004-01-01

Autonomic Computing (AC), a self-managing systems initiative based on the biological metaphor of the autonomic nervous system, is increasingly gaining momentum as the way forward in designing reliable systems. Agent technologies have been identified as a key enabler for engineering autonomicity in systems, both in terms of retrofitting autonomicity into legacy systems and designing new systems. The AC initiative provides an opportunity to consider other biological systems and principles in seeking new design strategies. This paper reports on one such investigation; utilizing the apoptosis metaphor of biological systems to provide a dynamic health indicator signal between autonomic agents.

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

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.

A Multi-Level Model of Information Seeking in the Clinical Domain

PubMed Central

Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.

2008-01-01

Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an automated information retrieval system that uses an intelligent search agent to bridge clinician information needs and human search expertise. PMID:18006383

Agent-Based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

NASA Astrophysics Data System (ADS)

Faroqi, H.; Mesgari, M.-S.

2015-12-01

During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

HSA-based multi-target combination therapy: regulating drugs' release from HSA and overcoming single drug resistance in a breast cancer model.

PubMed

Gou, Yi; Zhang, Zhenlei; Li, Dongyang; Zhao, Lei; Cai, Meiling; Sun, Zhewen; Li, Yongping; Zhang, Yao; Khan, Hamid; Sun, Hongbing; Wang, Tao; Liang, Hong; Yang, Feng

2018-11-01

Multi-drug delivery systems, which may be promising solution to overcome obstacles, have limited the clinical success of multi-drug combination therapies to treat cancer. To this end, we used three different anticancer agents, Cu(BpT)Br, NAMI-A, and doxorubicin (DOX), to build human serum albumin (HSA)-based multi-drug delivery systems in a breast cancer model to investigate the therapeutic efficacy of overcoming single drug (DOX) resistance to cancer cells in vivo, and to regulate the drugs' release from HSA. The HSA complex structure revealed that NAMI-A and Cu(BpT)Br bind to the IB and IIA sub-domain of HSA by N-donor residue replacing a leaving group and coordinating to their metal centers, respectively. The MALDI-TOF mass spectra demonstrated that one DOX molecule is conjugated with lysine of HSA by a pH-sensitive linker. Furthermore, the release behavior of three agents form HSA can be regulated at different pH levels. Importantly, in vivo results revealed that the HSA-NAMI-A-Cu(BpT)Br-DOX complex not only increases the targeting ability compared with a combination of the three agents (the NAMI-A/Cu(BpT)Br/DOX mixture), but it also overcomes DOX resistance to drug-resistant breast cancer cell lines.

L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

NASA Technical Reports Server (NTRS)

Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

2010-01-01

This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

In Vivo Microdialysis and Electroencephalographic Activity in Freely Moving Guinea Pigs Exposed to Organophosphorus Nerve Agents Sarin and VX: Analysis of Acetylcholine and Glutamate

DTIC Science & Technology

2011-01-01

3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE In vivo microdialysis and electroencephalographic activity in freely moving guinea pigs 5a...microdialysis and electroencephalographic activity in freely moving guinea pigs exposed to organophosphorus nerve agents sarin and VX: analysis of...brain seizure activity . This robust double multi- variate design provides greater fidelity when comparing data while also reducing the required number

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

NASA Astrophysics Data System (ADS)

Lu, Yanrong; Liao, Fucheng; Deng, Jiamei; Liu, Huiyang

2017-09-01

This paper investigates the cooperative global optimal preview tracking problem of linear multi-agent systems under the assumption that the output of a leader is a previewable periodic signal and the topology graph contains a directed spanning tree. First, a type of distributed internal model is introduced, and the cooperative preview tracking problem is converted to a global optimal regulation problem of an augmented system. Second, an optimal controller, which can guarantee the asymptotic stability of the augmented system, is obtained by means of the standard linear quadratic optimal preview control theory. Third, on the basis of proving the existence conditions of the controller, sufficient conditions are given for the original problem to be solvable, meanwhile a cooperative global optimal controller with error integral and preview compensation is derived. Finally, the validity of theoretical results is demonstrated by a numerical simulation.

Multi-disciplinary coupling for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions for determining the true response of propulsion systems. Results are presented for propulsion system responses including multi-discipline coupling effects via (1) coupled multi-discipline tailoring, (2) an integrated system of multidisciplinary simulators, (3) coupled material-behavior/fabrication-process tailoring, (4) sensitivities using a probabilistic simulator, and (5) coupled materials/structures/fracture/probabilistic behavior simulator. The results show that the best designs can be determined if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated interactive multi-discipline numerical propulsion system simulator.

Emergency response nurse scheduling with medical support robot by multi-agent and fuzzy technique.

PubMed

Kono, Shinya; Kitamura, Akira

2015-08-01

In this paper, a new co-operative re-scheduling method corresponding the medical support tasks that the time of occurrence can not be predicted is described, assuming robot can co-operate medical activities with the nurse. Here, Multi-Agent-System (MAS) is used for the co-operative re-scheduling, in which Fuzzy-Contract-Net (FCN) is applied to the robots task assignment for the emergency tasks. As the simulation results, it is confirmed that the re-scheduling results by the proposed method can keep the patients satisfaction and decrease the work load of the nurse.

A trust-based sensor allocation algorithm in cooperative space search problems

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

2011-06-01

Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

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.

A Bayesian multi-stage cost-effectiveness design for animal studies in stroke research

PubMed Central

Cai, Chunyan; Ning, Jing; Huang, Xuelin

2017-01-01

Much progress has been made in the area of adaptive designs for clinical trials. However, little has been done regarding adaptive designs to identify optimal treatment strategies in animal studies. Motivated by an animal study of a novel strategy for treating strokes, we propose a Bayesian multi-stage cost-effectiveness design to simultaneously identify the optimal dose and determine the therapeutic treatment window for administrating the experimental agent. We consider a non-monotonic pattern for the dose-schedule-efficacy relationship and develop an adaptive shrinkage algorithm to assign more cohorts to admissible strategies. We conduct simulation studies to evaluate the performance of the proposed design by comparing it with two standard designs. These simulation studies show that the proposed design yields a significantly higher probability of selecting the optimal strategy, while it is generally more efficient and practical in terms of resource usage. PMID:27405325

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

Design Multi-Sides System Unmanned Surface Vehicle (USV) Rocket

NASA Astrophysics Data System (ADS)

Syam, Rafiudin; Sutresman, Onny; Mappaita, Abdullah; Amiruddin; Wiranata, Ardi

2018-02-01

This study aims to design and test USV multislide forms. This system is excellent for maneuvering on the x-y-z coordinates. The disadvantage of a single side USV is that it is very difficult to maneuver to achieve very dynamic targets. While for multi sides system easily maneuvered though x-y-z coordinates. In addition to security defense purposes, multi-side system is also good for maritime intelligence, surveillance. In this case, electric deducted fan with Multi-Side system so that the vehicle can still operate even in reverse condition. Multipleside USV experiments have done with good results. In a USV study designed to use two propulsions.

Adaptive, Distributed Control of Constrained Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Multi-agent modelling framework for water, energy and other resource networks

NASA Astrophysics Data System (ADS)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be used to evaluate a multitude of topologies for identifying the optimal location of infrastructure investments. Pynsim is available on GitHub or via standard python installer packages such as pip. It comes with several examples and online documentation, making it attractive for those less experienced in software engineering.

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

PubMed

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

Mobile Agents: A Distributed Voice-Commanded Sensory and Robotic System for Surface EVA Assistance

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Alena, Rick; Crawford, Sekou; Dowding, John; Graham, Jeff; Kaskiris, Charis; Tyree, Kim S.; vanHoof, Ronnie

2003-01-01

A model-based, distributed architecture integrates diverse components in a system designed for lunar and planetary surface operations: spacesuit biosensors, cameras, GPS, and a robotic assistant. The system transmits data and assists communication between the extra-vehicular activity (EVA) astronauts, the crew in a local habitat, and a remote mission support team. Software processes ("agents"), implemented in a system called Brahms, run on multiple, mobile platforms, including the spacesuit backpacks, all-terrain vehicles, and robot. These "mobile agents" interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. Different types of agents relate platforms to each other ("proxy agents"), devices to software ("comm agents"), and people to the system ("personal agents"). A state-of-the-art spoken dialogue interface enables people to communicate with their personal agents, supporting a speech-driven navigation and scheduling tool, field observation record, and rover command system. An important aspect of the engineering methodology involves first simulating the entire hardware and software system in Brahms, and then configuring the agents into a runtime system. Design of mobile agent functionality has been based on ethnographic observation of scientists working in Mars analog settings in the High Canadian Arctic on Devon Island and the southeast Utah desert. The Mobile Agents system is developed iteratively in the context of use, with people doing authentic work. This paper provides a brief introduction to the architecture and emphasizes the method of empirical requirements analysis, through which observation, modeling, design, and testing are integrated in simulated EVA operations.

Multi-reactor power system configurations for multimegawatt nuclear electric propulsion

NASA Technical Reports Server (NTRS)

George, Jeffrey A.

1991-01-01

A modular, multi-reactor power system and vehicle configuration for piloted nuclear electric propulsion (NEP) missions to Mars is presented. Such a design could provide enhanced system and mission reliability, allowing a comfortable safety margin for early manned flights, and would allow a range of piloted and cargo missions to be performed with a single power system design. Early use of common power modules for cargo missions would also provide progressive flight experience and validation of standardized systems for use in later piloted applications. System and mission analysis are presented to compare single and multi-reactor configurations for piloted Mars missions. A conceptual design for the Hydra modular multi-reactor NEP vehicle is presented.

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow.

PubMed

Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow

PubMed Central

Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. PMID:28809957

MARS, a multi-agent system for assessing rowers' coordination via motion-based stigmergy.

PubMed

Avvenuti, Marco; Cesarini, Daniel; Cimino, Mario G C A

2013-09-12

A crucial aspect in rowing is having a synchronized, highly-efficient stroke. This is very difficult to obtain, due to the many interacting factors that each rower of the crew must perceive. Having a system that monitors and represents the crew coordination would be of great help to the coach during training sessions. In the literature, some methods already employ wireless sensors for capturing motion patterns that affect rowing performance. A challenging problem is to support the coach's decisions at his same level of knowledge, using a limited number of sensors and avoiding the complexity of the biomechanical analysis of human movements. In this paper, we present a multi-agent information-processing system for on-water measuring of both the overall crew asynchrony and the individual rower asynchrony towards the crew. More specifically, in the system, the first level of processing is managed by marking agents, which release marks in a sensing space, according to the rowers' motion. The accumulation of marks enables a stigmergic cooperation mechanism, generating collective marks, i.e., short-term memory structures in the sensing space. At the second level of processing, information provided by marks is observed by similarity agents, which associate a similarity degree with respect to optimal marks. Finally, the third level is managed by granulation agents, which extract asynchrony indicators for different purposes. The effectiveness of the system has been experimented on real-world scenarios. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and initial experimental setting.

MARS, a Multi-Agent System for Assessing Rowers' Coordination via Motion-Based Stigmergy

PubMed Central

Avvenuti, Marco; Cesarini, Daniel; Cimino, Mario G. C. A.

2013-01-01

A crucial aspect in rowing is having a synchronized, highly-efficient stroke. This is very difficult to obtain, due to the many interacting factors that each rower of the crew must perceive. Having a system that monitors and represents the crew coordination would be of great help to the coach during training sessions. In the literature, some methods already employ wireless sensors for capturing motion patterns that affect rowing performance. A challenging problem is to support the coach's decisions at his same level of knowledge, using a limited number of sensors and avoiding the complexity of the biomechanical analysis of human movements. In this paper, we present a multi-agent information-processing system for on-water measuring of both the overall crew asynchrony and the individual rower asynchrony towards the crew. More specifically, in the system, the first level of processing is managed by marking agents, which release marks in a sensing space, according to the rowers' motion. The accumulation of marks enables a stigmergic cooperation mechanism, generating collective marks, i.e., short-term memory structures in the sensing space. At the second level of processing, information provided by marks is observed by similarity agents, which associate a similarity degree with respect to optimal marks. Finally, the third level is managed by granulation agents, which extract asynchrony indicators for different purposes. The effectiveness of the system has been experimented on real-world scenarios. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and initial experimental setting. PMID:24036582

Can Moral Hazard Be Resolved by Common-Knowledge in S4n-Knowledge?

NASA Astrophysics Data System (ADS)

Matsuhisa, Takashi

This article investigates the relationship between common-knowledge and agreement in multi-agent system, and to apply the agreement result by common-knowledge to the principal-agent model under non-partition information. We treat the two problems: (1) how we capture the fact that the agents agree on an event or they get consensus on it from epistemic point of view, and (2) how the agreement theorem will be able to make progress to settle a moral hazard problem in the principal-agents model under non-partition information. We shall propose a solution program for the moral hazard in the principal-agents model under non-partition information by common-knowledge. Let us start that the agents have the knowledge structure induced from a reflexive and transitive relation associated with the multi-modal logic S4n. Each agent obtains the membership value of an event under his/her private information, so he/she considers the event as fuzzy set. Specifically consider the situation that the agents commonly know all membership values of the other agents. In this circumstance we shall show the agreement theorem that consensus on the membership values among all agents can still be guaranteed. Furthermore, under certain assumptions we shall show that the moral hazard can be resolved in the principal-agent model when all the expected marginal costs are common-knowledge among the principal and agents.

Modeling, Simulation, and Characterization of Distributed Multi-Agent Systems

DTIC Science & Technology

2012-01-01

capabilities (vision, LIDAR , differential global positioning, ultrasonic proximity sensing, etc.), the agents comprising a MAS tend to have somewhat lesser...on the simultaneous localization and mapping ( SLAM ) problem [19]. SLAM acknowledges that externally-provided localization information is not...continually-updated mapping databases, generates a comprehensive representation of the spatial and spectral environment. Many times though, inherent SLAM

Research into a distributed fault diagnosis system and its application

NASA Astrophysics Data System (ADS)

Qian, Suxiang; Jiao, Weidong; Lou, Yongjian; Shen, Xiaomei

2005-12-01

CORBA (Common Object Request Broker Architecture) is a solution to distributed computing methods over heterogeneity systems, which establishes a communication protocol between distributed objects. It takes great emphasis on realizing the interoperation between distributed objects. However, only after developing some application approaches and some practical technology in monitoring and diagnosis, can the customers share the monitoring and diagnosis information, so that the purpose of realizing remote multi-expert cooperation diagnosis online can be achieved. This paper aims at building an open fault monitoring and diagnosis platform combining CORBA, Web and agent. Heterogeneity diagnosis object interoperate in independent thread through the CORBA (soft-bus), realizing sharing resource and multi-expert cooperation diagnosis online, solving the disadvantage such as lack of diagnosis knowledge, oneness of diagnosis technique and imperfectness of analysis function, so that more complicated and further diagnosis can be carried on. Take high-speed centrifugal air compressor set for example, we demonstrate a distributed diagnosis based on CORBA. It proves that we can find out more efficient approaches to settle the problems such as real-time monitoring and diagnosis on the net and the break-up of complicated tasks, inosculating CORBA, Web technique and agent frame model to carry on complemental research. In this system, Multi-diagnosis Intelligent Agent helps improve diagnosis efficiency. Besides, this system offers an open circumstances, which is easy for the diagnosis objects to upgrade and for new diagnosis server objects to join in.

Multi-agent Simulations of Population Behavior: A Promising Tool for Systems Biology.

PubMed

Colosimo, Alfredo

2018-01-01

This contribution reports on the simulation of some dynamical events observed in the collective behavior of different kinds of populations, ranging from shape-changing cells in a Petri dish to functionally correlated brain areas in vivo. The unifying methodological approach, based upon a Multi-Agent Simulation (MAS) paradigm as incorporated in the NetLogo™ interpreter, is a direct consequence of the cornerstone that simple, individual actions within a population of interacting agents often give rise to complex, collective behavior.The discussion will mainly focus on the emergence and spreading of synchronous activities within the population, as well as on the modulation of the collective behavior exerted by environmental force-fields. A relevant section of this contribution is dedicated to the extension of the MAS paradigm to Brain Network models. In such a general framework some recent applications taken from the direct experience of the author, and exploring the activation patterns characteristic of specific brain functional states, are described, and their impact on the Systems-Biology universe underlined.

Integration of multi-array sensors and support vector machines for the detection and classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Sadik, Omowunmi A.; Embrechts, Mark J.; Leibensperger, Dale; Wong, Lut; Wanekaya, Adam; Uematsu, Michiko

2003-08-01

Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. Furthermore, recent events have highlighted awareness that chemical and biological agents (CBAs) may become the preferred, cheap alternative WMD, because these agents can effectively attack large populations while leaving infrastructures intact. Despite the availability of numerous sensing devices, intelligent hybrid sensors that can detect and degrade CBAs are virtually nonexistent. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using parathion and dichlorvos as model stimulants compounds. SVMs were used for the design and evaluation of new and more accurate data extraction, preprocessing and classification. Experimental results for the paradigms developed using Structural Risk Minimization, show a significant increase in classification accuracy when compared to the existing AromaScan baseline system. Specifically, the results of this research has demonstrated that, for the Parathion versus Dichlorvos pair, when compared to the AromaScan baseline system: (1) a 23% improvement in the overall ROC Az index using the S2000 kernel, with similar improvements with the Gaussian and polynomial (of degree 2) kernels, (2) a significant 173% improvement in specificity with the S2000 kernel. This means that the number of false negative errors were reduced by 173%, while making no false positive errors, when compared to the AromaScan base line performance. (3) The Gaussian and polynomial kernels demonstrated similar specificity at 100% sensitivity. All SVM classifiers provided essentially perfect classification performance for the Dichlorvos versus Trichlorfon pair. For the most difficult classification task, the Parathion versus Paraoxon pair, the following results were achieved (using the three SVM kernels: (1) ROC Az indices from approximately 93% to greater than 99%, (2) partial Az values from ~79% to 93%, (3) specificities from 76% to ~84% at 100 and 98% sensitivity, and (4) PPVs from 73% to ~84% at 100% and 98% sensitivities. These are excellent results, considering only one atom differentiates these nerve agents.

Addressing Production System Failures Using Multi-agent Control

NASA Astrophysics Data System (ADS)

Gautam, Rajesh; Miyashita, Kazuo

Output in high-volume production facilities is limited by bottleneck machines. We propose a control mechanism by modeling workstations as agents that pull jobs from other agents based on their current WIP level and requirements. During failures, when flows of some jobs are disrupted, the agents pull alternative jobs to maintain utilization of their capacity at a high level. In this paper, we empirically demonstrate that the proposed mechanism can react to failures more appropriately than other control mechanisms using a benchmark problem of a semiconductor manufacturing process.

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.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Nanoparticle imaging probes for molecular imaging with computed tomography and application to cancer imaging

NASA Astrophysics Data System (ADS)

Roeder, Ryan K.; Curtis, Tyler E.; Nallathamby, Prakash D.; Irimata, Lisa E.; McGinnity, Tracie L.; Cole, Lisa E.; Vargo-Gogola, Tracy; Cowden Dahl, Karen D.

2017-03-01

Precision imaging is needed to realize precision medicine in cancer detection and treatment. Molecular imaging offers the ability to target and identify tumors, associated abnormalities, and specific cell populations with overexpressed receptors. Nuclear imaging and radionuclide probes provide high sensitivity but subject the patient to a high radiation dose and provide limited spatiotemporal information, requiring combined computed tomography (CT) for anatomic imaging. Therefore, nanoparticle contrast agents have been designed to enable molecular imaging and improve detection in CT alone. Core-shell nanoparticles provide a powerful platform for designing tailored imaging probes. The composition of the core is chosen for enabling strong X-ray contrast, multi-agent imaging with photon-counting spectral CT, and multimodal imaging. A silica shell is used for protective, biocompatible encapsulation of the core composition, volume-loading fluorophores or radionuclides for multimodal imaging, and facile surface functionalization with antibodies or small molecules for targeted delivery. Multi-agent (k-edge) imaging and quantitative molecular imaging with spectral CT was demonstrated using current clinical agents (iodine and BaSO4) and a proposed spectral library of contrast agents (Gd2O3, HfO2, and Au). Bisphosphonate-functionalized Au nanoparticles were demonstrated to enhance sensitivity and specificity for the detection of breast microcalcifications by conventional radiography and CT in both normal and dense mammary tissue using murine models. Moreover, photon-counting spectral CT enabled quantitative material decomposition of the Au and calcium signals. Immunoconjugated Au@SiO2 nanoparticles enabled highly-specific targeting of CD133+ ovarian cancer stem cells for contrast-enhanced detection in model tumors.

Negotiating designs of multi-purpose reservoir systems in international basins

NASA Astrophysics Data System (ADS)

Geressu, Robel; Harou, Julien

2016-04-01

Given increasing agricultural and energy demands, coordinated management of multi-reservoir systems could help increase production without further stressing available water resources. However, regional or international disputes about water-use rights pose a challenge to efficient expansion and management of many large reservoir systems. Even when projects are likely to benefit all stakeholders, agreeing on the design, operation, financing, and benefit sharing can be challenging. This is due to the difficulty of considering multiple stakeholder interests in the design of projects and understanding the benefit trade-offs that designs imply. Incommensurate performance metrics, incomplete knowledge on system requirements, lack of objectivity in managing conflict and difficulty to communicate complex issue exacerbate the problem. This work proposes a multi-step hybrid multi-objective optimization and multi-criteria ranking approach for supporting negotiation in water resource systems. The approach uses many-objective optimization to generate alternative efficient designs and reveal the trade-offs between conflicting objectives. This enables informed elicitation of criteria weights for further multi-criteria ranking of alternatives. An ideal design would be ranked as best by all stakeholders. Resource-sharing mechanisms such as power-trade and/or cost sharing may help competing stakeholders arrive at designs acceptable to all. Many-objective optimization helps suggests efficient designs (reservoir site, its storage size and operating rule) and coordination levels considering the perspectives of multiple stakeholders simultaneously. We apply the proposed approach to a proof-of-concept study of the expansion of the Blue Nile transboundary reservoir system.

Precision gimballed mirror control in remote sensing LIDAR for environmental monitoring

NASA Astrophysics Data System (ADS)

Singh, Ravindra; Mudgil, Ashwani; Prakash, Chandra; Pal, Suranjan

2006-12-01

Differential Absorption Lidar (DIAL) Systems are advantageously used to detect and measure very small concentrations of trace gases in the atmosphere. There is a requirement to interrogate and search for the presence of one or more of toxic agents out of a large number (about 20 or so) of possible agents at distances up to several kilometers with the help of a ground-based multi-wavelength DIAL system employing pulsed, tunable laser sources in the wavelength bands of 2-5 micron and 9.2-10.8 micron. The Laser beams from the two sources are directed in the atmosphere with a predefined divergence to scan the atmosphere. Two methodologies can be implemented to provide the beam steering, one is to mount the entire telescope of transmitting and receiving channel on to a motorized gimbal platform and second is to keep the optical telescope stationary and use a slewing mirror to steer the beam in required direction. The first scheme is named as mass control and second scheme is called mirror control. Both the schemes have relative advantages and disadvantages and in the present DIAL application second scheme is being adopted. The present opto-mechanical configuration of DIAL system employs a 700 x 500 mm 2 (Elliptical) steering mirror for transmitting the collimated beams in a required direction and receiving the reflected beam as well. In the receiving channel a Telescope is used which collects the return beam and focuses the same on to a detector. The slewing mirror is housed in a gimbal mount having a sufficient FOR (Field of Regard) in Azimuth and elevation plane. The paper describes the modeling and simulation of Opto-mechanical and servo-mechanical subsystems of precision gimbaled mirror and also discusses the issues related to design of control system. The requirement specifications in regard to field of regard, slew rates 5°/s, scanning rates 1°/s are to be met with stringent beam pointing and scanning accuracies. The design of this system is categorized as multidisciplinary problem. The design parameters obtained from opto-mechanical analysis forms the input for control system design. The design of control system is carried out using conventional design methodologies.

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.

Multi-Agent Methods for the Configuration of Random Nanocomputers

NASA Technical Reports Server (NTRS)

Lawson, John W.

2004-01-01

As computational devices continue to shrink, the cost of manufacturing such devices is expected to grow exponentially. One alternative to the costly, detailed design and assembly of conventional computers is to place the nano-electronic components randomly on a chip. The price for such a trivial assembly process is that the resulting chip would not be programmable by conventional means. In this work, we show that such random nanocomputers can be adaptively programmed using multi-agent methods. This is accomplished through the optimization of an associated high dimensional error function. By representing each of the independent variables as a reinforcement learning agent, we are able to achieve convergence must faster than with other methods, including simulated annealing. Standard combinational logic circuits such as adders and multipliers are implemented in a straightforward manner. In addition, we show that the intrinsic flexibility of these adaptive methods allows the random computers to be reconfigured easily, making them reusable. Recovery from faults is also demonstrated.

A Systematic Literature Review of Agents Applied in Healthcare.

PubMed

Isern, David; Moreno, Antonio

2016-02-01

Intelligent agents and healthcare have been intimately linked in the last years. The intrinsic complexity and diversity of care can be tackled with the flexibility, dynamics and reliability of multi-agent systems. The purpose of this review is to show the feasibility of applying intelligent agents in the healthcare domain and use the findings to provide a discussion of current trends and devise future research directions. A review of the most recent literature (2009-2014) of applications of agents in healthcare is discussed, and two classifications considering the main goal of the health systems as well as the main actors involved have been investigated. This review shows that the number of published works exhibits a growing interest of researchers in this field in a wide range of applications.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

The Design of Motivational Agents and Avatars

ERIC Educational Resources Information Center

Baylor, Amy L.

2011-01-01

While the addition of an anthropomorphic interface agent to a learning system generally has little direct impact on learning, it potentially has a huge impact on learner motivation. As such agents become increasingly ubiquitous on the Internet, in virtual worlds, and as interfaces for learning and gaming systems, it is important to design them to…

Analysis of Foreign Exchange Interventions by Intervention Agent with an Artificial Market Approach

NASA Astrophysics Data System (ADS)

Matsui, Hiroki; Tojo, Satoshi

We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. Izumi et al. had presented a system called AGEDASI TOF to simulate artificial market, together with a support system for the government to decide foreign exchange policies. However, the system needed to fix the amount of governmental intervention prior to the simulation, and was not realistic. In addition, the interventions in the system did not affect supply and demand of currencies; thus we could not discuss the effect of intervention correctly. First, we improve the system so as to make much of the weights of influential factors. Thereafter, we introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning, and that the exchange rate converged to a certain extent in the expected range. We could also estimate the amount of intervention, showing the efficacy of signaling. In this model, in order to investigate the aliasing of the perception of the intervention agent, we introduced a pseudo-agent who was supposed to be able to observe all the behaviors of dealer agents; with this super-agent, we discussed the adequate granularity for a market state description.

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.

Designing across Ages: Multi-Agent-Based Models and Learning Electricity

ERIC Educational Resources Information Center

Sengupta, Pratim

2009-01-01

Electricity is regarded as one of the most challenging topics for students at all levels--middle school--college (Cohen, Eylon, & Ganiel, 1983; Belcher & Olbert, 2003; Eylon & Ganiel, 1990; Steinberg et al., 1985). Several researchers have suggested that naive misconceptions about electricity stem from a deep incommensurability (Slotta & Chi,…

The Multi-Agent Tactical Sentry: Designing and Delivering Robots to the CF

DTIC Science & Technology

2008-08-01

believed that there is no substitute for having the man in the loop during military operations. After the World Trade Center and Tokyo subway attacks...and vibration isolation for the more sensitive components. Additional space was left to account for possible future changes to the primary sensors

Application of systems thinking in health: opportunities for translating theory into practice Comment on "Constraints to applying systems thinking concepts in health systems: a regional perspective from surveying stakeholders in Eastern Mediterranean countries".

PubMed

Malik, Asmat Ullah

2015-03-19

Systems thinking is not a new concept to health system strengthening; however, one question remains unanswered: How policy-makers, system designers and consultants with a system thinking philosophy should act (have acted) as potential change agents in actually gaining opportunities to introduce systems thinking? Development of Comprehensive Multi-Year Plans (cMYPs) for Immunization System is one such opportunity because almost all Low- and Middle-Income Countries (LMICs) develop and implement cMYPs every five years. Without building upon examples and showing practical application, the discussions and deliberations on systems thinking may fade away with passage of time. There are opportunities that exist around us in our existing health systems that we can benefit from starting with an incremental approach and generating evidence for longer lasting system-wide changes. © 2015 by Kerman University of Medical Sciences.

Novel aminohydrazide cross-linked chitosan filled with multi-walled carbon nanotubes as antimicrobial agents.

PubMed

Mohamed, Nadia A; Abd El-Ghany, Nahed A

2018-04-21

Four chemically modified chitosan derivatives 1-4 were designed and synthesized via a series of four reactions; first by reaction with benzaldehyde to protect its amino groups (Derivative 1), second by reaction with epichlorohydrine (Derivative 2), third by reaction with aminobenzhydrazide (Derivative 3), and forth by removing of benzaldehyde to restore the free amino groups on the chitosan (Derivative 4). Two multi-walled carbon nanotube (MWCNT) biocomposites based on Derivative 4 were also prepared. The structure of the prepared derivatives and MWCNT composites was elucidated using elemental analyses, FTIR, XRD, SEM and TEM. The modified chitosan derivatives and MWCNT composites showed better antimicrobial activities than that of chitosan against Enterococcus faecalis, Staphylococcus epidermidis, Escherichia coli, Aspergillus niger, Cryptococcus neoformans and Candida tropicalis as judged by their higher inhibition zone diameters using the agar well diffusion technique. These derivatives and MWCNT composites are more potent against Gram-positive bacteria than against Gram-negative bacteria. The MWCNT composites displayed comparable or even better antimicrobial activities than the reference bactericides or fungicides. Thus, structural modification of chitosan through combination with functionalized moieties and MWCNTs in one system was taken as a way to achieve promising templates for antimicrobial agents and to be appropriate candidates for medical applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Human-Centric Teaming in a Multi-Agent EVA Assembly Task

NASA Technical Reports Server (NTRS)

Rehnmark, Fredrik; Currie, Nancy; Ambrose, Robert O.; Culbert, Christopher

2004-01-01

NASA's Human Space Flight program depends heavily on spacewalks performed by pairs of suited human astronauts. These Extra-Vehicular Activities (EVAs) are severely restricted in both duration and scope by consumables and available manpower.An expanded multi-agent EVA team combining the information-gathering and problem-solving skills of human astronauts with the survivability and physical capabilities of highly dexterous space robots is proposed. A 1-g test featuring two NASA/DARPA Robonaut systems working side-by-side with a suited human subject is conducted to evaluate human-robot teaming strategies in the context of a simulated EVA assembly task based on the STS-61B ACCESS flight experiment.

Designing a Successful Bidding Strategy Using Fuzzy Sets and Agent Attitudes

NASA Astrophysics Data System (ADS)

Ma, Jun; Goyal, Madhu Lata

To be successful in a multi-attribute auction, agents must be capable of adapting to continuously changing bidding price. This chapter presents a novel fuzzy attitude-based bidding strategy (FA-Bid), which employs dual assessment technique, i.e., assessment of multiple attributes of the goods as well as assessment of agents' attitude (eagerness) to procure an item in automated auction. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process as well use heuristic rules to determine the attitude of bidding agents in simulated auctions to procure goods. The overall assessment is used to determine a price range based on current bid, which finally selects the best one as the new bid.

Patient and health care professional views and experiences of computer agent-supported health care.

PubMed

Neville, Ron G; Greene, Alexandra C; Lewis, Sue

2006-01-01

To explore patient and health care professional (HCP) views towards the use of multi-agent computer systems in their GP practice. Qualitative analysis of in-depth interviews and analysis of transcriptions. Urban health centre in Dundee, Scotland. Five representative healthcare professionals and 11 patients. Emergent themes from interviews revealed participants' attitudes and beliefs, which were coded and indexed. Patients and HCPs had similar beliefs, attitudes and views towards the implementation of multi-agent systems (MAS). Both felt modern communication methods were useful to supplement, not supplant, face-to-face consultations between doctors and patients. This was based on the immense trust these patients placed in their doctors in this practice, which extended to trust in their choice of communication technology and security. Rapid access to medical information increased patients' sense of shared partnership and self-efficacy. Patients and HCPs expressed respect for each other's time and were keen to embrace technology that made interactions more efficient, including for the altruistic benefit of others less technically competent. Patients and HCPs welcomed the introduction of agent technology to the delivery of health care. Widespread use will depend more on the trust patients place in their own GP than on technological issues.

Common aperture multispectral optics for military applications

NASA Astrophysics Data System (ADS)

Thompson, N. A.

2012-06-01

With the recent developments in multi-spectral detector technology the interest in common aperture, common focal plane multi-spectral imaging systems is increasing. Such systems are particularly desirable for military applications where increased levels of target discrimination and identification are required in cost-effective, rugged, lightweight systems. During the optical design of dual waveband or multi-spectral systems, the options for material selection are limited. This selection becomes even more restrictive for military applications as material resilience and thermal properties must be considered in addition to colour correction. In this paper we discuss the design challenges that lightweight multi-spectral common aperture systems present along with some potential design solutions. Consideration will be given to material selection for optimum colour correction as well as material resilience and thermal correction. This discussion is supported using design examples that are currently in development at Qioptiq.

A surgical confocal microlaparoscope for real-time optical biopsies

NASA Astrophysics Data System (ADS)

Tanbakuchi, Anthony Amir

The first real-time fluorescence confocal microlaparoscope has been developed that provides instant in vivo cellular images, comparable to those provided by histology, through a nondestructive procedure. The device includes an integrated contrast agent delivery mechanism and a computerized depth scan system. The instrument uses a fiber bundle to relay the image plane of a slit-scan confocal microlaparoscope into tissue. The confocal laparoscope was used to image the ovaries of twenty-one patients in vivo using fluorescein sodium and acridine orange as the fluorescent contrast agents. The results indicate that the device is safe and functions as designed. A Monte Carlo model was developed to characterize the system performance in a scattering media representative of human tissues. The results indicate that a slit aperture has limited ability to image below the surface of tissue. In contrast, the results show that multi-pinhole apertures such as a Nipkow disk or a linear pinhole array can achieve nearly the same depth performance as a single pinhole aperture. The model was used to determine the optimal aperture spacing for the multi-pinhole apertures. The confocal microlaparoscope represents a new type of in vivo imaging device. With its ability to image cellular details in real time, it has the potential to aid in the early diagnosis of cancer. Initially, the device may be used to locate unusual regions for guided biopsies. In the long term, the device may be able to supplant traditional biopsies and allow the surgeon to identify early stage cancer in vivo.

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

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.

Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

PubMed

Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

2012-08-01

The discovery of new and more potent anti-cancer agents constitutes one of the most active fields of research in chemotherapy. Colorectal cancer (CRC) is one of the most studied cancers because of its high prevalence and number of deaths. In the current pharmaceutical design of more efficient anti-CRC drugs, the use of methodologies based on Chemoinformatics has played a decisive role, including Quantitative-Structure-Activity Relationship (QSAR) techniques. However, until now, there is no methodology able to predict anti-CRC activity of compounds against more than one CRC cell line, which should constitute the principal goal. In an attempt to overcome this problem we develop here the first multi-target (mt) approach for the virtual screening and rational in silico discovery of anti-CRC agents against ten cell lines. Here, two mt-QSAR classification models were constructed using a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors while the second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted from the molecules and their contributions to anti-CRC activity were calculated using mt-QSAR-LDA model. Several fragments were identified as potential substructural features responsible for the anti-CRC activity and new molecules designed from those fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-CRC agents. Copyright © 2012 Elsevier Ltd. All rights reserved.

A novel multi-stimuli responsive gelator based on D-gluconic acetal and its potential applications.

PubMed

Guan, Xidong; Fan, Kaiqi; Gao, Tongyang; Ma, Anping; Zhang, Bao; Song, Jian

2016-01-18

We construct a simple-structured super gelator with multi-stimuli responsive properties, among which anion responsiveness follows the Hofmeister series in a non-aqueous system. Versatile applications such as being rheological and self-healing agents, waste water treatment, spilled oil recovery and flexible optical device manufacture are integrated into a single organogelator, which was rarely reported.

Coalition Agents Experiment: Multi-Agent Co-operation in an International Coalition Setting

DTIC Science & Technology

2002-04-01

middleware layer based on Java / Jini technology that provides the computing infrastructure to integrate heterogeneous agent communities and systems...Bowl of Africa". E GAO Elb i-on1-1 I ~ ~ L11g A1adz^ , fo foq r cs 9 6 •F ..................................... Figure 1. Map of Binni showing...firestorm deception. Misinformation from Gao is intended to displace the firestorm to the west, allowing Gao and Agadez forces to clash in the region of the

Process-oriented integration and coordination of healthcare services across organizational boundaries.

PubMed

Tello-Leal, Edgar; Chiotti, Omar; Villarreal, Pablo David

2012-12-01

The paper presents a methodology that follows a top-down approach based on a Model-Driven Architecture for integrating and coordinating healthcare services through cross-organizational processes to enable organizations providing high quality healthcare services and continuous process improvements. The methodology provides a modeling language that enables organizations conceptualizing an integration agreement, and identifying and designing cross-organizational process models. These models are used for the automatic generation of: the private view of processes each organization should perform to fulfill its role in cross-organizational processes, and Colored Petri Net specifications to implement these processes. A multi-agent system platform provides agents able to interpret Colored Petri-Nets to enable the communication between the Healthcare Information Systems for executing the cross-organizational processes. Clinical documents are defined using the HL7 Clinical Document Architecture. This methodology guarantees that important requirements for healthcare services integration and coordination are fulfilled: interoperability between heterogeneous Healthcare Information Systems; ability to cope with changes in cross-organizational processes; guarantee of alignment between the integrated healthcare service solution defined at the organizational level and the solution defined at technological level; and the distributed execution of cross-organizational processes keeping the organizations autonomy.

Multi-stimuli responsive Cu2S nanocrystals as trimodal imaging and synergistic chemo-photothermal therapy agents

NASA Astrophysics Data System (ADS)

Poulose, Aby Cheruvathoor; Veeranarayanan, Srivani; Mohamed, M. Sheikh; Nagaoka, Yutaka; Romero Aburto, Rebeca; Mitcham, Trevor; Ajayan, Pulickel M.; Bouchard, Richard R.; Sakamoto, Yasushi; Yoshida, Yasuhiko; Maekawa, Toru; Sakthi Kumar, D.

2015-04-01

A size and shape tuned, multifunctional metal chalcogenide, Cu2S-based nanotheranostic agent is developed for trimodal imaging and multimodal therapeutics against brain cancer cells. This theranostic agent was highly efficient in optical, photoacoustic and X-ray contrast imaging systems. The folate targeted NIR-responsive photothermal ablation in synergism with the chemotherapeutic action of doxorubicin proved to be a rapid precision guided cancer-killing module. The multi-stimuli, i.e., pH-, thermo- and photo-responsive drug release behavior of the nanoconjugates opens up a wider corridor for on-demand triggered drug administration. The simple synthesis protocol, combined with the multitudes of interesting features packed into a single nanoformulation, clearly demonstrates the competing role of this Cu2S nanosystem in future cancer treatment strategies.A size and shape tuned, multifunctional metal chalcogenide, Cu2S-based nanotheranostic agent is developed for trimodal imaging and multimodal therapeutics against brain cancer cells. This theranostic agent was highly efficient in optical, photoacoustic and X-ray contrast imaging systems. The folate targeted NIR-responsive photothermal ablation in synergism with the chemotherapeutic action of doxorubicin proved to be a rapid precision guided cancer-killing module. The multi-stimuli, i.e., pH-, thermo- and photo-responsive drug release behavior of the nanoconjugates opens up a wider corridor for on-demand triggered drug administration. The simple synthesis protocol, combined with the multitudes of interesting features packed into a single nanoformulation, clearly demonstrates the competing role of this Cu2S nanosystem in future cancer treatment strategies. Electronic supplementary information (ESI) available: Methodology and additional experimental results. See DOI: 10.1039/c4nr07139e

Health Care Decision Support System for the Pediatric Emeregency Department Management.

PubMed

Ben Othman, Sarah; Hammadi, Slim; Quilliot, Alain; Martinot, Alain; Renard, Jean-Marie

2015-01-01

Health organization management is facing a high amount of complexity due to the inherent dynamics of the processes and the distributed organization of hospitals. It is therefore necessary for health care institutions to focus on this issue in order to deal with patients' requirements and satisfy their needs. The main objective of this study is to develop and implement a Decision Support System which can help physicians to better manage their organization, to anticipate the overcrowding feature, and to establish avoidance proposals for it. This work is a part of HOST project (Hospital: Optimization, Simulation, and Crowding Avoidance) of the French National Research Agency (ANR). It aims to optimize the functioning of the Pediatric Emergency Department characterized by stochastic arrivals of patients which leads to its overcrowding and services overload. Our study is a set of tools to smooth out patient flows, enhance care quality and minimize long waiting times and costs due to resources allocation. So we defined a decision aided tool based on Multi-agent Systems where actors negotiate and cooperate under some constraints in a dynamic environment. These entities which can be either physical agents representing real actors in the health care institution or software agents allowing the implementation of optimizing tools, cooperate to satisfy the demands of patients while respecting emergency degrees. This paper is concerned with agents' negotiation. It proposes a new approach for multi-skill tasks scheduling based on interactions between agents.

A Review of Chemical Warfare Agent (CWA) Detector Technologies and Commercial-Off-The-Shelf Items

DTIC Science & Technology

2009-03-01

Environmental Health Perspectives 1994, 102, 18-38. 21. La Franchi , P., Chemical and Biological Weapons: The War from Hell. ADM September, 1995, pp 9-10...One-to-Five Gas Monitor with VOC Detection. In ENVCO Global . DSTO-GD-0570 98 152. MultiRAE Plus. In RAE Systems: San Jose, CA. 153. ToxiRAE Plus PID...158. Rippen, M., Chemical and Biological Agent Sensor/Detector Systems Technology Development for Applications in the Global War on Terrorism. In

Intercell scheduling: A negotiation approach using multi-agent coalitions

NASA Astrophysics Data System (ADS)

Tian, Yunna; Li, Dongni; Zheng, Dan; Jia, Yunde

2016-10-01

Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.

75 FR 23223 - Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-03

...] Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program; Public... Select Agent Program established under the Public Health Security and Bioterrorism Preparedness and... Roberson, Veterinary Permit Examiner, APHIS Select Agent Program, VS, ASAP, APHIS, 4700 River Road Unit 2...

76 FR 14896 - Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-18

...] Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program; Public... specific regulatory guidance related to the Federal Select Agent Program established under the Public.... Sarah Kwiatkowski, Veterinary Program Assistant, APHIS Select Agent Program, APHIS, 4700 River Road Unit...

76 FR 17617 - Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-30

...] Multi-Agency Informational Meeting Concerning Compliance With the Federal Select Agent Program; Public... specific regulatory guidance related to the Federal Select Agent Program established under the Public.... Sarah Kwiatkowski, Veterinary Program Assistant, APHIS Select Agent Program, APHIS, 4700 River Road Unit...

Design of a Multi-Pinhole Collimator for I-123 DaTscan Imaging on Dual-Headed SPECT Systems in Combination with a Fan-Beam Collimator.

PubMed

King, Michael A; Mukherjee, Joyeeta M; Könik, Arda; Zubal, I George; Dey, Joyoni; Licho, Robert

2016-02-01

For the 2011 FDA approved Parkinson's Disease (PD) SPECT imaging agent I-123 labeled DaTscan, the volume of interest (VOI) is the interior portion of the brain. However imaging of the occipital lobe is also required with PD for calculation of the striatal binding ratio (SBR), a parameter of significance in early diagnosis, differentiation of PD from other disorders with similar clinical presentations, and monitoring progression. Thus we propose the usage of a combination of a multi-pinhole (MPH) collimator on one head of the SPECT system and a fan-beam on the other. The MPH would be designed to provide high resolution and sensitivity for imaging of the interior portion of the brain. The fan-beam collimator would provide lower resolution but complete sampling of the brain addressing data sufficiency and allowing a volume-of-interest to be defined over the occipital lobe for calculation of SBR's. Herein we focus on the design of the MPH component of the combined system. Combined reconstruction will be addressed in a subsequent publication. An analysis of 46 clinical DaTscan studies was performed to provide information to define the VOI, and design of a MPH collimator to image this VOI. The system spatial resolution for the MPH was set to 4.7 mm, which is comparable to that of clinical PET systems, and significantly smaller than that of fan-beam collimators employed in SPECT. With this set, we compared system sensitivities for three aperture array designs, and selected the 3 × 3 array due to it being the highest of the three. The combined sensitivity of the apertures for it was similar to that of an ultra-high resolution fan-beam (LEUHRF) collimator, but smaller than that of a high-resolution fan-beam collimator (LEHRF). On the basis of these results we propose the further exploration of this design through simulations, and the development of combined MPH and fan-beam reconstruction.

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

‘Multi-Epitope-Targeted’ Immune-Specific Therapy for a Multiple Sclerosis-Like Disease via Engineered Multi-Epitope Protein Is Superior to Peptides

PubMed Central

Zilkha-Falb, Rina; Yosef-Hemo, Reut; Cohen, Lydia; Ben-Nun, Avraham

2011-01-01

Antigen-induced peripheral tolerance is potentially one of the most efficient and specific therapeutic approaches for autoimmune diseases. Although highly effective in animal models, antigen-based strategies have not yet been translated into practicable human therapy, and several clinical trials using a single antigen or peptidic-epitope in multiple sclerosis (MS) yielded disappointing results. In these clinical trials, however, the apparent complexity and dynamics of the pathogenic autoimmunity associated with MS, which result from the multiplicity of potential target antigens and “epitope spread”, have not been sufficiently considered. Thus, targeting pathogenic T-cells reactive against a single antigen/epitope is unlikely to be sufficient; to be effective, immunospecific therapy to MS should logically neutralize concomitantly T-cells reactive against as many major target antigens/epitopes as possible. We investigated such “multi-epitope-targeting” approach in murine experimental autoimmune encephalomyelitis (EAE) associated with a single (“classical”) or multiple (“complex”) anti-myelin autoreactivities, using cocktail of different encephalitogenic peptides vis-a-vis artificial multi-epitope-protein (designated Y-MSPc) encompassing rationally selected MS-relevant epitopes of five major myelin antigens, as “multi-epitope-targeting” agents. Y-MSPc was superior to peptide(s) in concomitantly downregulating pathogenic T-cells reactive against multiple myelin antigens/epitopes, via inducing more effective, longer lasting peripheral regulatory mechanisms (cytokine shift, anergy, and Foxp3+ CTLA4+ regulatory T-cells). Y-MSPc was also consistently more effective than the disease-inducing single peptide or peptide cocktail, not only in suppressing the development of “classical” or “complex EAE” or ameliorating ongoing disease, but most importantly, in reversing chronic EAE. Overall, our data emphasize that a “multi-epitope-targeting” strategy is required for effective immune-specific therapy of organ-specific autoimmune diseases associated with complex and dynamic pathogenic autoimmunity, such as MS; our data further demonstrate that the “multi-epitope-targeting” approach to therapy is optimized through specifically designed multi-epitope-proteins, rather than myelin peptide cocktails, as “multi-epitope-targeting” agents. Such artificial multi-epitope proteins can be tailored to other organ-specific autoimmune diseases. PMID:22140475

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

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

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.

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.

Analysis multi-agent with precense of the leader

NASA Astrophysics Data System (ADS)

Achmadi, Sentot; Marjono, Miswanto

2017-12-01

The phenomenon of swarm is a natural phenomenon that is often done by a collection of living things in the form of motion from one place to another. By clustering, a group of animals can increase their effectiveness in food search and avoid predators. A group of geese also performs a swarm phenomenon when flying and forms an inverted V-formation with one of the geese acting as a leader. Each flying track of members of the geese group always follows the leader's path at a certain distance. This article discusses the mathematical modeling of the swarm phenomenon, which is the optimal tracking control for multi-agent model with the influence of the leader in the 2-dimensional space. The leader in this model is intended to track the specified path. Firstly, the leader's motion control is to follow the predetermined path using the Tracking Error Dynamic method. Then, the path from the leader is used to design the motion control of each agent to track the leader's path at a certain distance. The result of numerical simulation shows that the leader trajectory can track the specified path. Similarly, the motion of each agent can trace and follow the leader's path.