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.

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.

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.

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.

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

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.

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.

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

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.

Reach a nonlinear consensus for MAS via doubly stochastic quadratic operators

NASA Astrophysics Data System (ADS)

Abdulghafor, Rawad; Turaev, Sherzod; Zeki, Akram; Al-Shaikhli, Imad

2018-06-01

This technical note addresses the new nonlinear protocol class of doubly stochastic quadratic operators (DSQOs) for coordination of consensus problem in multi-agent systems (MAS). We derive the conditions for ensuring that every agent reaches consensus on a desired rate of the group's decision where the group decision value in its agent's initial statuses varies. Besides that, we investigate a nonlinear protocol sub-class of extreme DSQO (EDSQO) to reach a consensus for MAS to a common value with nonlinear low-complexity rules and fast time convergence if the interactions for each agent are not selfish. In addition, to extend the results to reach a consensus and to avoid the selfish case we specify a general class of DSQO for reaching a consensus under any given case of initial states. The case that MAS reach a consensus by DSQO is if each member of the agent group has positive interactions of DSQO (PDSQO) with the others. The convergence of both EDSQO and PDSQO classes is found to be directed towards the centre point. Finally, experimental simulations are given to support the analysis from theoretical aspect.

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.

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.

Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

NASA Astrophysics Data System (ADS)

Rienow, A.; Menz, G.

2015-12-01

Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future face of post-industrial cities are revealed. Finally, the advantages and limitations of linking pixels and people by combining AI and machine learning techniques in a multi-scale geosimulation approach are to be discussed.

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

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.

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

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.

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.

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.

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.

Energy Optimization Using a Case-Based Reasoning Strategy

PubMed Central

Herrera-Viedma, Enrique

2018-01-01

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices. PMID:29543729

Energy Optimization Using a Case-Based Reasoning Strategy.

PubMed

González-Briones, Alfonso; Prieto, Javier; De La Prieta, Fernando; Herrera-Viedma, Enrique; Corchado, Juan M

2018-03-15

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

The Control of Multi-Agent Systems (MAS)

DTIC Science & Technology

2004-09-01

Mixes rational (ground state E0 = |↓>) & emotional (excited state E1 = |↑>) • M(I, S) -> shifts agent |↑> or |↓> w/P(1) (Gibson, 1986; Caccioppo...1951): a group is more than sum of parts – Luce & Raiffa (1967): individual rational perspective cannot account for the “social” (viz., game and...deception • Assumption: Reality is bistable with I that is mostly inaccessible 2 9th ICCRTS, Copenhagen, 9/2004 Paradoxes • Rational , Individual: ∑xi

The Control of Multi-Agent Systems (MAS)

DTIC Science & Technology

2004-06-01

alternatively, system or organization theory) Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Paine College,1235 15th Street,Augusta,GA,30901-3182 8. PERFORMING ORGANIZATION ...idp’s) (Lawless & Grayson, 2004). Introduction To construct a mathematical theory of organization for the control of MAS’s sufficient to

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

Advanced Modeling System for Optimization of Wind Farm Layout and Wind Turbine Sizing Using a Multi-Level Extended Pattern Search Algorithm

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

DuPont, Bryony; Cagan, Jonathan; Moriarty, Patrick

This paper presents a system of modeling advances that can be applied in the computational optimization of wind plants. These modeling advances include accurate cost and power modeling, partial wake interaction, and the effects of varying atmospheric stability. To validate the use of this advanced modeling system, it is employed within an Extended Pattern Search (EPS)-Multi-Agent System (MAS) optimization approach for multiple wind scenarios. The wind farm layout optimization problem involves optimizing the position and size of wind turbines such that the aerodynamic effects of upstream turbines are reduced, which increases the effective wind speed and resultant power at eachmore » turbine. The EPS-MAS optimization algorithm employs a profit objective, and an overarching search determines individual turbine positions, with a concurrent EPS-MAS determining the optimal hub height and rotor diameter for each turbine. Two wind cases are considered: (1) constant, unidirectional wind, and (2) three discrete wind speeds and varying wind directions, each of which have a probability of occurrence. Results show the advantages of applying the series of advanced models compared to previous application of an EPS with less advanced models to wind farm layout optimization, and imply best practices for computational optimization of wind farms with improved accuracy.« less

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.

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.

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

Role playing games: a methodology to acquire knowledge for integrated wastewater infrastructures management in a river basin scale.

PubMed

Prat, P; Aulinas, M; Turon, C; Comas, J; Poch, M

2009-01-01

Current management of sanitation infrastructures (sewer systems, wastewater treatment plant, receiving water, bypasses, deposits, etc) is not fulfilling the objectives of up to date legislation, to achieve a good ecological and chemical status of water bodies through integrated management. These made it necessary to develop new methodologies that help decision makers to improve the management in order to achieve that status. Decision Support Systems (DSS) based on Multi-Agent System (MAS) paradigm are promising tools to improve the integrated management. When all the different agents involved interact, new important knowledge emerges. This knowledge can be used to build better DSS and improve wastewater infrastructures management achieving the objectives planned by legislation. The paper describes a methodology to acquire this knowledge through a Role Playing Game (RPG). First of all there is an introduction about the wastewater problems, a definition of RPG, and the relation between RPG and MAS. Then it is explained how the RPG was built with two examples of game sessions and results. The paper finishes with a discussion about the uses of this methodology and future work.

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.

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

PubMed Central

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

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy. PMID:26161437

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems.

PubMed

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

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

Product Distribution Theory and Semi-Coordinate Transformations

NASA Technical Reports Server (NTRS)

Airiau, Stephane; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for doing distributed adaptive control of a multiagent system (MAS). We introduce the technique of "coordinate transformations" in PD theory gradient descent. These transformations selectively couple a few agents with each other into "meta-agents". Intuitively, this can be viewed as a generalization of forming binding contracts between those agents. Doing this sacrifices a bit of the distributed nature of the MAS, in that there must now be communication from multiple agents in determining what joint-move is finally implemented However, as we demonstrate in computer experiments, these transformations improve the performance of the MAS.

A Study on the Application of the Extended Matrices Based on TRIZ in Constructing a Collaborative Model of Enterprise Network

NASA Astrophysics Data System (ADS)

Yang, Yan; Shao, Yunfei; Tang, Xiaowo

Based on mass related literature on enterprise network, the key influence factors are reduced to Trust, Control, Relationship and Interaction. Meanwhile, the specific contradiction matrices, judgment matrices and strategy collections based on TRIZ are constructed which make the connotation of contradiction matrices in TRIZ extended. Finally they are applied to the construction of the collaborative model on enterprise network based on Multi Agent System (MAS).

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.

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

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.

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.

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.

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

PubMed

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

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

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

PubMed Central

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

2016-01-01

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

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.

IA and PA network-based computation of coordinating combat behaviors in the military MAS

NASA Astrophysics Data System (ADS)

Xia, Zuxun; Fang, Huijia

2004-09-01

In the military multi-agent system every agent needs to analyze the dependent and temporal relations among the tasks or combat behaviors for working-out its plans and getting the correct behavior sequences, it could guarantee good coordination, avoid unexpected damnification and guard against bungling the change of winning a battle due to the possible incorrect scheduling and conflicts. In this paper IA and PA network based computation of coordinating combat behaviors is put forward, and emphasize particularly on using 5x5 matrix to represent and compute the temporal binary relation (between two interval-events, two point-events or between one interval-event and one point-event), this matrix method makes the coordination computing convenience than before.

Agreement Technologies for Energy Optimization at Home.

PubMed

González-Briones, Alfonso; Chamoso, Pablo; De La Prieta, Fernando; Demazeau, Yves; Corchado, Juan M

2018-05-19

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.

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.

Urban Expansion Modeling Approach Based on Multi-Agent System and Cellular Automata

NASA Astrophysics Data System (ADS)

Zeng, Y. N.; Yu, M. M.; Li, S. N.

2018-04-01

Urban expansion is a land-use change process that transforms non-urban land into urban land. This process results in the loss of natural vegetation and increase in impervious surfaces. Urban expansion also alters the hydrologic cycling, atmospheric circulation, and nutrient cycling processes and generates enormous environmental and social impacts. Urban expansion monitoring and modeling are crucial to understanding urban expansion process, mechanism, and its environmental impacts, and predicting urban expansion in future scenarios. Therefore, it is important to study urban expansion monitoring and modeling approaches. We proposed to simulate urban expansion by combining CA and MAS model. The proposed urban expansion model based on MSA and CA was applied to a case study area of Changsha-Zhuzhou-Xiangtan urban agglomeration, China. The results show that this model can capture urban expansion with good adaptability. The Kappa coefficient of the simulation results is 0.75, which indicated that the combination of MAS and CA offered the better simulation result.

Agreement Technologies for Energy Optimization at Home

PubMed Central

2018-01-01

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%. PMID:29783768

Global Sensitivity Analysis for Large-scale Socio-hydrological Models using the Cloud

NASA Astrophysics Data System (ADS)

Hu, Y.; Garcia-Cabrejo, O.; Cai, X.; Valocchi, A. J.; Dupont, B.

2014-12-01

In the context of coupled human and natural system (CHNS), incorporating human factors into water resource management provides us with the opportunity to understand the interactions between human and environmental systems. A multi-agent system (MAS) model is designed to couple with the physically-based Republican River Compact Administration (RRCA) groundwater model, in an attempt to understand the declining water table and base flow in the heavily irrigated Republican River basin. For MAS modelling, we defined five behavioral parameters (κ_pr, ν_pr, κ_prep, ν_prep and λ) to characterize the agent's pumping behavior given the uncertainties of the future crop prices and precipitation. κ and ν describe agent's beliefs in their prior knowledge of the mean and variance of crop prices (κ_pr, ν_pr) and precipitation (κ_prep, ν_prep), and λ is used to describe the agent's attitude towards the fluctuation of crop profits. Notice that these human behavioral parameters as inputs to the MAS model are highly uncertain and even not measurable. Thus, we estimate the influences of these behavioral parameters on the coupled models using Global Sensitivity Analysis (GSA). In this paper, we address two main challenges arising from GSA with such a large-scale socio-hydrological model by using Hadoop-based Cloud Computing techniques and Polynomial Chaos Expansion (PCE) based variance decomposition approach. As a result, 1,000 scenarios of the coupled models are completed within two hours with the Hadoop framework, rather than about 28days if we run those scenarios sequentially. Based on the model results, GSA using PCE is able to measure the impacts of the spatial and temporal variations of these behavioral parameters on crop profits and water table, and thus identifies two influential parameters, κ_pr and λ. The major contribution of this work is a methodological framework for the application of GSA in large-scale socio-hydrological models. This framework attempts to find a balance between the heavy computational burden regarding model execution and the number of model evaluations required in the GSA analysis, particularly through an organic combination of Hadoop-based Cloud Computing to efficiently evaluate the socio-hydrological model and PCE where the sensitivity indices are efficiently estimated from its coefficients.

Real-Time Smart Grids Control for Preventing Cascading Failures and Blackout using Neural Networks: Experimental Approach for N-1-1 Contingency

NASA Astrophysics Data System (ADS)

Zarrabian, Sina; Belkacemi, Rabie; Babalola, Adeniyi A.

2016-12-01

In this paper, a novel intelligent control is proposed based on Artificial Neural Networks (ANN) to mitigate cascading failure (CF) and prevent blackout in smart grid systems after N-1-1 contingency condition in real-time. The fundamental contribution of this research is to deploy the machine learning concept for preventing blackout at early stages of its occurrence and to make smart grids more resilient, reliable, and robust. The proposed method provides the best action selection strategy for adaptive adjustment of generators' output power through frequency control. This method is able to relieve congestion of transmission lines and prevent consecutive transmission line outage after N-1-1 contingency condition. The proposed ANN-based control approach is tested on an experimental 100 kW test system developed by the authors to test intelligent systems. Additionally, the proposed approach is validated on the large-scale IEEE 118-bus power system by simulation studies. Experimental results show that the ANN approach is very promising and provides accurate and robust control by preventing blackout. The technique is compared to a heuristic multi-agent system (MAS) approach based on communication interchanges. The ANN approach showed more accurate and robust response than the MAS algorithm.

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

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

None, None

The multi-agent system (MAS) approach has been applied with promising results for enhancing an electric power distribution circuit, such as the Circuit of the Future as developed by Southern California Edison. These next generation power system results include better ability to reconfigure the circuit as well as the increased capability to improve the protection and enhance the reliability of the circuit. There were four main tasks in this project. The specific results for each of these four tasks and their related topics are presented in main sections of this report. Also, there were seven deliverables for this project. The mainmore » conclusions for these deliverables are summarized in the identified subtask section of this report. The specific details for each of these deliverables are included in the “Project Deliverables” section at the end of this Final Report.« less

1H line width dependence on MAS speed in solid state NMR - Comparison of experiment and simulation

NASA Astrophysics Data System (ADS)

Sternberg, Ulrich; Witter, Raiker; Kuprov, Ilya; Lamley, Jonathan M.; Oss, Andres; Lewandowski, Józef R.; Samoson, Ago

2018-06-01

Recent developments in magic angle spinning (MAS) technology permit spinning frequencies of ≥100 kHz. We examine the effect of such fast MAS rates upon nuclear magnetic resonance proton line widths in the multi-spin system of β-Asp-Ala crystal. We perform powder pattern simulations employing Fokker-Plank approach with periodic boundary conditions and 1H-chemical shift tensors calculated using the bond polarization theory. The theoretical predictions mirror well the experimental results. Both approaches demonstrate that homogeneous broadening has a linear-quadratic dependency on the inverse of the MAS spinning frequency and that, at the faster end of the spinning frequencies, the residual spectral line broadening becomes dominated by chemical shift distributions and susceptibility effects even for crystalline systems.

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

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

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

A multiagent system enhancing home-care health services for chronic disease management.

PubMed

Koutkias, Vassilis G; Chouvarda, Ioanna; Maglaveras, Nicos

2005-12-01

In this paper, a multiagent system (MAS) is presented, aiming to enhance monitoring, surveillance, and educational services of a generic medical contact center (MCC) for chronic disease management. In such a home-care scenario, a persistent need arises for efficiently monitoring the patient contacts and the MCC's functionality, in order to effectively manage and interpret the large volume of medical data collected during the patient sessions with the system, and to assess the use of MCC resources. Software agents were adopted to provide the means to accomplish such real-time information-processing tasks, due to their autonomous, reactive and/or proactive nature, and their effectiveness in dynamic environments by incorporating coordination strategies. Specifically, the objective of the MAS is to monitor the MCC environment, detect important cases, and inform the healthcare and administrative personnel via alert messages, notifications, recommendations, and reports, prompting them for actions. The main aim of this paper is to present the overall design and implementation of a proposed MAS, emphasizing its functional model and architecture, as well as on the agent interactions and the knowledge-sharing mechanism incorporated, in the context of a generic MCC.

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.

The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

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.

Concepts and theoretical specifications of a Coastal Vulnerability Dynamic Simulator (COVUDS): A multi-agent system for simulating coastal vulnerability towards management of coastal ecosystem services

NASA Astrophysics Data System (ADS)

Orencio, P. M.; Endo, A.; Taniguchi, M.

2014-12-01

Disaster-causing natural hazards such as floods, erosions, earthquakes or slope failures were particularly observed to be concentrated in certain geographical regions. In the Asia-pacific region, coastal ecosystems were suffering because of perennial threats driven by chronic fluctuations in climate variability (e.g., typhoons, ENSO), or by dynamically occurring events (e.g., earthquakes, tsunamis). Among the many people that were found prone to such a risky condition were the ones inhabiting near the coastal areas. Characteristically, aside from being located at the forefront of these events, the coastal communities have impacted the resource by the kind of behavioral patterns they exhibited, such as overdependence and overexploitation to achieve their wellbeing. In this paper, we introduce the development of an approach to an assessment of the coupled human- environment using a multi- agent simulation (MAS) model known as Coastal Vulnerability Dynamic Simulator (COVUDS). The COVUDS comprised a human- environmental platform consisting multi- agents with corresponding spatial- based dynamic and static variables. These variables were used to present multiple hypothetical future situations that contribute to the purpose of supporting a more rational management of the coastal ecosystem and their environmental equities. Initially, we present the theoretical and conceptual components that would lead to the development of the COVUDS. These consisted of the human population engaged in behavioral patterns affecting the conditions of coastal ecosystem services; the system of the biophysical environment and changes in patches brought by global environment and local behavioral variations; the policy factors that were important for choosing area- specific interventions; and the decision- making mechanism that integrates the first three components. To guide a future scenario-based application that will be undertaken in a coastal area in the Philippines, the components of the model will be presented within a platform following a parameterized architecture.

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.

Making the Grid "Smart" Through "Smart" Microgrids: Real-Time Power Management of Microgrids with Multiple Distributed Generation Sources Using Intelligent Control

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

Nehrir, M. Hashem

In this Project we collaborated with two DOE National Laboratories, Pacific Northwest National Lab (PNNL) and Lawrence Berkeley National Lab (LBL). Dr. Hammerstrom of PNNL initially supported our project and was on the graduate committee of one of the Ph.D. students (graduated in 2014) who was supported by this project. He is also a committee member of a current graduate student of the PI who was supported by this project in the last two years (August 2014-July 2016). The graduate student is now supported be the Electrical and Computer Engineering (ECE) Department at Montana State University (MSU). Dr. Chris Marneymore » of LBL provided actual load data, and the software WEBOPT developed at LBL for microgrid (MG) design for our project. NEC-Labs America, a private industry, also supported our project, providing expert support and modest financial support. We also used the software “HOMER,” originally developed at the National Renewable Energy Laboratory (NREL) and the most recent version made available to us by HOMER Energy, Inc., for MG (hybrid energy system) unit sizing. We compared the findings from WebOpt and HOMER and designed appropriately sized hybrid systems for our case studies. The objective of the project was to investigate real-time power management strategies for MGs using intelligent control, considering maximum feasible energy sustainability, reliability and efficiency while, minimizing cost and undesired environmental impact (emissions). Through analytic and simulation studies, we evaluated the suitability of several heuristic and artificial-intelligence (AI)-based optimization techniques that had potential for real-time MG power management, including genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and multi-agent systems (MAS), which is based on the negotiation of smart software-based agents. We found that PSO and MAS, in particular, distributed MAS, were more efficient and better suited for our work. We investigated the following: • Intelligent load control - demand response (DR) - for frequency stabilization in islanded MGs (partially supported by PNNL). • The impact of high penetration of solar photovoltaic (PV)-generated power at the distribution level (partially supported by PNNL). • The application of AI approaches to renewable (wind, PV) power forecasting (proposed by the reviewers of our proposal). • Application of AI approaches and DR for real-time MG power management (partially supported by NEC Labs-America) • Application of DR in dealing with the variability of wind power • Real-time MG power management using DR and storage (partially supported by NEC Labs-America) • Application of DR in enhancing the performance of load-frequency controller • MAS-based whole-sale and retail power market design for smart grid A« less

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.

Enhancing E-Health Information Systems with Agent Technology

PubMed Central

Nguyen, Minh Tuan; Fuhrer, Patrik; Pasquier-Rocha, Jacques

2009-01-01

Agent Technology is an emerging and promising research area in software technology, which increasingly contributes to the development of value-added information systems for large healthcare organizations. Through the MediMAS prototype, resulting from a case study conducted at a local Swiss hospital, this paper aims at presenting the advantages of reinforcing such a complex E-health man-machine information organization with software agents. The latter will work on behalf of human agents, taking care of routine tasks, and thus increasing the speed, the systematic, and ultimately the reliability of the information exchanges. We further claim that the modeling of the software agent layer can be methodically derived from the actual “classical” laboratory organization and practices, as well as seamlessly integrated with the existing information system. PMID:19096509

A quantitative study on magnesium alloy stent biodegradation.

PubMed

Gao, Yuanming; Wang, Lizhen; Gu, Xuenan; Chu, Zhaowei; Guo, Meng; Fan, Yubo

2018-06-06

Insufficient scaffolding time in the process of rapid corrosion is the main problem of magnesium alloy stent (MAS). Finite element method had been used to investigate corrosion of MAS. However, related researches mostly described all elements suffered corrosion in view of one-dimensional corrosion. Multi-dimensional corrosions significantly influence mechanical integrity of MAS structures such as edges and corners. In this study, the effects of multi-dimensional corrosion were studied using experiment quantitatively, then a phenomenological corrosion model was developed to consider these effects. We implemented immersion test with magnesium alloy (AZ31B) cubes, which had different numbers of exposed surfaces to analyze differences of dimension. It was indicated that corrosion rates of cubes are almost proportional to their exposed-surface numbers, especially when pitting corrosions are not marked. The cubes also represented the hexahedron elements in simulation. In conclusion, corrosion rate of every element accelerates by increasing corrosion-surface numbers in multi-dimensional corrosion. The damage ratios among elements with the same size are proportional to the ratios of corrosion-surface numbers under uniform corrosion. The finite element simulation using proposed model provided more details of changes of morphology and mechanics in scaffolding time by removing 25.7% of elements of MAS. The proposed corrosion model reflected the effects of multi-dimension on corrosions. It would be used to predict degradation process of MAS quantitatively. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Leaderless consensus for the fractional-order nonlinear multi-agent systems under directed interaction topology

NASA Astrophysics Data System (ADS)

Bai, Jing; Wen, Guoguang; Rahmani, Ahmed

2018-04-01

Leaderless consensus for the fractional-order nonlinear multi-agent systems is investigated in this paper. At the first part, a control protocol is proposed to achieve leaderless consensus for the nonlinear single-integrator multi-agent systems. At the second part, based on sliding mode estimator, a control protocol is given to solve leaderless consensus for the the nonlinear single-integrator multi-agent systems. It shows that the control protocol can improve the systems' convergence speed. At the third part, a control protocol is designed to accomplish leaderless consensus for the nonlinear double-integrator multi-agent systems. To judge the systems' stability in this paper, two classic continuous Lyapunov candidate functions are chosen. Finally, several worked out examples under directed interaction topology are given to prove above results.

Cooperating systems: Layered MAS

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel

1990-01-01

Distributed intelligent systems can be distinguished by the models that they use. The model developed focuses on layered multiagent system conceived of as a bureaucracy in which a distributed data base serves as a central means of communication. The various generic bureaus of such a system is described and a basic vocabulary for such systems is presented. In presenting the bureaus and vocabularies, special attention is given to the sorts of reasonings that are appropriate. A bureaucratic model has a hierarchy of master system and work group that organizes E agents and B agents. The master system provides the administrative services and support facilities for the work groups.

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

Managing the Evolution of an Enterprise Architecture using a MAS-Product-Line Approach

NASA Technical Reports Server (NTRS)

Pena, Joaquin; Hinchey, Michael G.; Resinas, manuel; Sterritt, Roy; Rash, James L.

2006-01-01

We view an evolutionary system ns being n software product line. The core architecture is the unchanging part of the system, and each version of the system may be viewed as a product from the product line. Each "product" may be described as the core architecture with sonre agent-based additions. The result is a multiagent system software product line. We describe an approach to such n Software Product Line-based approach using the MaCMAS Agent-Oriented nzethoclology. The approach scales to enterprise nrchitectures as a multiagent system is an approprinre means of representing a changing enterprise nrchitectclre nnd the inferaction between components in it.

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...

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.

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.

Building intelligence in third-generation training and battle simulations

NASA Astrophysics Data System (ADS)

Jacobi, Dennis; Anderson, Don; von Borries, Vance; Elmaghraby, Adel; Kantardzic, Mehmed; Ragade, Rammohan

2003-09-01

Current war games and simulations are primarily attrition based, and are centered on the concept of force on force. They constitute what can be defined as "second generation" war games. So-called "first generation" war games were focused on strategy with the primary concept of mind on mind. We envision "third generation" war games and battle simulations as concentrating on effects with the primary concept being system on system. Thus the third generation systems will incorporate each successive generation and take into account strategy, attrition and effects. This paper will describe the principal advantages and features that need to be implemented to create a true "third generation" battle simulation and the architectural issues faced when designing and building such a system. Areas of primary concern are doctrine, command and control, allied and coalition warfare, and cascading effects. Effectively addressing the interactive effects of these issues is of critical importance. In order to provide an adaptable and modular system that will accept future modifications and additions with relative ease, we are researching the use of a distributed Multi-Agent System (MAS) that incorporates various artificial intelligence methods. The agent architecture can mirror the military command structure from both vertical and horizontal perspectives while providing the ability to make modifications to doctrine, command structures, inter-command communications, as well as model the results of various effects upon one another, and upon the components of the simulation. This is commonly referred to as "cascading effects," in which A affects B, B affects C and so on. Agents can be used to simulate units or parts of units that interact to form the whole. Even individuals can eventually be simulated to take into account the affect to key individuals such as commanders, heroes, and aces. Each agent will have a learning component built in to provide "individual intelligence" based on experience.

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.

Dynamic Nuclear Polarization NMR in Human Cells Using Fluorescent Polarizing Agents.

PubMed

Albert, Brice J; Gao, Chukun; Sesti, Erika L; Saliba, Edward P; Alaniva, Nicholas; Scott, Faith J; Sigurdsson, Snorri Th; Barnes, Alexander B

2018-06-20

Solid-state nuclear magnetic resonance (NMR) enables atomic resolution characterization of molecular structure and dynamics within complex heterogeneous samples, but it is typically insensitive. Dynamic nuclear polarization (DNP) increases NMR signal intensity by orders of magnitude and can be performed in combination with magic angle spinning (MAS) for sensitive, high-resolution spectroscopy. Here we report MAS DNP experiments, for the first time, within intact human cells with >40-fold DNP enhancement and a sample temperature below 6 K. In addition to cryogenic MAS results below 6 K, we also show in-cell DNP enhancements of 57-fold at 90 K. In-cell DNP is demonstrated using biradicals and sterically-shielded monoradicals as polarizing agents. A novel trimodal polarizing agent is introduced for DNP, which contains a nitroxide biradical, a targeting peptide for cell penetration, and a fluorophore for subcellular localization with confocal microscopy. The fluorescent polarizing agent provides in-cell DNP enhancements of 63-fold at a concentration of 2.7 mM. These experiments pave the way for structural characterization of biomolecules in an endogenous cellular context.

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…

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Trajectory Control of Scale-Free Dynamical Networks with Exogenous Disturbances

NASA Astrophysics Data System (ADS)

Yang, Hong-Yong; Zhang, Shun; Zong, Guang-Deng

2011-01-01

In this paper, the trajectory control of multi-agent dynamical systems with exogenous disturbances is studied. Suppose multiple agents composing of a scale-free network topology, the performance of rejecting disturbances for the low degree node and high degree node is analyzed. Firstly, the consensus of multi-agent systems without disturbances is studied by designing a pinning control strategy on a part of agents, where this pinning control can bring multiple agents' states to an expected consensus track. Then, the influence of the disturbances is considered by developing disturbance observers, and disturbance observers based control (DOBC) are developed for disturbances generated by an exogenous system to estimate the disturbances. Asymptotical consensus of the multi-agent systems with disturbances under the composite controller can be achieved for scale-free network topology. Finally, by analyzing examples of multi-agent systems with scale-free network topology and exogenous disturbances, the verities of the results are proved. Under the DOBC with the designed parameters, the trajectory convergence of multi-agent systems is researched by pinning two class of the nodes. We have found that it has more stronger robustness to exogenous disturbances for the high degree node pinned than that of the low degree node pinned.

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.

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.

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.

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).

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.

Chitin degradation and metabolism by virulent Aeromonas hydropila

USDA-ARS?s Scientific Manuscript database

Aeromonas hydrophila is the causal agent of motile Aeromonas septicemia (MAS) in catfish and other warm-water fishes. Severe outbreak of MAS caused by virulent A. hydrophila (vAh) was reported in 2009 in the Southeastern United States; the disease has since resulted in loss of millions of pounds of ...

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…

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.

Multi-Atlas Segmentation of Biomedical Images: A Survey

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert R.

2015-01-01

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, Brandt, Menzel and Maurer Jr (2004), Klein, Mensh, Ghosh, Tourville and Hirsch (2005), and Heckemann, Hajnal, Aljabar, Rueckert and Hammers (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of “atlases” (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003 – 2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation. PMID:26201875

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.

Adaptive tracking control of leader-following linear multi-agent systems with external disturbances

NASA Astrophysics Data System (ADS)

Lin, Hanquan; Wei, Qinglai; Liu, Derong; Ma, Hongwen

2016-10-01

In this paper, the consensus problem for leader-following linear multi-agent systems with external disturbances is investigated. Brownian motions are used to describe exogenous disturbances. A distributed tracking controller based on Riccati inequalities with an adaptive law for adjusting coupling weights between neighbouring agents is designed for leader-following multi-agent systems under fixed and switching topologies. In traditional distributed static controllers, the coupling weights depend on the communication graph. However, coupling weights associated with the feedback gain matrix in our method are updated by state errors between neighbouring agents. We further present the stability analysis of leader-following multi-agent systems with stochastic disturbances under switching topology. Most traditional literature requires the graph to be connected all the time, while the communication graph is only assumed to be jointly connected in this paper. The design technique is based on Riccati inequalities and algebraic graph theory. Finally, simulations are given to show the validity of our method.

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

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.

Distributed Optimization of Multi-Agent Systems: Framework, Local Optimizer, and Applications

NASA Astrophysics Data System (ADS)

Zu, Yue

Convex optimization problem can be solved in a centralized or distributed manner. Compared with centralized methods based on single-agent system, distributed algorithms rely on multi-agent systems with information exchanging among connected neighbors, which leads to great improvement on the system fault tolerance. Thus, a task within multi-agent system can be completed with presence of partial agent failures. By problem decomposition, a large-scale problem can be divided into a set of small-scale sub-problems that can be solved in sequence/parallel. Hence, the computational complexity is greatly reduced by distributed algorithm in multi-agent system. Moreover, distributed algorithm allows data collected and stored in a distributed fashion, which successfully overcomes the drawbacks of using multicast due to the bandwidth limitation. Distributed algorithm has been applied in solving a variety of real-world problems. Our research focuses on the framework and local optimizer design in practical engineering applications. In the first one, we propose a multi-sensor and multi-agent scheme for spatial motion estimation of a rigid body. Estimation performance is improved in terms of accuracy and convergence speed. Second, we develop a cyber-physical system and implement distributed computation devices to optimize the in-building evacuation path when hazard occurs. The proposed Bellman-Ford Dual-Subgradient path planning method relieves the congestion in corridor and the exit areas. At last, highway traffic flow is managed by adjusting speed limits to minimize the fuel consumption and travel time in the third project. Optimal control strategy is designed through both centralized and distributed algorithm based on convex problem formulation. Moreover, a hybrid control scheme is presented for highway network travel time minimization. Compared with no controlled case or conventional highway traffic control strategy, the proposed hybrid control strategy greatly reduces total travel time on test highway network.

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.

Quicker Q-Learning in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2005-01-01

Multi-agent learning in Markov Decisions Problems is challenging because of the presence ot two credit assignment problems: 1) How to credit an action taken at time step t for rewards received at t' greater than t; and 2) How to credit an action taken by agent i considering the system reward is a function of the actions of all the agents. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning OK TD(lambda) The second credit assi,onment problem is typically addressed either by hand-crafting reward functions that assign proper credit to an agent, or by making certain independence assumptions about an agent's state-space and reward function. 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. Instead of assuming that an agent s value function can be made independent of other agents, this method suppresses the impact of other agents using counterfactual rewards. Results on multi-agent grid-world problems over multiple topologies show that QUICR-learning can achieve up to thirty fold improvements in performance over both conventional and local Q-learning in the largest tested systems.

An applicable approach for extracting human heart rate and oxygen saturation during physical movements using a multi-wavelength illumination optoelectronic sensor system

NASA Astrophysics Data System (ADS)

Alharbi, Samah; Hu, Sijung; Mulvaney, David; Blanos, Panagiotis

2018-02-01

The ability to gather physiological parameters such as heart rate (HR) and oxygen saturation (SpO2%) during physical movement allows to continuously monitor personal health status without disrupt their normal daily activities. Photoplethysmography (PPG) based pulse oximetry and similar principle devices are unable to extract the HR and SpO2% reliably during physical movement due to interference in the signals that arise from motion artefacts (MAs). In this research, a flexible reflectance multi-wavelength optoelectronic patch sensor (OEPS) has been developed to overcome the susceptibility of conventional pulse oximetry readings to MAs. The OEPS incorporates light embittered diodes as illumination sources with four different wavelengths, e.g. green, orange, red, and infrared unlike the conventional pulse oximetry devices that normally measure the skin absorption of only two wavelengths (red and infrared). The additional green and orange wavelengths were found to be distinguish to the absorption of deoxyhemoglobin (RHb) and oxyhemoglobin (HbO2). The reliability of extracting physiological parameters from the green and orange wavelengths is due to absorbed near to the surface of the skin, thereby shortening the optical path and so effectively reducing the influence of physical movements. To compensate of MAs, a three-axis accelerometer was used as a reference with help of adaptive filter to reduce MAs. The experiments were performed using 15 healthy subjects aged 20 to 30. The primary results show that there are no significant difference of heart rate and oxygen saturation measurements between commercial devices and OEPS Green (r=0.992), Orange(r=0.984), Red(r=0.952) and IR(r=0.97) and SpO2% (r = 0.982, p = 0.894).

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.

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.

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.

Project MAS, 1982-1983. O.E.E. Evaluation Report.

ERIC Educational Resources Information Center

Villegas, Ana; Villegas, Jose

This multi-site instructional program, in its first year of a three-year funding cycle, provided instruction in English as a Second Language (ESL) and native language arts, as well as bilingual instruction in various content areas, to 400 Spanish speaking students of limited English proficiency in grades 3-8. The functional goal of Project MAS,…

The ACE-2/Ang1-7/Mas cascade enhances bone structure and metabolism following angiotensin-II type 1 receptor blockade.

PubMed

Abuohashish, Hatem M; Ahmed, Mohammed M; Sabry, Dina; Khattab, Mahmoud M; Al-Rejaie, Salim S

2017-07-15

The renin angiotensin system (RAS) regulates numerous systemic functions and is expressed locally in skeletal tissues. Angiotensin1-7 (Ang1-7) is a beneficial member of the RAS, and the therapeutic effects of a large number of angiotensin receptors blockers (ARBs) are mediated by an Ang1-7-dependent cascade. This study examines whether the reported osteo-preservative effects of losartan are mediated through the angiotensin converting enzyme2 (ACE-2)/Ang1-7/Mas pathway in ovariectomized (OVX) rats. Sham and OVX animals received losartan (10mg/kg/d p.o.) for 6 weeks. A specific Mas receptor blocker (A-779) was delivered via mini-osmotic pumps during the losartan treatment period. Serum and urine bone metabolism biomarker levels were measured. Bone trabecular and cortical morphometry were quantified in distal femurs, whereas mineral contents were estimated in ashed bones, serum and urine. Finally, the expression of RAS components, the receptor activator of NF-κB ligand (RANKL) and osteoprotegerin (OPG) was determined. Losartan significantly improved the elevated bone metabolism marker levels and altered trabecular and cortical structures in OVX animals, and restored normal urinary and skeletal mineral levels. Mas receptor inhibition significantly abolished all osteo-protective effects of losartan and enhanced the deleterious effects of OVX. Losartan enhanced OVX-induced up-regulation of ACE-1, AngII, angiotensin type 1 (AT 1 ) receptor and RANKL expression, and increased ACE-2, Ang1-7, Mas and OPG expression in OVX animals. However, A-779 significantly eradicated the effects of losartan on RAS components and RANKL/OPG expression. Thus, Ang1-7 are involved in the osteo-preservative effects of losartan via Mas receptor, which may add therapeutic value to this well-known antihypertensive agent. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-agent system as a new approach to effective chronic heart failure management: key considerations.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Rahimi, Azin

2013-09-01

Given the importance of the follow-up of chronic heart failure (CHF) patients to reduce common causes of re-admission and deterioration of their status that lead to imposing spiritual and physical costs on patients and society, modern technology tools should be used to the best advantage. The aim of this article is to explain key points which should be considered in designing an appropriate multi-agent system to improve CHF management. In this literature review articles were searched with keywords like multi-agent system, heart failure, chronic disease management in Science Direct, Google Scholar and PubMed databases without regard to the year of publications. Agents are an innovation in the field of artificial intelligence. Because agents are capable of solving complex and dynamic health problems, to take full advantage of e-Health, the healthcare system must take steps to make use of this technology. Key factors in CHF management through a multi-agent system approach must be considered such as organization, confidentiality in general aspects and design and architecture points in specific aspects. Note that use of agent systems only with a technical view is associated with many problems. Hence, in delivering healthcare to CHF patients, considering social and human aspects is essential. It is obvious that identifying and resolving technical and non-technical challenges is vital in the successful implementation of this technology.

Multi-Agent System as a New Approach to Effective Chronic Heart Failure Management: Key Considerations

PubMed Central

Mohammadzadeh, Niloofar; Rahimi, Azin

2013-01-01

Objectives Given the importance of the follow-up of chronic heart failure (CHF) patients to reduce common causes of re-admission and deterioration of their status that lead to imposing spiritual and physical costs on patients and society, modern technology tools should be used to the best advantage. The aim of this article is to explain key points which should be considered in designing an appropriate multi-agent system to improve CHF management. Methods In this literature review articles were searched with keywords like multi-agent system, heart failure, chronic disease management in Science Direct, Google Scholar and PubMed databases without regard to the year of publications. Results Agents are an innovation in the field of artificial intelligence. Because agents are capable of solving complex and dynamic health problems, to take full advantage of e-Health, the healthcare system must take steps to make use of this technology. Key factors in CHF management through a multi-agent system approach must be considered such as organization, confidentiality in general aspects and design and architecture points in specific aspects. Conclusions Note that use of agent systems only with a technical view is associated with many problems. Hence, in delivering healthcare to CHF patients, considering social and human aspects is essential. It is obvious that identifying and resolving technical and non-technical challenges is vital in the successful implementation of this technology. PMID:24195010

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.

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

NASA Astrophysics Data System (ADS)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

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 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 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.

Improving Scene Classifications with Combined Active/Passive Measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Rodier, S.; Vaughan, M.; McGill, M.

The uncertainties in cloud and aerosol physical properties derived from passive instruments such as MODIS are not insignificant And the uncertainty increases when the optical depths decrease Lidar observations do much better for the thin clouds and aerosols Unfortunately space-based lidar measurements such as the one onboard CALIPSO satellites are limited to nadir view only and thus have limited spatial coverage To produce climatologically meaningful thin cloud and aerosol data products it is necessary to combine the spatial coverage of MODIS with the highly sensitive CALIPSO lidar measurements Can we improving the quality of cloud and aerosol remote sensing data products by extending the knowledge about thin clouds and aerosols learned from CALIPSO-type of lidar measurements to a larger portion of the off-nadir MODIS-like multi-spectral pixels To answer the question we studied the collocated Cloud Physics Lidar CPL with Modis-Airborne-Simulation MAS observations and established an effective data fusion technique that will be applied in the combined CALIPSO MODIS cloud aerosol product algorithms This technique performs k-mean and Kohonen self-organized map cluster analysis on the entire swath of MAS data as well as on the combined CPL MAS data at the nadir track Interestingly the clusters generated from the two approaches are almost identical It indicates that the MAS multi-spectral data may have already captured most of the cloud and aerosol scene types such as cloud ice water phase multi-layer information aerosols

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.

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

Retinal Microaneurysms Detection Using Gradient Vector Analysis and Class Imbalance Classification.

PubMed

Dai, Baisheng; Wu, Xiangqian; Bu, Wei

2016-01-01

Retinal microaneurysms (MAs) are the earliest clinically observable lesions of diabetic retinopathy. Reliable automated MAs detection is thus critical for early diagnosis of diabetic retinopathy. This paper proposes a novel method for the automated MAs detection in color fundus images based on gradient vector analysis and class imbalance classification, which is composed of two stages, i.e. candidate MAs extraction and classification. In the first stage, a candidate MAs extraction algorithm is devised by analyzing the gradient field of the image, in which a multi-scale log condition number map is computed based on the gradient vectors for vessel removal, and then the candidate MAs are localized according to the second order directional derivatives computed in different directions. Due to the complexity of fundus image, besides a small number of true MAs, there are also a large amount of non-MAs in the extracted candidates. Classifying the true MAs and the non-MAs is an extremely class imbalanced classification problem. Therefore, in the second stage, several types of features including geometry, contrast, intensity, edge, texture, region descriptors and other features are extracted from the candidate MAs and a class imbalance classifier, i.e., RUSBoost, is trained for the MAs classification. With the Retinopathy Online Challenge (ROC) criterion, the proposed method achieves an average sensitivity of 0.433 at 1/8, 1/4, 1/2, 1, 2, 4 and 8 false positives per image on the ROC database, which is comparable with the state-of-the-art approaches, and 0.321 on the DiaRetDB1 V2.1 database, which outperforms the state-of-the-art approaches.

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.

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.

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.

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.

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.

Distributed robust finite-time nonlinear consensus protocols for multi-agent systems

NASA Astrophysics Data System (ADS)

Zuo, Zongyu; Tie, Lin

2016-04-01

This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.

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.

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.

Sensitivity subgroup analysis based on single-center vs. multi-center trial status when interpreting meta-analyses pooled estimates: the logical way forward.

PubMed

Alexander, Paul E; Bonner, Ashley J; Agarwal, Arnav; Li, Shelly-Anne; Hariharan, Abishek; Izhar, Zain; Bhatnagar, Neera; Alba, Carolina; Akl, Elie A; Fei, Yutong; Guyatt, Gordon H; Beyene, Joseph

2016-06-01

Prior studies regarding whether single-center trial estimates are larger than multi-center are equivocal. We examined the extent to which single-center trials yield systematically larger effects than multi-center trials. We searched the 119 core clinical journals and the Cochrane Database of Systematic Reviews for meta-analyses (MAs) of randomized controlled trials (RCTs) published during 2012. In this meta-epidemiologic study, for binary variables, we computed the pooled ratio of ORs (RORs), and for continuous outcomes mean difference in standardized mean differences (SMDs), we conducted weighted random-effects meta-regression and random-effects MA modeling. Our primary analyses were restricted to MAs that included at least five RCTs and in which at least 25% of the studies used each of single trial center (SC) and more trial center (MC) designs. We identified 81 MAs for the odds ratio (OR) and 43 for the SMD outcome measures. Based on our analytic plan, our primary analysis (core) is based on 25 MAs/241 RCTs (binary outcome) and 18 MAs/173 RCTs (continuous outcome). Based on the core analysis, we found no difference in magnitude of effect between SC and MC for binary outcomes [RORs: 1.02; 95% confidence interval (CI): 0.83, 1.24; I(2) 20.2%]. Effect sizes were systematically larger for SC than MC for the continuous outcome measure (mean difference in SMDs: -0.13; 95% CI: -0.21, -0.05; I(2) 0%). Our results do not support prior findings of larger effects in SC than MC trials addressing binary outcomes but show a very similar small increase in effect in SC than MC trials addressing continuous outcomes. Authors of systematic reviews would be wise to include all trials irrespective of SC vs. MC design and address SC vs. MC status as a possible explanation of heterogeneity (and consider sensitivity analyses). Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Observer-based distributed adaptive iterative learning control for linear multi-agent systems

NASA Astrophysics Data System (ADS)

Li, Jinsha; Liu, Sanyang; Li, Junmin

2017-10-01

This paper investigates the consensus problem for linear multi-agent systems from the viewpoint of two-dimensional systems when the state information of each agent is not available. Observer-based fully distributed adaptive iterative learning protocol is designed in this paper. A local observer is designed for each agent and it is shown that without using any global information about the communication graph, all agents achieve consensus perfectly for all undirected connected communication graph when the number of iterations tends to infinity. The Lyapunov-like energy function is employed to facilitate the learning protocol design and property analysis. Finally, simulation example is given to illustrate the theoretical analysis.

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.

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.

Hydration properties of regioselectively etherified celluloses monitored by 2H and 13C solid-state MAS NMR spectroscopy.

PubMed

Larsen, Flemming H; Schöbitz, Michael; Schaller, Jens

2012-06-20

The hydration properties of 2,3-O-hydroxypropylcellulose (HPC) and 2,3-O-hydroxyethylcellulose (HEC) were analyzed by multi-nuclear solid-state MAS NMR spectroscopy. By 13C single-pulse (SP) MAS and cross-polarization (CP) MAS NMR, differences between the immobile regions and all parts of the polysaccharides were detected as a function of hydration. Complementary information about the water environments was observed by 2H MAS NMR. By this approach it was demonstrated that side chains in 2,3-O-HPC and 2,3-O-HEC were easier to hydrate than the cellulose backbone. Furthermore the motion of water was more restricted (slower) in 2,3-O-HPC than in 2,3-O-HEC. For both polysaccharides the hydration could be explained by a two-step process: in step one increased ordering of the immobile regions occurs after which the entire polymer is hydrated in step two. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Improved conventional and microwave-assisted silylation protocols for simultaneous gas chromatographic determination of tocopherols and sterols: Method development and multi-response optimization.

PubMed

Poojary, Mahesha M; Passamonti, Paolo

2016-12-09

This paper reports on improved conventional thermal silylation (CTS) and microwave-assisted silylation (MAS) methods for simultaneous determination of tocopherols and sterols by gas chromatography. Reaction parameters in each of the methods developed were systematically optimized using a full factorial design followed by a central composite design. Initially, experimental conditions for CTS were optimized using a block heater. Further, a rapid MAS was developed and optimized. To understand microwave heating mechanisms, MAS was optimized by two distinct modes of microwave heating: temperature-controlled MAS and power-controlled MAS, using dedicated instruments where reaction temperature and microwave power level were controlled and monitored online. Developed methods: were compared with routine overnight derivatization. On a comprehensive level, while both CTS and MAS were found to be efficient derivatization techniques, MAS significantly reduced the reaction time. The optimal derivatization temperature and time for CTS found to be 55°C and 54min, while it was 87°C and 1.2min for temperature-controlled MAS. Further, a microwave power of 300W and a derivatization time 0.5min found to be optimal for power-controlled MAS. The use of an appropriate derivatization solvent, such as pyridine, was found to be critical for the successful determination. Catalysts, like potassium acetate and 4-dimethylaminopyridine, enhanced the efficiency slightly. The developed methods showed excellent analytical performance in terms of linearity, accuracy and precision. Copyright © 2016 Elsevier B.V. All rights reserved.

Paramagnet induced signal quenching in MAS-DNP experiments in frozen homogeneous solutions

NASA Astrophysics Data System (ADS)

Corzilius, Björn; Andreas, Loren B.; Smith, Albert A.; Ni, Qing Zhe; Griffin, Robert G.

2014-03-01

The effects of nuclear signal quenching induced by the presence of a paramagnetic polarizing agent are documented for conditions used in magic angle spinning (MAS)-dynamic nuclear polarization (DNP) experiments on homogeneous solutions. In particular, we present a detailed analysis of three time constants: (1) the longitudinal build-up time constant TB for 1H; (2) the rotating frame relaxation time constant T1ρ for 1H and 13C and (3) T2 of 13C, the transverse relaxation time constant in the laboratory frame. These relaxation times were measured during microwave irradiation at a magnetic field of 5 T (140 GHz) as a function of the concentration of four polarizing agents: TOTAPOL, 4-amino-TEMPO, trityl (OX063), and Gd-DOTA and are compared to those obtained for a sample lacking paramagnetic doping. We also report the EPR relaxation time constants T1S and T2S, the DNP enhancements, ε, and the parameter E, defined below, which measures the sensitivity enhancement for the four polarizing agents as a function of the electron concentration. We observe substantial intensity losses (paramagnetic quenching) with all of the polarizing agents due to broadening mechanisms and cross relaxation during MAS. In particular, the monoradical trityl and biradical TOTAPOL induce ∼40% and 50% loss of signal intensity. In contrast there is little suppression of signal intensity in static samples containing these paramagnetic species. Despite the losses due to quenching, we find that all of the polarizing agents provide substantial gains in signal intensity with DNP, and in particular that the net enhancement is optimal for biradicals that operate with the cross effect. We discuss the possibility that much of this polarization loss can be regained with the development of instrumentation and methods to perform electron decoupling.

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.

Research and application of multi-agent genetic algorithm in tower defense game

NASA Astrophysics Data System (ADS)

Jin, Shaohua

2018-04-01

In this paper, a new multi-agent genetic algorithm based on orthogonal experiment is proposed, which is based on multi-agent system, genetic algorithm and orthogonal experimental design. The design of neighborhood competition operator, orthogonal crossover operator, Son and self-learning operator. The new algorithm is applied to mobile tower defense game, according to the characteristics of the game, the establishment of mathematical models, and finally increases the value of the game's monster.

An Agent-Based Model of Farmer Decision Making in Jordan

NASA Astrophysics Data System (ADS)

Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

2016-04-01

We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

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.

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

NASA Astrophysics Data System (ADS)

Qiao, Wei; Sipahi, Rifat

2014-01-01

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

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.

Fluid flow dynamics in MAS systems

NASA Astrophysics Data System (ADS)

Wilhelm, Dirk; Purea, Armin; Engelke, Frank

2015-08-01

The turbine system and the radial bearing of a high performance magic angle spinning (MAS) probe with 1.3 mm-rotor diameter has been analyzed for spinning rates up to 67 kHz. We focused mainly on the fluid flow properties of the MAS system. Therefore, computational fluid dynamics (CFD) simulations and fluid measurements of the turbine and the radial bearings have been performed. CFD simulation and measurement results of the 1.3 mm-MAS rotor system show relatively low efficiency (about 25%) compared to standard turbo machines outside the realm of MAS. However, in particular, MAS turbines are mainly optimized for speed and stability instead of efficiency. We have compared MAS systems for rotor diameter of 1.3-7 mm converted to dimensionless values with classical turbomachinery systems showing that the operation parameters (rotor diameter, inlet mass flow, spinning rate) are in the favorable range. This dimensionless analysis also supports radial turbines for low speed MAS probes and diagonal turbines for high speed MAS probes. Consequently, a change from Pelton type MAS turbines to diagonal turbines might be worth considering for high speed applications. CFD simulations of the radial bearings have been compared with basic theoretical values proposing considerably smaller frictional loss values. The discrepancies might be due to the simple linear flow profile employed for the theoretical model. Frictional losses generated inside the radial bearings result in undesired heat-up of the rotor. The rotor surface temperature distribution computed by CFD simulations show a large temperature gradient over the rotor.

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...

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ = 0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. © 2015, American College of Rheumatology.

Jessner's solution vs. 30% salicylic acid peels: a comparative study of the efficacy and safety in mild-to-moderate acne vulgaris.

PubMed

Dayal, Surabhi; Amrani, Ashish; Sahu, Priyadarshini; Jain, Vijay Kumar

2017-03-01

Chemical peeling is a well-identified therapeutic modality for acne vulgaris (AV). Jessner's solution (JS) is a known peeling agent for acne since more than 100 years. Salicylic acid (SA) peel is a well-established peeling agent for acne. There is paucity of literature comparing the current peeling agents of choice, that is, SA with the older peeling agents, that is, JS for acne. To compare the efficacy and safety of 30% SA vs. JS peels in treatment of mild-to-moderate facial acne in Indian patients. A total of 40 patients with mild-to-moderate AV were enrolled for 12 weeks and were randomly divided into two groups: group 1, 30% SA peels and group 2, JS peels were performed 2 weeks apart with total of six peels in 12-week duration. Clinical improvement was assessed objectively using Michaelsson acne scores (MAS) and clinical photographs. Side effects were observed at each visit. At the end of therapy, improvement in MAS and percentage decrease in MAS were significantly higher in group 1 as compared to group 2. Likewise, decrease in mean comedone counts in group 1 was significantly higher as compared to group 2. However, there was no statistically significant difference in the decrease in mean papule and pustule counts between the two groups. Both the groups tolerated the peels well. Thus, 30% SA peels were more effective than JS peels in treatment of noninflammatory lesions, that is, comedones and in overall improvement of mild-to-moderate facial acne vulgaris. © 2016 Wiley Periodicals, Inc.

Features, Treatment, and Outcomes of Macrophage Activation Syndrome in Childhood-Onset Systemic Lupus Erythematosus.

PubMed

Borgia, R Ezequiel; Gerstein, Maya; Levy, Deborah M; Silverman, Earl D; Hiraki, Linda T

2018-04-01

To describe the features and treatment of macrophage activation syndrome (MAS) in a single-center cohort of patients with childhood-onset systemic lupus erythematosus (SLE), and to compare childhood-onset SLE manifestations and outcomes between those with and those without MAS. We included all patients with childhood-onset SLE followed up at The Hospital for Sick Children from 2002 to 2012, and identified those also diagnosed as having MAS. Demographic, clinical, and laboratory features of MAS and SLE, medication use, hospital and pediatric intensive care unit (PICU) admissions, as well as damage indices and mortality data were extracted from the Lupus database. Student's t-tests and Fisher's exact tests were used to compare continuous and categorical variables, respectively. We calculated incidence rate ratios of hospital and PICU admissions comparing patients with and those without MAS, using Poisson models. Kaplan-Meier survival analysis was used to examine the time to disease damage accrual. Of the 403 patients with childhood-onset SLE, 38 (9%) had MAS. The majority (68%) had concomitant MAS and SLE diagnoses. Fever was the most common MAS clinical feature. The frequency of renal and central nervous system disease, hospital admissions, the average daily dose of steroids, and time to disease damage were similar between those with and those without MAS. We observed a higher mortality rate among those with MAS (5%) than those without MAS (0.2%) (P = 0.02). MAS was most likely to develop concomitantly with childhood-onset SLE diagnosis. The majority of the MAS patients were successfully treated with corticosteroids with no MAS relapses. Although the numbers were small, there was a higher risk of death associated with MAS compared to SLE without MAS. © 2018, American College of Rheumatology.

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

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.

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

BUDEM: an urban growth simulation model using CA for Beijing metropolitan area

NASA Astrophysics Data System (ADS)

Long, Ying; Shen, Zhenjiang; Du, Liqun; Mao, Qizhi; Gao, Zhanping

2008-10-01

It is in great need of identifying the future urban form of Beijing, which faces challenges of rapid growth in urban development projects implemented in Beijing. We develop Beijing Urban Developing Model (BUDEM in short) to support urban planning and corresponding policies evaluation. BUDEM is the spatio-temporal dynamic model for simulating urban growth in Beijing metropolitan area, using cellular automata (CA) and Multi-agent system (MAS) approaches. In this phase, the computer simulation using CA in Beijing metropolitan area is conducted, which attempts to provide a premise of urban activities including different kinds of urban development projects for industrial plants, shopping facilities, houses. In the paper, concept model of BUDEM is introduced, which is established basing on prevalent urban growth theories. The method integrating logistic regression and MonoLoop is used to retrieve weights in the transition rule by MCE. After model sensibility analysis, we apply BUDEM into three aspects of urban planning practices: (1) Identifying urban growth mechanism in various historical phases since 1986; (2) Identifying urban growth policies needed to implement desired urban form (BEIJING2020), namely planned urban form; (3) Simulating urban growth scenarios of 2049 (BEIJING2049) basing on the urban form and parameter set of BEIJING2020.

Fluid flow dynamics in MAS systems.

PubMed

Wilhelm, Dirk; Purea, Armin; Engelke, Frank

2015-08-01

The turbine system and the radial bearing of a high performance magic angle spinning (MAS) probe with 1.3mm-rotor diameter has been analyzed for spinning rates up to 67kHz. We focused mainly on the fluid flow properties of the MAS system. Therefore, computational fluid dynamics (CFD) simulations and fluid measurements of the turbine and the radial bearings have been performed. CFD simulation and measurement results of the 1.3mm-MAS rotor system show relatively low efficiency (about 25%) compared to standard turbo machines outside the realm of MAS. However, in particular, MAS turbines are mainly optimized for speed and stability instead of efficiency. We have compared MAS systems for rotor diameter of 1.3-7mm converted to dimensionless values with classical turbomachinery systems showing that the operation parameters (rotor diameter, inlet mass flow, spinning rate) are in the favorable range. This dimensionless analysis also supports radial turbines for low speed MAS probes and diagonal turbines for high speed MAS probes. Consequently, a change from Pelton type MAS turbines to diagonal turbines might be worth considering for high speed applications. CFD simulations of the radial bearings have been compared with basic theoretical values proposing considerably smaller frictional loss values. The discrepancies might be due to the simple linear flow profile employed for the theoretical model. Frictional losses generated inside the radial bearings result in undesired heat-up of the rotor. The rotor surface temperature distribution computed by CFD simulations show a large temperature gradient over the rotor. Copyright © 2015 Elsevier Inc. All rights reserved.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Development and evaluation of a monitoring-aid system for a nuclear power plant in control room system manipulation.

PubMed

Lin, Jhih-Tsong; Chen, Yan-Cheng; Wu, Shih-Chieh; Hwang, Sheue-Ling

2017-01-01

In an advanced nuclear power plant (NPP), the operators are responsible for monitoring a massive number of alarm parameters. To assist the operators, a monitoring-aid system (MAS), that applies four quality control chart methods, was proposed and evaluated. Two types of MAS, namely, text and graph marks, were proposed and compared with the original display. To validate the proposed MAS, 17 professional engineers and operators were invited to join an experiment. Two different system states, normal and abnormal, were simulated. The operators were asked to manipulate the system, monitor the critical parameters, search for operational procedures, and deal with other secondary tasks. The primary and secondary task performance and heart rate were measured. After each task was conducted, three subjective rating questionnaires, namely, mental workload, situation awareness, and preference ratings, were implemented for the proposed MAS and the original system. With the assistance of the MAS, the alarm detection rate, secondary task performance, and subjective mental workload demonstrate significant improvements. The proposed MAS helps the operators monitor critical parameters. Therefore, the MAS should be considered for implementation with the control panel to increase the safety of NPPs. Furthermore, the MAS could reduce the mental workload might decrease the health hazard of the operators.

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.

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.

Towards Time Automata and Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Hutzler, G.; Klaudel, H.; Wang, D. Y.

2004-01-01

The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.

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%.

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.

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ=0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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

High Frequency Dynamic Nuclear Polarization

PubMed Central

Ni, Qing Zhe; Daviso, Eugenio; Can, Thach V.; Markhasin, Evgeny; Jawla, Sudheer K.; Swager, Timothy M.; Temkin, Richard J.; Herzfeld, Judith; Griffin, Robert G.

2013-01-01

Conspectus During the three decades 1980–2010, magic angle spinning (MAS) NMR developed into the method of choice to examine many chemical, physical and biological problems. In particular, a variety of dipolar recoupling methods to measure distances and torsion angles can now constrain molecular structures to high resolution. However, applications are often limited by the low sensitivity of the experiments, due in large part to the necessity of observing spectra of low-γ nuclei such as the I = ½ species 13C or 15N. The difficulty is still greater when quadrupolar nuclei, like 17O or 27Al, are involved. This problem has stimulated efforts to increase the sensitivity of MAS experiments. A particularly powerful approach is dynamic nuclear polarization (DNP) which takes advantage of the higher equilibrium polarization of electrons (which conventionally manifests in the great sensitivity advantage of EPR over NMR). In DNP, the sample is doped with a stable paramagnetic polarizing agent and irradiated with microwaves to transfer the high polarization in the electron spin reservoir to the nuclei of interest. The idea was first explored by Overhauser and Slichter in 1953. However, these experiments were carried out on static samples, at magnetic fields that are low by current standards. To be implemented in contemporary MAS NMR experiments, DNP requires microwave sources operating in the subterahertz regime — roughly 150–660 GHz — and cryogenic MAS probes. In addition, improvements were required in the polarizing agents, because the high concentrations of conventional radicals that are required to produce significant enhancements compromise spectral resolution. In the last two decades scientific and technical advances have addressed these problems and brought DNP to the point where it is achieving wide applicability. These advances include the development of high frequency gyrotron microwave sources operating in the subterahertz frequency range. In addition, low temperature MAS probes were developed that permit in-situ microwave irradiation of the samples. And, finally, biradical polarizing agents were developed that increased the efficiency of DNP experiments by factors of ~4 at considerably lower paramagnet concentrations. Collectively these developments have made it possible to apply DNP on a routine basis to a number of different scientific endeavors, most prominently in the biological and material sciences. This Account reviews these developments, including the primary mechanisms used to transfer polarization in high frequency DNP, and the current choice of microwave sources and biradical polarizing agents. In addition, we illustrate the utility of the technique with a description of applications to membrane and amyloid proteins that emphasizes the unique structural information that is available in these two cases. PMID:23597038

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.

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.

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.

A distributed control approach for power and energy management in a notional shipboard power system

NASA Astrophysics Data System (ADS)

Shen, Qunying

The main goal of this thesis is to present a power control module (PCON) based approach for power and energy management and to examine its control capability in shipboard power system (SPS). The proposed control scheme is implemented in a notional medium voltage direct current (MVDC) integrated power system (IPS) for electric ship. To realize the control functions such as ship mode selection, generator launch schedule, blackout monitoring, and fault ride-through, a PCON based distributed power and energy management system (PEMS) is developed. The control scheme is proposed as two-layer hierarchical architecture with system level on the top as the supervisory control and zonal level on the bottom as the decentralized control, which is based on the zonal distribution characteristic of the notional MVDC IPS that was proposed as one of the approaches for Next Generation Integrated Power System (NGIPS) by Norbert Doerry. Several types of modules with different functionalities are used to derive the control scheme in detail for the notional MVDC IPS. Those modules include the power generation module (PGM) that controls the function of generators, the power conversion module (PCM) that controls the functions of DC/DC or DC/AC converters, etc. Among them, the power control module (PCON) plays a critical role in the PEMS. It is the core of the control process. PCONs in the PEMS interact with all the other modules, such as power propulsion module (PPM), energy storage module (ESM), load shedding module (LSHED), and human machine interface (HMI) to realize the control algorithm in PEMS. The proposed control scheme is implemented in real time using the real time digital simulator (RTDS) to verify its validity. To achieve this, a system level energy storage module (SESM) and a zonal level energy storage module (ZESM) are developed in RTDS to cooperate with PCONs to realize the control functionalities. In addition, a load shedding module which takes into account the reliability of power supply (in terms of quality of service) is developed. This module can supply uninterruptible power to the mission critical loads. In addition, a multi-agent system (MAS) based framework is proposed to implement the PCON based PEMS through a hardware setup that is composed of MAMBA boards and FPGA interface. Agents are implemented using Java Agent DEvelopment Framework (JADE). Various test scenarios were tested to validate the approach.

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.

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.

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).

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

Agent-based user-adaptive service provision in ubiquitous systems

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

The MicroMAS CubeSat Mission

NASA Astrophysics Data System (ADS)

Cahoy, K.; Blackwell, W. J.; Allen, G.; Bury, M.; Efromson, R.; Galbraith, C.; Hancock, T.; Leslie, V.; Osaretin, I.; Retherford, L.; Scarito, M.; Shields, M.; Toher, D.; Wight, K.; Miller, D.; Marinan, A.; Paek, S.; Peters, E.; Schmidt, F. H.; Alvisio, B.; Wise, E.; Masterson, R.; Franzim Miranda, D.; Crail, C.; Kingsbury, R.; Souffrant, A.; Orrego, L.; Eslinger, G.; Nicholas, A.; Pong, C.

2012-12-01

The recently published Midterm Assessment of NASA's Implementation of the Decadal Survey finds that, "The nation's Earth observing system is beginning a rapid decline in capability as long-running missions end and key new missions are delayed, lost, or canceled. The projected loss of observing capability could have significant adverse consequences for science and society." In this presentation, we explore low-cost, mission-flexible, and rapidly deployable spaceborne sensors that can meet stringent performance requirements pervading the NASA Earth Science measurement programs, including especially the recommended NRC Decadal Survey missions. New technologies have enabled a novel approach toward this science observational goal, and in this paper we describe recent technology develop efforts to address the challenges above through the use of CubeSat radiometers. The Micro-sized Microwave Atmospheric Satellite (MicroMAS) is a 3U cubesat (30x10x10 cm, ~4kg) hosting a passive microwave spectrometer operating near the 118.75-GHz oxygen absorption line. The focus of the first MicroMAS mission (hereafter, MicroMAS-1) is to observe convective thunderstorms, tropical cyclones, and hurricanes from a near-equatorial orbit at approximately 500-km altitude. A MicroMAS flight unit is currently being developed in anticipation of a 2014 launch to be provided by NASA. A parabolic reflector is mechanically rotated as the spacecraft orbits the earth, thus directing a cross-track scanned beam with FWHM beamwidth of 2.4-degrees, yielding an approximately 25-km diameter footprint from a nominal altitude of 500 km. Radiometric calibration is carried out using observations of cold space, the earth's limb, and an internal noise diode that is weakly coupled through the RF front-end electronics. A key technology feature is the development of an ultra-compact intermediate frequency processor module for channelization, detection, and A-to-D conversion. The antenna system and RF front-end electronics are highly integrated and miniaturized. A MicroMAS-2 mission is currently being planned using a multi-band spectrometer operating near 118 and 183 GHz in a sun-synchronous orbit of approximately 800-km altitude. A HyMAS-1 (Hyperspectral Microwave Atmospheric Satellite) mission with approximately 50 channels near 118 and 183 GHz is also being planned. In this talk, the mission concept of operations will be discussed, the radiometer payload will be described, and the spacecraft subsystems (avionics, power, communications, attitude determination and control, and mechanical structures) will be summarized. Test data from the recently completed MicroMAS Engineering Development Model (EDM) will also be presented. This work was sponsored by the National Oceanic and Atmospheric Administration under Air Force contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and not necessarily endorsed by the United States Government.

New agents modulating the renin-angiotensin-aldosterone system—Will there be a new therapeutic option?

PubMed Central

Szoka, Piotr; Kolodziejczyk, Patrycjusz; Kramkowski, Karol; Wojewodzka-Zelezniakowicz, Marzena; Chabielska, Ewa

2016-01-01

The renin-angiotensin-aldosterone system (RAAS) is more complex than it was originally regarded. According to the current subject knowledge, there are two main axes of the RAAS: (1) angiotensin-converting enzyme (ACE)-angiotensin II-AT1 receptor axis and (2) ACE2-angiotensin-(1-7)-Mas receptor axis. The activation of the first axis leads to deleterious effects, including vasoconstriction, endothelial dysfunction, thrombosis, inflammation, and fibrosis; therefore, blocking the components of this axis is a highly rational and commonly used therapeutic procedure. The ACE2-Ang-(1-7)-Mas receptor axis has a different role, since it often opposes the effects induced by the classical ACE-Ang II-AT1 axis. Once the positive effects of the ACE2-Ang-(1-7)-Mas axis were discovered, the alternative ways of pharmacotherapy activating this axis of RAAS appeared. This article briefly describes new molecules affecting the RAAS, namely: recombinant human ACE2, ACE2 activators, angiotensin-(1-7) peptide and non-peptide analogs, aldosterone synthase inhibitors, and the third and fourth generation of mineralocorticoid receptor antagonists. The results of the experimental and clinical studies are encouraging, which leads us to believe that these new molecules can support the treatment of cardiovascular diseases as well as cardiometabolic disorders. PMID:27439538

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 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.

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.

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 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.

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

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.

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.

Macrophage activation syndrome in children with systemic juvenile idiopathic arthritis and systemic lupus erythematosus.

PubMed

Aytaç, Selin; Batu, Ezgi Deniz; Ünal, Şule; Bilginer, Yelda; Çetin, Mualla; Tuncer, Murat; Gümrük, Fatma; Özen, Seza

2016-10-01

Macrophage activation syndrome (MAS) is a hyper-inflammatory disorder secondary to a rheumatic disease such as systemic juvenile idiopathic arthritis (SJIA) and systemic lupus erythematosus (SLE). We aimed to present the characteristics of our pediatric MAS patients. Clinical features, laboratory parameters, treatment, and outcome of 34 patients (28 SJIA; six SLE; 37 MAS episodes) followed at a tertiary health center between 2009 and 2015 were retrospectively reviewed. The median age at MAS onset was 11 years. More SJIA patients had MAS at disease onset than SLE patients (53.6 vs. 16.7 %). Fever, high C-reactive protein and hyperferritinemia were present in all MAS episodes. Rash was less (p = 0.03), and fatigue was more frequent (p = 0.042) in SLE than SJIA patients. All received corticosteroids. Cyclosporine was given in 74.2 % of SJIA-MAS; 66.7 % of SLE-MAS episodes. Intravenous immunoglobulin, anakinra, or etoposide was administered during 67.7; 41.9; 32.3 % of SJIA-MAS and 33.3; 33.3; 50 % of SLE-MAS episodes, respectively. Plasmapheresis was performed during 41.9 % of SJIA-MAS and 33.3 % of SLE-MAS episodes. The mortality rate was 11.8 % (n = 4;3 SJIA, 1 SLE). Hepatosplenomegaly was more frequent (p = 0.005), and plasmapheresis was performed more frequently (p = 0.021) in the patients who died compared to the cured patients. The median duration between symptom onset and admission to our hospital was longer among the patients who died (16.5 vs. 7 days; p = 0.049). Our patients' characteristics were similar to the reported cases, but our mortality rate is slightly higher probably due to late referral to our center. Early diagnosis and effective treatment are crucial to prevent mortality.

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.

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.

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.

A Vision in Jeopardy: Royal Navy Maritime Autonomous Systems (MAS)

DTIC Science & Technology

2017-03-31

Chapter 6 will propose a new MAS vision for the RN. However, before doing so, a fresh look at the problem is required. Consensus of the Problem, Not the... assessment , the RN has failed to deliver any sustainable MAS operational capability. A vision for MAS finally materialized in 2014. Yet, the vision...continuous investment and assessment , the RN has failed to deliver any sustainable MAS operational capability. A vision for MAS finally materialized in

Solid-state dynamic nuclear polarization at 263 GHz: spectrometer design and experimental results†

PubMed Central

Rosay, Melanie; Tometich, Leo; Pawsey, Shane; Bader, Reto; Schauwecker, Robert; Blank, Monica; Borchard, Philipp M.; Cauffman, Stephen R.; Felch, Kevin L.; Weber, Ralph T.; Temkin, Richard J.; Griffin, Robert G.; Maas, Werner E.

2015-01-01

Dynamic Nuclear Polarization (DNP) experiments transfer polarization from electron spins to nuclear spins with microwave irradiation of the electron spins for enhanced sensitivity in nuclear magnetic resonance (NMR) spectroscopy. Design and testing of a spectrometer for magic angle spinning (MAS) DNP experiments at 263 GHz microwave frequency, 400 MHz 1H frequency is described. Microwaves are generated by a novel continuous-wave gyrotron, transmitted to the NMR probe via a transmission line, and irradiated on a 3.2 mm rotor for MAS DNP experiments. DNP signal enhancements of up to 80 have been measured at 95 K on urea and proline in water–glycerol with the biradical polarizing agent TOTAPOL. We characterize the experimental parameters affecting the DNP efficiency: the magnetic field dependence, temperature dependence and polarization build-up times, microwave power dependence, sample heating effects, and spinning frequency dependence of the DNP signal enhancement. Stable system operation, including DNP performance, is also demonstrated over a 36 h period. PMID:20449524

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.

Successful control of juvenile dermatomyositis-associated macrophage activation syndrome and interstitial pneumonia: distinct kinetics of interleukin-6 and -18 levels.

PubMed

Wakiguchi, Hiroyuki; Hasegawa, Shunji; Hirano, Reiji; Kaneyasu, Hidenobu; Wakabayashi-Takahara, Midori; Ohga, Shouichi

2015-11-18

Macrophage activation syndrome (MAS) is the secondary hemophagocytic lymphohistiocytosis associated with rheumatic diseases. Recently, the different cytokine profiles between systemic juvenile idiopathic arthritis (sJIA)-associated MAS (sJIA-MAS) and juvenile systemic lupus erythematosus (JSLE)-associated MAS (JSLE-MAS) were reported. However, there is little information about juvenile dermatomyositis (JDM)-associated MAS (JDM-MAS). A 4-year-old girl with JDM was hospitalized because of fever, erythema, hepatosplenomegaly, cytopenia, liver dysfunction and coagulopathy. Bone marrow aspiration revealed appreciable numbers of activated and hemophagocytosing macrophages. She was diagnosed as having JDM-MAS complicated with interstitial pneumonia (IP) based on the findings of the elevation of serum Krebs von den Lungen-6 (KL-6) levels and chest computed tomography findings. We analyzed circulating levels of interleukin (IL)-2,4,6,10,18, tumor necrosis factor-α and interferon-γ in the patient. Hypercytokinemia occurred at the diagnosis of MAS and IP, showing with the prominent elevations of IL-6 and IL-18 levels. The cytokine profiles were distinct from those reported in patients with sJIA-MAS or JSLE-MAS. High-dose corticosteroid and cyclosporine therapy led to a drastic improvement of MAS with decreased IL-6 levels. Subsequent cyclophosphamide therapy successfully controlled IP, paralleled with the declining pattern of IL-18 and KL-6 levels. This is the first report to describe a successful treatment and the cytokine profile of JDM-MAS and IP. Serum IL-6 and IL-18 levels may be useful for predicting the disease activity of JDM-MAS and IP, respectively.

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.

Leader–follower fixed-time consensus of multi-agent systems with high-order integrator dynamics

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

Tian, Bailing; Zuo, Zongyu; Wang, Hong

The leader-follower fixed-time consensus of high-order multi-agent systems with external disturbances is investigated in this paper. A novel sliding manifold is designed to ensure that the tracking errors converge to zero in a fixed-time during the sliding motion. Then, a distributed control law is designed based on Lyapunov technique to drive the system states to the sliding manifold in finite-time independent of initial conditions. Finally, the efficiency of the proposed method is illustrated by numerical simulations.

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.

Shrimp serine proteinase homologues PmMasSPH-1 and -2 play a role in the activation of the prophenoloxidase system.

PubMed

Jearaphunt, Miti; Amparyup, Piti; Sangsuriya, Pakkakul; Charoensapsri, Walaiporn; Senapin, Saengchan; Tassanakajon, Anchalee

2015-01-01

Melanization mediated by the prophenoloxidase (proPO) activating system is a rapid immune response used by invertebrates against intruding pathogens. Several masquerade-like and serine proteinase homologues (SPHs) have been demonstrated to play an essential role in proPO activation in insects and crustaceans. In a previous study, we characterized the masquerade-like SPH, PmMasSPH1, in the black tiger shrimp Penaeus monodon as a multifunctional immune protein based on its recognition and antimicrobial activity against the Gram-negative bacteria Vibrio harveyi. In the present study, we identify a novel SPH, known as PmMasSPH2, composed of an N-terminal clip domain and a C-terminal SP-like domain that share high similarity to those of other insect and crustacean SPHs. We demonstrate that gene silencing of PmMasSPH1 and PmMasSPH2 significantly reduces PO activity, resulting in a high number of V. harveyi in the hemolymph. Interestingly, knockdown of PmMasSPH1 suppressed not only its gene transcript but also other immune-related genes in the proPO system (e.g., PmPPAE2) and antimicrobial peptides (e.g., PenmonPEN3, PenmonPEN5, crustinPm1 and Crus-likePm). The PmMasSPH1 and PmMasSPH2 also show binding activity to peptidoglycan (PGN) of Gram-positive bacteria. Using a yeast two-hybrid analysis and co-immunoprecipitation, we demonstrate that PmMasSPH1 specifically interacted with the final proteinase of the proPO cascade, PmPPAE2. Furthermore, the presence of both PmMasSPH1 and PmPPAE2 enhances PGN-induced PO activity in vitro. Taken together, these results suggest the importance of PmMasSPHs in the activation of the shrimp proPO system.

Shrimp Serine Proteinase Homologues PmMasSPH-1 and -2 Play a Role in the Activation of the Prophenoloxidase System

PubMed Central

Jearaphunt, Miti; Amparyup, Piti; Sangsuriya, Pakkakul; Charoensapsri, Walaiporn; Senapin, Saengchan; Tassanakajon, Anchalee

2015-01-01

Melanization mediated by the prophenoloxidase (proPO) activating system is a rapid immune response used by invertebrates against intruding pathogens. Several masquerade-like and serine proteinase homologues (SPHs) have been demonstrated to play an essential role in proPO activation in insects and crustaceans. In a previous study, we characterized the masquerade-like SPH, PmMasSPH1, in the black tiger shrimp Penaeus monodon as a multifunctional immune protein based on its recognition and antimicrobial activity against the Gram-negative bacteria Vibrio harveyi. In the present study, we identify a novel SPH, known as PmMasSPH2, composed of an N-terminal clip domain and a C-terminal SP-like domain that share high similarity to those of other insect and crustacean SPHs. We demonstrate that gene silencing of PmMasSPH1 and PmMasSPH2 significantly reduces PO activity, resulting in a high number of V. harveyi in the hemolymph. Interestingly, knockdown of PmMasSPH1 suppressed not only its gene transcript but also other immune-related genes in the proPO system (e.g., PmPPAE2) and antimicrobial peptides (e.g., PenmonPEN3, PenmonPEN5, crustinPm1 and Crus-likePm). The PmMasSPH1 and PmMasSPH2 also show binding activity to peptidoglycan (PGN) of Gram-positive bacteria. Using a yeast two-hybrid analysis and co-immunoprecipitation, we demonstrate that PmMasSPH1 specifically interacted with the final proteinase of the proPO cascade, PmPPAE2. Furthermore, the presence of both PmMasSPH1 and PmPPAE2 enhances PGN-induced PO activity in vitro. Taken together, these results suggest the importance of PmMasSPHs in the activation of the shrimp proPO system. PMID:25803442

Association of IRF5 polymorphisms with susceptibility to macrophage activation syndrome in patients with juvenile idiopathic arthritis.

PubMed

Yanagimachi, Masakatsu; Naruto, Takuya; Miyamae, Takako; Hara, Takuma; Kikuchi, Masako; Hara, Ryoki; Imagawa, Tomoyuki; Mori, Masaaki; Sato, Hidenori; Goto, Hiroaki; Yokota, Shumpei

2011-04-01

Systemic-onset juvenile idiopathic arthritis (systemic JIA) and macrophage activation syndrome (MAS), the most devastating complication of systemic JIA, are characterized by abnormal levels of proinflammatory cytokines. Interferon regulatory factor 5 (IRF5) is a member of the IRF family of transcription factors, and acts as a master transcription factor in the activation of genes encoding proinflammatory cytokines. Polymorphisms in the IRF5 gene have been associated with susceptibility to autoimmune diseases such as systemic lupus erythematosus (SLE) and rheumatoid arthritis. Our aim was to assess associations of IRF5 gene polymorphisms with susceptibility to systemic JIA and MAS. Three IRF5 single-nucleotide polymorphisms (rs729302, rs2004640, and rs2280714) were genotyped using TaqMan assays in 81 patients with systemic JIA (33 with MAS, 48 without) and 190 controls. There were no associations of the IRF5 gene polymorphisms or haplotypes under study with susceptibility to systemic JIA. There was a significant association of the rs2004640 T allele with MAS susceptibility (OR 4.11; 95% CI 1.84, 9.16; p = 0.001). The IRF5 haplotype (rs729302 A, rs2004640 T, and rs2280714 T), which was reported as conferring an increased risk of SLE, was significantly associated with MAS susceptibility in patients with systemic JIA (OR 4.61; 95% CI 1.73, 12.3; p < 0.001). IRF5 gene polymorphism is a genetic factor influencing susceptibility to MAS in patients with systemic JIA, and IRF5 contributes to the pathogenesis of MAS in these patients.

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.

Solvent signal suppression for high-resolution MAS-DNP

NASA Astrophysics Data System (ADS)

Lee, Daniel; Chaudhari, Sachin R.; De Paëpe, Gaël

2017-05-01

Dynamic nuclear polarization (DNP) has become a powerful tool to substantially increase the sensitivity of high-field magic angle spinning (MAS) solid-state NMR experiments. The addition of dissolved hyperpolarizing agents usually results in the presence of solvent signals that can overlap and obscure those of interest from the analyte. Here, two methods are proposed to suppress DNP solvent signals: a Forced Echo Dephasing experiment (FEDex) and TRAnsfer of Populations in DOuble Resonance Echo Dephasing (TRAPDORED) NMR. These methods reintroduce a heteronuclear dipolar interaction that is specific to the solvent, thereby forcing a dephasing of recoupled solvent spins and leaving acquired NMR spectra free of associated resonance overlap with the analyte. The potency of these methods is demonstrated on sample types common to MAS-DNP experiments, namely a frozen solution (of L-proline) and a powdered solid (progesterone), both containing deuterated glycerol as a DNP solvent. The proposed methods are efficient, simple to implement, compatible with other NMR experiments, and extendable past spectral editing for just DNP solvents. The sensitivity gains from MAS-DNP in conjunction with FEDex or TRAPDORED then permits rapid and uninterrupted sample analysis.

Radio Measurements of the Stellar Proper Motions in the Core of the Orion Nebula Cluster

NASA Astrophysics Data System (ADS)

Dzib, Sergio A.; Loinard, Laurent; Rodríguez, Luis F.; Gómez, Laura; Forbrich, Jan; Menten, Karl M.; Kounkel, Marina A.; Mioduszewski, Amy J.; Hartmann, Lee; Tobin, John J.; Rivera, Juana L.

2017-01-01

Using multi-epoch Very Large Array observations, covering a time baseline of 29.1 years, we have measured the proper motions of 88 young stars with compact radio emission in the core of the Orion Nebula Cluster (ONC) and the neighboring BN/KL region. Our work increases the number of young stars with measured proper motion at radio frequencies by a factor of 2.5 and enables us to perform a better statistical analysis of the kinematics of the region than was previously possible. Most stars (79 out of 88) have proper motions consistent with a Gaussian distribution centered on \\overline{{μ }α \\cos δ }=1.07+/- 0.09 mas yr-1, and \\overline{{μ }δ }=-0.84+/- 0.16 mas yr-1, with velocity dispersions of {σ }α =1.08+/- 0.07 mas yr-1, {σ }δ =1.27+/- 0.15 mas yr-1. We looked for organized movements of these stars but found no clear indication of radial expansion/contraction or rotation. The remaining nine stars in our sample show peculiar proper motions that differ from the mean proper motions of the ONC by more than 3σ. One of these stars, V 1326 Ori, could have been expelled from the Orion Trapezium 7000 years ago. Two could be related to the multi-stellar disintegration in the BN/KL region, in addition to the previously known sources BN, I and n. The others either have high uncertainties (so their anomalous proper motions are not firmly established) or could be foreground objects.

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.

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.

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.

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.

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.

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.

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

Land Surface Temperature Measurements from EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1997-01-01

We applied the multi-method strategy of land-surface temperature (LST) and emissivity measurements in two field campaigns this year for validating the MODIS LST algorithm. The first field campaign was conducted in Death Valley, CA, on March 3rd and the second one in Railroad Valley, NV, on June 23-27. ER2 MODIS Airborne Simulator (MAS) data were acquired in morning and evening for these two field campaigns. TIR spectrometer, radiometer, and thermistor data were also collected in the field campaigns. The LST values retrieved from MAS data with the day/night LST algorithm agree with those obtained from ground-based measurements within 1 C and show close correlations with topographic maps. The band emissivities retrieved from MAS data show close correlations with geological maps in the Death Valley field campaign. The comparison of measurement data in the latest Railroad Valley field campaign indicates that we are approaching the goals of the LST validation: LST uncertainty less than 0.5 C, and emissivity uncertainty less than 0.005 in the 10-13 spectral range. Measurement data show that the spatial variation in LST is the major uncertainty in the LST validation. In order to reduce this uncertainty, a new component of the multi-method strategy has been identified.

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

Toleration and the Design of Norms.

PubMed

Floridi, Luciano

2015-10-01

One of the pressing challenges we face today-in a post-Westphalian order (emergence of the state as the modern, political information agent) and post-Bretton Woods world (emergence of non-state multiagent systems or MASs as "hyperhistorical" players in the global economy and politics)-is how to design the right kind of MAS that can take full advantage of the socio-economic and political progress made so far, while dealing successfully with the new global challenges that are undermining the best legacy of that very progress. This is the topic of the article. In it, I argue that (i) in order to design the right kind of MAS, we need to design the right kind of norms that constitute them; (ii) in order to design the right kind of constitutive norms, we need to identify and adopt the right kind of principles of normative design; (iii) toleration is one of those principles; (iv) unfortunately, its role as a foundation for the design of norms has been undermined by the "paradox of toleration"; (v) however, the paradox can be solved; (vi) so toleration can be re-instated as the right kind of foundational principle for the design of the right kind of norms that can constitute the right kind of MAS that can operate across cultures, societies and states, to help us to tackle the new global challenges facing us.

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Decomposition of adsorbed VX on activated carbons studied by {sup 31}P MAS NMR

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

Ishay Columbus; Daniel Waysbort; Liora Shmueli

2006-06-15

The fate of the persistent OP nerve agent O-ethyl S-(2-(diisopropylamino)ethyl) methylphosphonothioate (VX) on granular activated carbons that are used for gas filtration was studied by means of 31P magic angle spinning (MAS) NMR spectroscopy. Four types of activated carbon were used, including coal-based BPL. VX as vapor or liquid was adsorbed on carbon granules, and MAS NMR spectra were recorded periodically. The results show that at least 90% of the adsorbed VX decomposes within 20 days or less to the nontoxic ethyl methylphosphonic acid (EMPA) and bis(S-2-diisopropylaminoethane) ((DES){sub 2}). Decomposition occurred irrespective of the phase from which VX was loaded,more » the presence of metal impregnation on the carbon surface, and the water content of the carbon. Theoretical and practical aspects of the degradation are discussed. 17 refs., 6 figs., 3 tabs.« less

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…

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

Investigation of fluorocarbon blowing agents in insulating polymer foams by 19F NMR imaging.

PubMed

Fyfe, C A; Mei, Z; Grondey, H

1996-01-01

Currently, there is no reliable and readily accessible technique with which the distribution and diffusion of blowing agents in rigid insulating foams can be detected and monitored. In this paper, we demonstrate that 19F NMR microscopic imaging together with 19F solid-state MAS NMR spectroscopy is ideally suited for such measurements and yield quantitatively reliable information that will be critical to the development and fabrication of optimized insulating materials with alternative blowing agents. Polystyrene (PS) and polyurethane (PU) foam samples were investigated with the objective of determining quantitatively the amount of blowing agents in the gaseous phase and dissolved in the polymer phase, and to determine and monitor the distribution of the blowing agents in aged foams as a function of time and temperature. The concentrations of the gaseous blowing agents in the cells and dissolved in the solid were simultaneously and quantitatively measured by 19F MAS NMR spectroscopy. An unfaced 1-yr-old PS foam filled with CH3CF2Cl has about 13% of total HCFCs dissolved in the solid; while there is about 24% of HCFCs in the solid of a faced 3-mos-old PU foam filled with CH3CCl2F. The data from 19F NMR imaging demonstrate that the distributions of the blowing agents in an aged foam are quite uniform around the center part (2 cm away from any edge) of a foam board; however, a gradient in blowing agent concentration was found as a function of distance from the initial factory cut edge. The effective diffusion coefficients of the blowing agents can be directly calculated from the imaging data. Quantitative diffusion constants and activation barriers were determined. Additionally, a foam treated with a second blowing agent was monitored with chemical shift selective imaging and the diffusion of the second gas into the foam and the out-diffusion of the original gas were determined.

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.

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.

U.S. Geological Survey mineral databases; MRDS and MAS/MILS

USGS Publications Warehouse

McFaul, E.J.; Mason, G.T.; Ferguson, W.B.; Lipin, B.R.

2000-01-01

These two CD-ROM's contain the latest version of the Mineral Resources Data System (MRDS) database and the Minerals Availability System/Minerals Industry Location System (MAS/MILS) database for coverage of North America and the world outside North America. The records in the MRDS database each contain almost 200 data fields describing metallic and nonmetallic mineral resources, deposits, and commodities. The records in the MAS/MILS database each contain almost 100 data fields describing mines and mineral processing plans.

MAS2-8 radar and digital control unit

NASA Technical Reports Server (NTRS)

Oberg, J. M.; Ulaby, F. T.

1974-01-01

The design of the MAS 2-8 (2 to 8 GHz microwave-active spectrometer), a ground-based sensor system, is presented. A major modification in 1974 to the MAS 2-8, that of a control subsystem to automate the data-taking operation, is the prime focus. The digital control unit automatically changes all system parameters except FM rate and records the return signal on paper tape. The overall system operation and a detailed discussion of the design and operation of the digital control unit are presented.

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.

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.

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.

Synthesis and characterization of magnesium aluminate (MgAl2O4) spinel (MAS) thin films

NASA Astrophysics Data System (ADS)

Ahmad, Syed Muhammad; Hussain, Tousif; Ahmad, Riaz; Siddiqui, Jamil; Ali, Dilawar

2018-01-01

In a quest to identify more economic routes for synthesis of magnesium aluminate (MgAl2O4) spinel (MAS) thin films, dense plasma focus device was used with multiple plasma focus shots. Structural, bonding between composite films, surface morphological, compositional and hardness properties of MAS thin films were investigated by using x-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive x-rays (EDX) analysis and Vickers micro hardness test respectively. In XRD graph, the presence of MgAl2O4 diffraction peaks in crystallographic orientations (222), (400) and (622) pointed out the successful formation of polycrystalline thin films of MgAl2O4 with face centered cubic structure. The FTIR spectrums showed a major common transmittance band at 697.95 cm-1 which belongs to MgAl2O4. SEM micrographs illustrated a mesh type, granular and multi layers microstructures with significant melting effects. EDX spectrum confirmed the existence of magnesium, oxygen and aluminum in MAS films. A common increasing behavior in micro-hardness of composite MgAl2O4 films by increasing number of plasma focus shots was found.

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.

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

Revisiting LS I +61°303 with VLBI astrometry

NASA Astrophysics Data System (ADS)

Wu, Y. W.; Torricelli-Ciamponi, G.; Massi, M.; Reid, M. J.; Zhang, B.; Shao, L.; Zheng, X. W.

2018-03-01

We conducted multi-epoch Very Long Baseline Array (VLBA) phase-referenced observations of LS I +61°303 in order to study its precessing radio jet. Compared to similar observations in 2006, we find that the observed elliptical trajectory of emission at 8.4 GHz repeats after the 9 yr gap. The accurate alignment of the emission patterns yields a precession period of 26.926 ± 0.005 d, which is consistent with that determined by Lomb-Scargle analysis of the radio light curve. We analytically model the projection on the sky plane of the peak position of a precessing, synchrotron-emitting jet, which traces an elliptical trajectory on the sky. Comparing the simulation with the VLBA astrometry we improve our knowledge of the geometry of the system. We measure the LS I +61°303 absolute proper motion to be -0.150 ± 0.006 mas yr-1 eastward and -0.264 ± 0.006 mas yr-1 northward. Removing Galactic rotation, this reveals a small, <20 km s-1, non-circular motion, which indicates a very low kick velocity when the black hole was formed.

A Cognitive Game Theoretic Analysis of Conflict Alerts in Air Traffic Control

NASA Technical Reports Server (NTRS)

Erev, Ido; Gopher, Daniel; Remington, Roger

1999-01-01

The current research was motivated by the recommendation made by a joint Government/Industry committee to introduce a new traffic control system, referred to as the Free Flight. This system is designed to use recent new technology to facilitate efficient and safe air transportation. We addressed one of the major difficulties that arise in the design of this and similar multi-agent systems: the adaptive (and slippery) nature of human agents. To facilitate a safe and efficient design of this multi-agent system, designers have to rely on assessments of the expected behavior of the different agents under various scenarios. Whereas the behavior of the computerized agents is predictable, the behavior of the human agents (including air traffic controllers and pilots) is not. Experimental and empirical observations suggest that human agents are likely to adjust their behavior to the design of the system. To see the difficulty that the adaptive nature of human agents creates assume that a good approximation of the way operators currently behave is available. Given this information an optimal design can be performed. The problem arises as the human operator will learn to adjust their behavior to the new system. Following this adjustment process the assumptions made by the designer concerning the operators behavior will no longer be accurate and the system might reach a suboptimal state. In extreme situations these potential suboptimal states might involve unnecessary risk. That is, the fact that operators learn in an adaptive fashion does not imply that the system will become safer as they gain experience. At least in the context of Safety dilemmas, experience can lead to a pareto deficient risk taking behavior.

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.

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

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

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.

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.

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.

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

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.

Economic Cost and Benefits of Subsidizing Western Credits to the East,

DTIC Science & Technology

1984-07-01

Germany, a private insurance company acting as agent for the German government; the export credits guarantee depart- ment (ECGD) in Great Britain, which...arrive at better estimates of perceived default risks directly, by analyzing the various ways in which agents in the financial markets protect...Bloc countries had been very good, and he also ’until won, ma v would hm ame that the uan oall e ot Bloe count= u wee the mas a for the Sovet Union

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.

In vitro comparisons of the inhibitory activity of florfenicol copper sulfate and potassium permanganate towards Aeromonas hydrophila and Flavobacterium columnare

USDA-ARS?s Scientific Manuscript database

Aeromonas hydrophila and Flavobacterium columnare, the etiological agents of motile aeromonas septicemia (MAS) and columnaris disease, respectively, have been recently causing crippling moralities to the sunshine bass, Morone chrysops female X Morone saxatilis male (Percichthyidae), industry in the ...

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.

Radiation dose reduction in chest radiography using a flat-panel amorphous silicon detector.

PubMed

Hosch, W P; Fink, C; Radeleff, B; kampschulte a, A; Kauffmann, G W; Hansmann, J

2002-10-01

The aim of this study was to evaluate the image quality and the potential for radiation dose reduction with a digital flat-panel amorphous silicon detector radiography system. Using flat-panel technology, radiographs of an anthropomorphic thorax phantom were taken with a range of technical parameters (125kV, 200mA and 5, 4, 3.2, 2, 1, 0.5, and 0.25mAs) which were equivalent to a radiation dose of 332, 263, 209, 127, 58.7, 29, and 14 microGy, respectively. These images were compared to radiographs obtained by a conventional film-screen radiography system at 125kV, 200mA and 5mAs (equivalent to 252 microGy) which served as reference. Three observers evaluated independently the visibility of simulated rounded lesions and anatomical structures, comparing printed films from the flat-panel amorphous silicon detector and conventional x-ray system films. With flat-panel technology, the visibility of rounded lesions and normal anatomical structures at 5, 4, and 3.2mAs was superior compared to the conventional film-screen radiography system. (P< or =0.0001). At 2mAs, improvement was only marginal (P=0.19). At 1.0, 0.5 and 0.25mAs, the visibility of simulated rounded lesions was worse (P< or =0.004). Comparing fine lung parenchymal structures, the flat-panel amorphous silicon detector showed improvement for all exposure levels down to 2mAs and equality at 1mAs. Compared to a conventional x-ray film system, the flat-panel amorphous silicon detector demonstrated improved image quality and the possibility for a reduction of the radiation dose by 50% without loss in image quality.

MAS-NMR investigations of the crystallization behaviour of lithium aluminum silicate (LAS) glasses containing P 2O 5 and TiO 2 nucleants

NASA Astrophysics Data System (ADS)

Ananthanarayanan, A.; Kothiyal, G. P.; Montagne, L.; Revel, B.

2010-06-01

Lithium aluminum silicate (LAS) glass of composition (mol%) 20.4Li 2O-4.0Al 2O 3-68.6SiO 2-3.0K 2O-2.6B 2O 3-0.5P 2O 5-0.9TiO 2 was prepared by melt quenching. The glass was then nucleated and crystallized based on differential thermal analysis (DTA) data and was characterized by 29Si, 31P, 11B and 27Al MAS-NMR. XRD and 29Si NMR showed that lithium metasilicate (Li 2SiO 3) is the first phase to c form followed by cristobalite (SiO 2) and lithium disilicate (Li 2Si 2O 5). 29Si MAS-NMR revealed a change in the network structure already for the glasses nucleated at 550 °C. Since crystalline Li 3PO 4, as observed by 31P MAS-NMR, forms concurrently with the silicate phases, we conclude that crystalline Li 3PO 4 does not act as a nucleating agent for lithium silicate phases. Moreover, 31P NMR indicates the formation of M-PO 4 ( M=B, Al or Ti) complexes. The presence of BO 3 and BO 4 structural units in all the glass/glass-ceramic samples is revealed through 11B MAS-NMR. B remains in the residual glass and the crystallization of silicate phases causes a reduction in the number of alkali ions available for charge compensation. As a result, the number of trigonally coordinated B (BO 3) increases at the expense of tetrahedrally coordinated B (BO 4). The 27Al MAS-NMR spectra indicate the presence of tetrahedrally coordinated Al species, which are only slightly perturbed by the crystallization.

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

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.

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

WASP-12b and HAT-P-8b are Members of Triple Star Systems

NASA Astrophysics Data System (ADS)

Bechter, Eric B.; Crepp, Justin R.; Ngo, Henry; Knutson, Heather A.; Batygin, Konstantin; Hinkley, Sasha; Muirhead, Philip S.; Johnson, John Asher; Howard, Andrew W.; Montet, Benjamin T.; Matthews, Christopher T.; Morton, Timothy D.

2014-06-01

We present high spatial resolution images that demonstrate that WASP-12b and HAT-P-8b orbit the primary stars of hierarchical triple star systems. In each case, two distant companions with colors and brightnesses consistent with M dwarfs co-orbit the hot Jupiter planet host as well as one another. Our adaptive optics images spatially resolve the secondary around WASP-12, previously identified by Bergfors et al. and Crossfield et al. into two distinct sources separated by 84.3 ± 0.6 mas (21 ± 3 AU). We find that the secondary to HAT-P-8, also identified by Bergfors et al., is in fact composed of two stars separated by 65.3 ± 0.5 mas (15 ± 1 AU). Our follow-up observations demonstrate physical association through common proper motion. HAT-P-8 C has a particularly low mass, which we estimate to be 0.18 ± 0.02 M ⊙ using photometry. Due to their hierarchy, WASP-12 BC and HAT-P-8 BC will enable the first dynamical mass determination for hot Jupiter stellar companions. These previously well studied planet hosts now represent higher-order multi-star systems with potentially complex dynamics, underscoring the importance of diffraction-limited imaging and providing additional context for understanding the migrant population of transiting hot Jupiters.

WASP-12b AND HAT-P-8b are members of triple star systems

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

Bechter, Eric B.; Crepp, Justin R.; Matthews, Christopher T.

2014-06-10

We present high spatial resolution images that demonstrate that WASP-12b and HAT-P-8b orbit the primary stars of hierarchical triple star systems. In each case, two distant companions with colors and brightnesses consistent with M dwarfs co-orbit the hot Jupiter planet host as well as one another. Our adaptive optics images spatially resolve the secondary around WASP-12, previously identified by Bergfors et al. and Crossfield et al. into two distinct sources separated by 84.3 ± 0.6 mas (21 ± 3 AU). We find that the secondary to HAT-P-8, also identified by Bergfors et al., is in fact composed of two starsmore » separated by 65.3 ± 0.5 mas (15 ± 1 AU). Our follow-up observations demonstrate physical association through common proper motion. HAT-P-8 C has a particularly low mass, which we estimate to be 0.18 ± 0.02 M {sub ☉} using photometry. Due to their hierarchy, WASP-12 BC and HAT-P-8 BC will enable the first dynamical mass determination for hot Jupiter stellar companions. These previously well studied planet hosts now represent higher-order multi-star systems with potentially complex dynamics, underscoring the importance of diffraction-limited imaging and providing additional context for understanding the migrant population of transiting hot Jupiters.« less

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.

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.

Dose measurements for dental cone-beam CT: a comparison with MSCT and panoramic imaging

NASA Astrophysics Data System (ADS)

Deman, P.; Atwal, P.; Duzenli, C.; Thakur, Y.; Ford, N. L.

2014-06-01

To date there is a lack of published information on appropriate methods to determine patient doses from dental cone-beam computed tomography (CBCT) equipment. The goal of this study is to apply and extend the methods recommended in the American Association of Physicists in Medicine (AAPM) Report 111 for CBCT equipment to characterize dose and effective dose for a range of dental imaging equipment. A protocol derived from the one proposed by Dixon et al (2010 Technical Report 111, American Association of Physicist in Medicine, MD, USA), was applied to dose measurements of multi-slice CT, dental CBCT (small and large fields of view (FOV)) and a dental panoramic system. The computed tomography dose index protocol was also performed on the MSCT to compare both methods. The dose distributions in a cylindrical polymethyl methacrylate phantom were characterized using a thimble ionization chamber and Gafchromic™ film (beam profiles). Gafchromic™ films were used to measure the dose distribution in an anthropomorphic phantom. A method was proposed to extend dose estimates to planes superior and inferior to the central plane. The dose normalized to 100 mAs measured in the center of the phantom for the large FOV dental CBCT (11.4 mGy/100 mAs) is two times lower than that of MSCT (20.7 mGy/100 mAs) for the same FOV, but approximately 15 times higher than for a panoramic system (0.6 mGy/100 mAs). The effective dose per scan (in clinical conditions) found for the dental CBCT are 167.60 ± 3.62, 61.30 ± 3.88 and 92.86 ± 7.76 mSv for the Kodak 9000 (fixed scan length of 3.7 cm), and the iCAT Next Generation for 6 cm and 13 cm scan lengths respectively. The method to extend the dose estimates from the central slice to superior and inferior slices indicates a good agreement between theory and measurement. The Gafchromic™ films provided useful beam profile data and 2D distributions of dose in phantom.

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

A Gaia-PS1-SDSS (GPS1) Proper Motion Catalog Covering 3/4 of the Sky

NASA Astrophysics Data System (ADS)

Tian, Hai-Jun; Gupta, Prashansa; Sesar, Branimir; Rix, Hans-Walter; Martin, Nicolas F.; Liu, Chao; Goldman, Bertrand; Platais, Imants; Kudritzki, Rolf-Peter; Waters, Christopher Z.

2017-09-01

We combine Gaia DR1, PS1, Sloan Digital Sky Survey (SDSS), and 2MASS astrometry to measure proper motions for 350 million sources across three-fourths of the sky down to a magnitude of {m}r˜ 20. Using positions of galaxies from PS1, we build a common reference frame for the multi-epoch PS1, single-epoch SDSS and 2MASS data, and calibrate the data in small angular patches to this frame. As the Gaia DR1 excludes resolved galaxy images, we choose a different approach to calibrate its positions to this reference frame: we exploit the fact that the proper motions of stars in these patches are linear. By simultaneously fitting the positions of stars at different epochs of—Gaia DR1, PS1, SDSS, and 2MASS—we construct an extensive catalog of proper motions dubbed GPS1. GPS1 has a characteristic systematic error of less than 0.3 {mas} {{yr}}-1 and a typical precision of 1.5-2.0 {mas} {{yr}}-1. The proper motions have been validated using galaxies, open clusters, distant giant stars, and QSOs. In comparison with other published faint proper motion catalogs, GPS1's systematic error (< 0.3 {mas} {{yr}}-1) should be nearly an order of magnitude better than that of PPMXL and UCAC4 (> 2.0 {mas} {{yr}}-1). Similarly, its precision (˜1.5 {mas} {{yr}}-1) is a four-fold improvement relative to PPMXL and UCAC4 (˜6.0 {mas} {{yr}}-1). For QSOs, the precision of GPS1 is found to be worse (˜2.0-3.0 {mas} {{yr}}-1), possibly due to their particular differential chromatic refraction. The GPS1 catalog will be released online and be available via the VizieR Service and VO Service.

Robust Behavior-Based Control for Distributed Multi-Robot Collection Tasks

DTIC Science & Technology

2000-01-01

Department, University of Southern California, Los Angeles, CA 90089-0781 USA (e-mail: mataric @usc.edu) For a given task environment and set of robots...Press: Cambridge, Mas- sachusetts. [17] Richard T. Vaughan, Kasper Sty, Gaurav S. Sukhatme, and Maja J Mataric, \\Whistling in the dark : Cooperative

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

A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm.

PubMed

Budak, Umit; Şengür, Abdulkadir; Guo, Yanhui; Akbulut, Yaman

2017-12-01

Microaneurysms (MAs) are known as early signs of diabetic-retinopathy which are called red lesions in color fundus images. Detection of MAs in fundus images needs highly skilled physicians or eye angiography. Eye angiography is an invasive and expensive procedure. Therefore, an automatic detection system to identify the MAs locations in fundus images is in demand. In this paper, we proposed a system to detect the MAs in colored fundus images. The proposed method composed of three stages. In the first stage, a series of pre-processing steps are used to make the input images more convenient for MAs detection. To this end, green channel decomposition, Gaussian filtering, median filtering, back ground determination, and subtraction operations are applied to input colored fundus images. After pre-processing, a candidate MAs extraction procedure is applied to detect potential regions. A five-stepped procedure is adopted to get the potential MA locations. Finally, deep convolutional neural network (DCNN) with reinforcement sample learning strategy is used to train the proposed system. The DCNN is trained with color image patches which are collected from ground-truth MA locations and non-MA locations. We conducted extensive experiments on ROC dataset to evaluate of our proposal. The results are encouraging.

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.

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.

An image quality comparison study between XVI and OBI CBCT systems.

PubMed

Kamath, Srijit; Song, William; Chvetsov, Alexei; Ozawa, Shuichi; Lu, Haibin; Samant, Sanjiv; Liu, Chihray; Li, Jonathan G; Palta, Jatinder R

2011-02-04

The purpose of this study is to evaluate and compare image quality characteristics for two commonly used and commercially available CBCT systems: the X-ray Volumetric Imager and the On-Board Imager. A commonly used CATPHAN image quality phantom was used to measure various image quality parameters, namely, pixel value stability and accuracy, noise, contrast to noise ratio (CNR), high-contrast resolution, low contrast resolution and image uniformity. For the XVI unit, we evaluated the image quality for four manufacturer-supplied protocols as a function of mAs. For the OBI unit, we did the same for the full-fan and half-fan scanning modes, which were respectively used with the full bow-tie and half bow-tie filters. For XVI, the mean pixel values of regions of interest were found to generally decrease with increasing mAs for all protocols, while they were relatively stable with mAs for OBI. Noise was slightly lower on XVI and was seen to decrease with increasing mAs, while CNR increased with mAs for both systems. For XVI and OBI, the high-contrast resolution was approximately limited by the pixel resolution of the reconstructed image. On OBI images, up to 6 and 5 discs of 1% and 0.5% contrast, respectively, were visible for a high mAs setting using the full-fan mode, while none of the discs were clearly visible on the XVI images for various mAs settings when the medium resolution reconstruction was used. In conclusion, image quality parameters for XVI and OBI have been quantified and compared for clinical protocols under various mAs settings. These results need to be viewed in the context of a recent study that reported the dose-mAs relationship for the two systems and found that OBI generally delivered higher imaging doses than XVI.

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…

Biopolymer nanocomposite films reinforced with nanocellulose whiskers

Treesearch

Amit Saxena; Marcus Foston; Mohamad Kassaee; Thomas J. Elder; Arthur J. Ragauskas

2011-01-01

A xylan nanocomposite film with improved strength and barrier properties was prepared by a solution casting using nanocellulose whiskers as a reinforcing agent. The 13C cross-polarization magic angle spinning (CP/MAS) nuclear magnetic resonance (NMR) analysis of the spectral data obtained for the NCW/xylan nanocomposite films indicated the signal intensity originating...

Composite-pulse and partially dipolar dephased multiCP for improved quantitative solid-state 13C NMR

NASA Astrophysics Data System (ADS)

Duan, Pu; Schmidt-Rohr, Klaus

2017-12-01

Improved multiple cross polarization (multiCP) pulse sequences for quickly acquiring quantitative 13C NMR spectra of organic solids are presented. Loss of 13C magnetization due to imperfect read-out and storage pulses in multiCP has been identified as a significant mechanism limiting polarization enhancement for 13C sites with weak couplings to 1H. This problem can be greatly reduced by composite 90° pulses with non-orthogonal phases that flip the magnetization onto the spin-lock field and back to the longitudinal direction for the 1H repolarization period; the observed loss is <3% for over ±10 kHz resonance offset and up to 20% flip-angle error. This composite-pulse multiCP (ComPmultiCP) sequence consistently provides performance superior to that of conventional multiCP, without any trade-off. The longer total CP time enabled by the composite pulses allows for a wider amplitude ramp during CP, which decreases the sensitivity to Hartmann-Hahn mismatch by a factor of two, with a <7% root-mean-square deviation within a 1-dB range for Boc-alanine. In samples with very short T1ρ, under-polarization of non-protonated carbons can be compensated by slight dipolar dephasing of CHn signals resulting from relatively weak decoupling during the Hahn spin echo period before detection. Quantitative spectra have been obtained by ComPmultiCP for low-crystallinity branched polyethylene at 4.5 kHz MAS, and in combination with partial dipolar dephasing for soil organic matter at 14 kHz MAS.

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

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

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.

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.

Beneficial Effects of the Activation of the Angiotensin-(1–7) Mas Receptor in a Murine Model of Adriamycin-Induced Nephropathy

PubMed Central

Silveira, Kátia Daniela; Barroso, Lívia Corrêa; Vieira, Angélica Thomáz; Cisalpino, Daniel; Lima, Cristiano Xavier; Bader, Michael; Arantes, Rosa Maria Esteves; dos Santos, Robson Augusto Souza

2013-01-01

Angiotensin-(1–7) [Ang-(1–7)] is a biologically active heptapeptide that may counterbalance the physiological actions of angiotensin II (Ang II) within the renin-angiotensin system (RAS). Here, we evaluated whether activation of the Mas receptor with the oral agonist, AVE 0991, would have renoprotective effects in a model of adriamycin (ADR)-induced nephropathy. We also evaluated whether the Mas receptor contributed for the protective effects of treatment with AT1 receptor blockers. ADR (10 mg/kg) induced significant renal injury and dysfunction that was maximal at day 14 after injection. Treatment with the Mas receptor agonist AVE 0991 improved renal function parameters, reduced urinary protein loss and attenuated histological changes. Renoprotection was associated with reduction in urinary levels of TGF-β. Similar renoprotection was observed after treatment with the AT1 receptor antagonist, Losartan. AT1 and Mas receptor mRNA levels dropped after ADR administration and treatment with losartan reestablished the expression of Mas receptor and increased the expression of ACE2. ADR-induced nephropathy was similar in wild type (Mas+/+) and Mas knockout (Mas −/−) mice, suggesting there was no endogenous role for Mas receptor activation. However, treatment with Losartan was able to reduce renal injury only in Mas+/+, but not in Mas −/− mice. Therefore, these findings suggest that exogenous activation of the Mas receptor protects from ADR-induced nephropathy and contributes to the beneficial effects of AT1 receptor blockade. Medications which target specifically the ACE2/Ang-(1–7)/Mas axis may offer new therapeutic opportunities to treat human nephropathies. PMID:23762470

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.

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.

aCGH-MAS: Analysis of aCGH by means of Multiagent System

PubMed Central

Benito, Rocío; Bajo, Javier; Rodríguez, Ana Eugenia; Abáigar, María

2015-01-01

There are currently different techniques, such as CGH arrays, to study genetic variations in patients. CGH arrays analyze gains and losses in different regions in the chromosome. Regions with gains or losses in pathologies are important for selecting relevant genes or CNVs (copy-number variations) associated with the variations detected within chromosomes. Information corresponding to mutations, genes, proteins, variations, CNVs, and diseases can be found in different databases and it would be of interest to incorporate information of different sources to extract relevant information. This work proposes a multiagent system to manage the information of aCGH arrays, with the aim of providing an intuitive and extensible system to analyze and interpret the results. The agent roles integrate statistical techniques to select relevant variations and visualization techniques for the interpretation of the final results and to extract relevant information from different sources of information by applying a CBR system. PMID:25874203

[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.

Absorbent Analysis of Anniston Chemical Agent Disposal Facility Munition Demilitarization Building (MDB) Banks 1 and 2 Filter Samples Following Completion of The GB Agent and VX Rocket Campaigns

DTIC Science & Technology

2013-01-01

adsorbed on wet carbon (13 wt% water ). Left to right: initial and t = 6, 13, and 16 days ..............................3 2. 31 P MAS NMR spectra...obtained for 10 wt% VX adsorbed on wet carbon (13 wt% water ) Left to right: initial and t = 24 days ...............................................4...of feed air. Each Class A Type II filter contained approximately 48.2 lb of granular, activated, coconut shell-based carbon. A given filter bank

Reactions of CW Agents HD And GD with the Polymer Fabrics PVAM and CHEMCAT 41

DTIC Science & Technology

2015-09-01

analyses of the rates of G agent decomposition were followed by the methods of solids NMR (high resolution magic angle spinning, HR-MAS). A P-31...molecular weight copolymer of 30-35 kDa. The Erkol copolymer forms a pH 12 solution in water and functions as Lewis base when hydrated .6 GD and DFP...Reactions The hydrated PVAm film, containing 20% glycerol, was found to completely deplete and decompose a two-fold excess of DFP vapor (peaks -8 and

Angiotensin (1-7) ameliorates the structural and biochemical alterations of ovariectomy-induced osteoporosis in rats via activation of ACE-2/Mas receptor axis.

PubMed

Abuohashish, Hatem M; Ahmed, Mohammed M; Sabry, Dina; Khattab, Mahmoud M; Al-Rejaie, Salim S

2017-05-23

The local and systemic renin angiotensin system (RAS) influences the skeletal system micro-structure and metabolism. Studies suggested angiotensin 1-7 (Ang(1-7)) as the beneficial RAS molecule via Mas receptor activation. This study examines the function of Ang(1-7) in bone micro-architecture and metabolism in an ovariectomized (OVX) rodent model of osteoporosis. OVX rats showed structural and bone metabolic degeneration in parallel with suppressed expressions of the angiotensin converting enzyme-2 (ACE-2)/Ang(1-7)/Mas components. The infusion of Ang(1-7) markedly alleviated the altered bone metabolism and significantly enhanced both trabecular (metaphyseal) and cortical (metaphyseal-diaphyseal) morphometry. Urinary and bones minerals were also improved in OVX rats by Ang(1-7). The infusion of the heptapeptide enhanced ACE-2/Mas receptor expressions, while down-regulated AngII, ACE, and AngII type-1 receptor (AT1R) in OVX animals. Moreover, Ang(1-7) markedly improved osteoprotegerin (OPG) and lowered receptor activator NF-κB ligand (RANKL) expressions. The defensive properties of Ang(1-7) on bone metabolism, structure and minerals were considerably eradicated after blockage of Mas receptor with A-779. Ang(1-7)-induced up-regulated ACE-2/Ang(1-7)/Mas cascade and OPG expressions were abolished and the expressions of ACE/AngII/AT1R and RANKL were provoked by A-779. These findings shows for the first time the novel valuable therapeutic role of Ang(1-7) on bone health and metabolism through the ACE-2/Mas cascade.

Meconium Aspiration Syndrome: A Role for Fetal Systemic Inflammation

PubMed Central

LEE, JoonHo; ROMERO, Roberto; LEE, Kyung A; KIM, Eun Na; KORZENIEWSKI, Steven J; CHAEMSAITHONG, Piya; YOON, Bo Hyun

2017-01-01

Background Meconium aspiration syndrome (MAS) is a leading cause of morbidity and mortality in term infants. Meconium-stained amniotic fluid (MSAF) occurs in approximately one of every seven pregnancies, but only 5% of neonates exposed to MSAF develop MAS. Why some infants exposed to meconium develop MAS while others do not is a fundamental question. Patients with MSAF have a higher frequency of intra-amniotic infection/inflammation than those with clear fluid. We propose that fetal systemic inflammation is a risk factor for the development of MAS in patients with MSAF. Objective To investigate whether intra-amniotic inflammation and funisitis, the histopathologic landmark of a fetal inflammatory response, predispose to MAS. Study Design A prospective cohort study was conducted from 1995 through 2009. Amniotic fluid (AF) samples (n=1,281) were collected at the time of cesarean delivery from women who delivered singleton newborns at term (gestational age ≥38 weeks). Intra-amniotic inflammation was diagnosed if the AF concentration of matrix metalloproteinase-8 (MMP-8) was >23 ng/ml. Funisitis was diagnosed by histologic examination if inflammation was present in the umbilical cord. Results The prevalence of MSAF was 9.2% (118/1,281), and 10.2% (12/118) of neonates exposed to MSAF developed MAS. There were no significant differences in the median gestational age or umbilical cord arterial pH at birth between neonates who developed MAS and those who did not (each p > 0.1). Mothers whose newborns developed MAS had a higher median AF MMP-8 (456.8 ng/ml vs.157.2 ng/ml; p < 0.05). Newborns exposed to intra-amniotic inflammation had a higher rate of MAS than those who were not exposed to intra-amniotic inflammation [13.0% (10/77) vs. 0% (0/32), p = 0.03], as did those exposed to funisitis [31.3% (5/16) vs. 7.3% (6/82), relative risk, 4.3; 95% confidence interval, 1.5–12.3]. Among the 89 newborns for whom both AF and placental histology were available, MAS was more common in patients with both intra-amniotic inflammation and funisitis than in those without intra-amniotic inflammation and funisitis [28.6% (4/14) vs. 0% (0/28), p = 0.009], while the rate of MAS did not show a significant difference between patients with intra-amniotic inflammation alone (without funisitis) and those without intra-amniotic inflammation and funisitis [10.9% (5/46) vs. 0% (0/28)]. Conclusion The combination of intra-amniotic inflammation with fetal systemic inflammation is an important antecedent of MAS. This concept has implications for the understanding of the mechanisms of disease responsible for MAS and for the development of prognostic models and therapeutic interventions for this disorder. PMID:26484777

Hospital acquisitions, parenting styles and management accounting change: An institutional perspective.

PubMed

Dossi, Andrea; Lecci, Francesca; Longo, Francesco; Morelli, Marco

2017-02-01

Many healthcare scholars have applied institutional theories to the study of management accounting systems (MAS) change. However, little attention has been devoted to MAS change within groups. Kostova et al. highlight the limitations of traditional institutional frameworks in studying groups since they are characterised not only by the existence of external institutional environments but also by intra-organisational (meso-level) ones. Given this background, the research question is: how does the meso-level institutional environment affect MAS change in healthcare groups? We use a longitudinal multiple-case study design to understand the role of headquarters in shaping local MAS change. We would expect companies to adopt similar MAS. However, we argue that the relationship between external institutions and MAS change cannot be wholly understood without taking into consideration the role of headquarters. Our analysis shows how hospitals facing the same external institutional environment implement different MAS as a consequence of different parenting styles. From a scientific perspective, our article contributes to broaden traditional institutional theoretical frameworks.

Medication adherence and symptom reduction in adults treated with mixed amphetamine salts in a randomized crossover study.

PubMed

Adler, Lenard A; Lynch, Lauren R; Shaw, David M; Wallace, Samantha P; Ciranni, Michael A; Briggie, Alexis M; Kulaga, Agatha; O'Donnell, Katherine E; Faraone, Stephen V

2011-09-01

The study objectives were to 1) evaluate medication adherence for adults with attention-deficit/hyperactivity disorder (ADHD) treated with 3 times daily (TID) mixed amphetamine salts immediate release (MAS IR) versus once-daily (qAM) MAS extended release (MAS XR) in a randomized, crossover study; and 2) to examine the associations between adherence and efficacy for MAS IR and MAS XR. Sixty-two adults with ADHD were enrolled and 49 completed the study. The treatment condition order (TID-qAM or qAM-TID) was counterbalanced across participants, with an intervening washout period of ≥ 7 days. Adherence was assessed via 3 measures: 1) self-report, 2) pill count, and 3) the Medication Event Monitoring System (MEMS(®)). The primary efficacy measure was the ADHD Rating Scale (ADHD-RS); secondary measures included the Time-Sensitive ADHD Symptom Scale (TASS) and Clinical Global Impressions-Severity of Illness (CGI-S) scale. Adherence to treatment as measured by self-report and pill count was not significantly different between MAS XR and MAS IR. Adherence was significantly better for MAS XR than MAS IR for all of the MEMS(®) measures. The mean change in ADHD-RS, TASS, and CGI-S scores at endpoint was significantly improved for both MAS IR and MAS XR and did not differ significantly between groups. There was not a significant adherence by efficacy interaction. Adults with ADHD adhered equally well with MAS IR as with MAS XR when assessed by pill count and self-report, but not by the MEMS(®) measures. Both treatments significantly reduced ADHD symptoms, and efficacy was not significantly different between groups. Adherence was not associated with treatment outcome.

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.

Assessment of image quality in soft tissue and bone visualization tasks for a dedicated extremity cone-beam CT system.

PubMed

Demehri, S; Muhit, A; Zbijewski, W; Stayman, J W; Yorkston, J; Packard, N; Senn, R; Yang, D; Foos, D; Thawait, G K; Fayad, L M; Chhabra, A; Carrino, J A; Siewerdsen, J H

2015-06-01

To assess visualization tasks using cone-beam CT (CBCT) compared to multi-detector CT (MDCT) for musculoskeletal extremity imaging. Ten cadaveric hands and ten knees were examined using a dedicated CBCT prototype and a clinical multi-detector CT using nominal protocols (80 kVp-108mAs for CBCT; 120 kVp- 300 mAs for MDCT). Soft tissue and bone visualization tasks were assessed by four radiologists using five-point satisfaction (for CBCT and MDCT individually) and five-point preference (side-by-side CBCT versus MDCT image quality comparison) rating tests. Ratings were analyzed using Kruskal-Wallis and Wilcoxon signed-rank tests, and observer agreement was assessed using the Kappa-statistic. Knee CBCT images were rated "excellent" or "good" (median scores 5 and 4) for "bone" and "soft tissue" visualization tasks. Hand CBCT images were rated "excellent" or "adequate" (median scores 5 and 3) for "bone" and "soft tissue" visualization tasks. Preference tests rated CBCT equivalent or superior to MDCT for bone visualization and favoured the MDCT for soft tissue visualization tasks. Intraobserver agreement for CBCT satisfaction tests was fair to almost perfect (κ ~ 0.26-0.92), and interobserver agreement was fair to moderate (κ ~ 0.27-0.54). CBCT provided excellent image quality for bone visualization and adequate image quality for soft tissue visualization tasks. • CBCT provided adequate image quality for diagnostic tasks in extremity imaging. • CBCT images were "excellent" for "bone" and "good/adequate" for "soft tissue" visualization tasks. • CBCT image quality was equivalent/superior to MDCT for bone visualization tasks.

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)

Further refinement of 17O TRAPDOR NMR methods for determining oxygen speciation in multi-component oxide glasses

NASA Astrophysics Data System (ADS)

LaComb, M.; Stebbins, J. F.

2017-12-01

Solid state nuclear magnetic resonance (NMR) spectroscopy has often been utilized to determine network speciation in oxide glasses, typically using NMR-active nuclides such as 11B, 27Al and 17O. High field strength magnets allow for visible separation between bridging (BO) and non-bridging oxygens (NBO) in 17O magic-angle spinning (MAS) NMR spectra, but many questions remain due to limited ability to directly observe NBO associated with silicon, boron or aluminum in ternary glass systems with MAS NMR techniques. Recent studies have utilized the combination of 17O{27Al} and 17O{11B} TRAnsfer of Population in DOuble-Resonance (TRAPDOR) NMR to attempt to separate out resonances for these different bridging and non-bridging oxygen species in multicomponent calcium aluminosilicate and aluminoborosilicate glasses and rare-earth aluminoborosilicates. With improved technology and better resolution of spectral components we were able to expand this study to a wider range of calcium aluminosilicate, aluminoborate and aluminoborosilicate glasses and further separate out resonances for both bridging and non-bridging oxygens coordinated with aluminum, boron and/or silicon cations in these glasses.

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.

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.

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

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

ELTs adaptive optics for multi-objects 3D spectroscopy: key parameters and design rules

NASA Astrophysics Data System (ADS)

Neichel, B.; Conan, J.-M.; Fusco, T.; Gendron, E.; Puech, M.; Rousset, G.; Hammer, F.

2006-06-01

In the last few years, new Adaptive Optics [AO] techniques have emerged to answer new astronomical challenges: Ground-Layer AO [GLAO] and Multi-Conjugate AO [MCAO] to access a wider Field of View [FoV], Multi-Object AO [MOAO] for the simultaneous observation of several faint galaxies, eXtreme AO [XAO] for the detection of faint companions. In this paper, we focus our study to one of these applications : high red-shift galaxy observations using MOAO techniques in the framework of Extremely Large Telescopes [ELTs]. We present the high-level specifications of a dedicated instrument. We choose to describe the scientific requirements with the following criteria : 40% of Ensquared Energy [EE] in H band (1.65μm) and in an aperture size from 25 to 150 mas. Considering these specifications we investigate different AO solutions thanks to Fourier based simulations. Sky Coverage [SC] is computed for Natural and Laser Guide Stars [NGS, LGS] systems. We show that specifications are met for NGS-based systems at the cost of an extremely low SC. For the LGS approach, the option of low order correction with a faint NGS is discussed. We demonstrate that, this last solution allows the scientific requirements to be met together with a quasi full SC.

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 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.

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.

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.

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

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.

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.

Control of adipogenesis by the autocrine interplays between angiotensin 1-7/Mas receptor and angiotensin II/AT1 receptor signaling pathways.

PubMed

Than, Aung; Leow, Melvin Khee-Shing; Chen, Peng

2013-05-31

Angiotensin II (AngII), a peptide hormone released by adipocytes, can be catabolized by adipose angiotensin-converting enzyme 2 (ACE2) to form Ang(1-7). Co-expression of AngII receptors (AT1 and AT2) and Ang(1-7) receptors (Mas) in adipocytes implies the autocrine regulation of the local angiotensin system upon adipocyte functions, through yet unknown interactive mechanisms. In the present study, we reveal the adipogenic effects of Ang(1-7) through activation of Mas receptor and its subtle interplays with the antiadipogenic AngII-AT1 signaling pathways. Specifically, in human and 3T3-L1 preadipocytes, Ang(1-7)-Mas signaling promotes adipogenesis via activation of PI3K/Akt and inhibition of MAPK kinase/ERK pathways, and Ang(1-7)-Mas antagonizes the antiadipogenic effect of AngII-AT1 by inhibiting the AngII-AT1-triggered MAPK kinase/ERK pathway. The autocrine regulation of the AngII/AT1-ACE2-Ang(1-7)/Mas axis upon adipogenesis has also been revealed. This study suggests the importance of the local regulation of the delicately balanced angiotensin system upon adipogenesis and its potential as a novel therapeutic target for obesity and related metabolic disorders.

The demands and benefits of ergonomics in Sri Lankan apparel industry: A case study at MAS holdings.

PubMed

Abeysekera, John; Illankoon, Prasanna

2016-10-17

Apparel exports bring in sizeable foreign income to Sri Lanka. To protect and promote this industry is a paramount need. This can be carried out by applying Human Factors/Ergonomics (HFE) which has proved to control negative effects at work places. This paper reports a case study which describes the demands and benefits of HFE in MAS Holdings which owns a large share of the apparel industry in Sri Lanka. The study consisted of walk through observation survey, a questionnaire survey and ergonomic work place analysis followed by a training programme to selected employees in three companies. Positive responses to questionnaires revealed good ergonomic practices in the work places surveyed. Ergonomically unfit chairs and potential hazards e.g. exposure to noise and hot environment were detected. It is seen that MAS have introduced strategies originated by Toyota Production System viz. 5S, Kaizen, six sigma etc., which are in fact ergonomic methods. A progressive project MAS boast of viz. 'MAS Operating System' (MOS) empowers training and development to employees. MAS Holdings has adequately realized the benefits of applying HFE as evident by the number of awards received. Relevant companies were advised to take appropriate corrective measures to control the potential hazards.

Positioning Medical Assistants for a Greater Role in the Era of Health Reform.

PubMed

Chapman, Susan A; Marks, Angela; Dower, Catherine

2015-10-01

Medical assistants (MAs) are one of the fastest-growing occupations in the United States. As of 2014 there were about 585,000 MAs in the United States, and the Bureau of Labor Statistics projected the MA workforce to grow by 29% from 2012 to 2022. The MA population is primarily female, ethnically and racially diverse, and paid about $15.01 per hour. MAs are primarily educated in private schools, many at for-profit institutions. The MA curriculum and length of training can be quite varied and can lead to uneven preparation for practice. Traditionally, the MA role has involved a limited clinical role and little involvement with team care, particularly in larger practices or clinics. Medical groups, clinics, and health systems are now taking a new look at MAs and how they can play a greater role in reforming health care delivery models. Expanded roles for MAs might include health coach, referral coordinator, disease registry manager, and health screener using protocols. In expanding MA roles, education and regulatory issues need to be addressed by the provider community including current inconsistent regulation and certification requirements and the lack of preparation for expanded roles in traditional MA training programs. MAs are well positioned to help address challenges in the health care delivery system including improving access to care while reducing overall cost. Successful model practices using MAs in expanded roles need further formal evaluation and replication across practice settings.

Automated microaneurysm detection in diabetic retinopathy using curvelet transform

NASA Astrophysics Data System (ADS)

Ali Shah, Syed Ayaz; Laude, Augustinus; Faye, Ibrahima; Tang, Tong Boon

2016-10-01

Microaneurysms (MAs) are known to be the early signs of diabetic retinopathy (DR). An automated MA detection system based on curvelet transform is proposed for color fundus image analysis. Candidates of MA were extracted in two parallel steps. In step one, blood vessels were removed from preprocessed green band image and preliminary MA candidates were selected by local thresholding technique. In step two, based on statistical features, the image background was estimated. The results from the two steps allowed us to identify preliminary MA candidates which were also present in the image foreground. A collection set of features was fed to a rule-based classifier to divide the candidates into MAs and non-MAs. The proposed system was tested with Retinopathy Online Challenge database. The automated system detected 162 MAs out of 336, thus achieved a sensitivity of 48.21% with 65 false positives per image. Counting MA is a means to measure the progression of DR. Hence, the proposed system may be deployed to monitor the progression of DR at early stage in population studies.

Automated microaneurysm detection in diabetic retinopathy using curvelet transform.

PubMed

Ali Shah, Syed Ayaz; Laude, Augustinus; Faye, Ibrahima; Tang, Tong Boon

2016-10-01

Microaneurysms (MAs) are known to be the early signs of diabetic retinopathy (DR). An automated MA detection system based on curvelet transform is proposed for color fundus image analysis. Candidates of MA were extracted in two parallel steps. In step one, blood vessels were removed from preprocessed green band image and preliminary MA candidates were selected by local thresholding technique. In step two, based on statistical features, the image background was estimated. The results from the two steps allowed us to identify preliminary MA candidates which were also present in the image foreground. A collection set of features was fed to a rule-based classifier to divide the candidates into MAs and non-MAs. The proposed system was tested with Retinopathy Online Challenge database. The automated system detected 162 MAs out of 336, thus achieved a sensitivity of 48.21% with 65 false positives per image. Counting MA is a means to measure the progression of DR. Hence, the proposed system may be deployed to monitor the progression of DR at early stage in population studies.

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

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

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.

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.

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.

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.

Application of 1H and 23Na magic angle spinning NMR spectroscopy to define the HRBC up-taking of MRI contrast agents

NASA Astrophysics Data System (ADS)

Calabi, Luisella; Paleari, Lino; Biondi, Luca; Linati, Laura; De Miranda, Mario; Ghelli, Stefano

2003-09-01

The up-take of Gd(III) complexes of BOPTA, DTPA, DOTA, EDTP, HPDO3A, and DOTP in HRBC has been evaluated by measuring the lanthanide induced shift (LIS) produced by the corresponding dysprosium complexes (DC) on the MAS-NMR resonances of water protons and free sodium ions. These complexes are important in their use as MRI contrast agents (MRI-CA) in diagnostics. 1H and 23Na MAS-NMR spectra of HRBC suspension, collected at 9.395 T, show only one signal due to extra- and intra-cellular water (or sodium). In MAS spectra, the presence of DC in a cellular compartment produces the LIS of only the nuclei (water proton or sodium) in that cellular compartment and this LIS can be related to the DC concentrations (by the experimental curves of LIS vs. DC concentrations) collected in the physiological solution. To obtain correct results about LIS, the use of MAS technique is mandatory, because it guarantees the only the nuclei staying in the same cellular compartment where the LC is present show the LIS. In all the cases considered, the addition of the DC to HRBC (100% hematocrit) produced a shift of only the extra-cellular water (or sodium) signal and the gradient of concentration ( GC) between extra- and intra-cellular compartments resulted greater than 100:1, when calculated by means of sodium signals. These high values of GC are direct proofs that none of the tested dysprosium complexes crosses the HRBC membrane. Since the DC are iso-structural to the gadolinium complexes the corresponding gadolinium ones (MRI-CA) do not cross the HRBC membrane and, consequently, they are not up-taken in HRBC. The GC values calculated by means of water proton signals resulted much lower than those obtained by sodium signals. This proves that the choice of the isotope is a crucial step in order to use this method in the best way. In fact, GC value depends on the lowest detectable LIS which, in turn, depends on the nature of the LC (lanthanide complex) and the observed isotopes.

Macrophage Activation Syndrome.

PubMed

Ravelli, Angelo; Davì, Sergio; Minoia, Francesca; Martini, Alberto; Cron, Randy Q

2015-10-01

Macrophage activation syndrome (MAS) is a potentially life-threatening complication of rheumatic disorders that occurs most commonly in systemic juvenile idiopathic arthritis. In recent years, there have been several advances in the understanding of the pathophysiology of MAS. Furthermore, new classification criteria have been developed. Although the place of cytokine blockers in the management of MAS is still unclear, interleukin-1 inhibitors represent a promising adjunctive therapy, particularly in refractory cases. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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).

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.

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

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.

Modified Ashworth Scale (MAS) Model based on Clinical Data Measurement towards Quantitative Evaluation of Upper Limb Spasticity

NASA Astrophysics Data System (ADS)

Puzi, A. Ahmad; Sidek, S. N.; Mat Rosly, H.; Daud, N.; Yusof, H. Md

2017-11-01

Spasticity is common symptom presented amongst people with sensorimotor disabilities. Imbalanced signals from the central nervous systems (CNS) which are composed of the brain and spinal cord to the muscles ultimately leading to the injury and death of motor neurons. In clinical practice, the therapist assesses muscle spasticity using a standard assessment tool like Modified Ashworth Scale (MAS), Modified Tardiue Scale (MTS) or Fugl-Meyer Assessment (FMA). This is done subjectively based on the experience and perception of the therapist subjected to the patient fatigue level and body posture. However, the inconsistency in the assessment is prevalent and could affect the efficacy of the rehabilitation process. Thus, the aim of this paper is to describe the methodology of data collection and the quantitative model of MAS developed to satisfy its description. Two subjects with MAS of 2 and 3 spasticity levels were involved in the clinical data measurement. Their level of spasticity was verified by expert therapist using current practice. Data collection was established using mechanical system equipped with data acquisition system and LABVIEW software. The procedure engaged repeated series of flexion of the affected arm that was moved against the platform using a lever mechanism and performed by the therapist. The data was then analyzed to investigate the characteristics of spasticity signal in correspondence to the MAS description. Experimental results revealed that the methodology used to quantify spasticity satisfied the MAS tool requirement according to the description. Therefore, the result is crucial and useful towards the development of formal spasticity quantification model.

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

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

Multi-Epoch 8.4GHz VLBI Observations of the Nucleus of Centaurus A

NASA Technical Reports Server (NTRS)

Meier, David L.

1992-01-01

We present the results of several 8.4 GHz VLBI observations of the nucleus of Centaurus A. We fing that the source possesses a classical core-jet structure with the inner portion of the jet expanding at a proper motion of 4.o mas yr or an apparet velocity of 0.26c along the jet.

15x optical zoom and extreme optical image stabilisation: diffraction limited integral field spectroscopy with the Oxford SWIFT spectrograph

NASA Astrophysics Data System (ADS)

Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Lynn, James; Freeman, David; Roberts, Jennifer; Dekany, Richard

2012-09-01

When commissioned in November 2008 at the Palomar 200 inch Hale Telescope, the Oxford SWIFT I and z band integral field spectrograph, fed by the adaptive optics system PALAO, provided a wide (3×) range of spatial resolutions: three plate scales of 235 mas, 160 mas, and 80 mas per spaxel over a contiguous field-of-view of 89×44 pixels. Depending on observing conditions and guide star brightness we can choose a seeing limited scale of 235 mas per spaxel, or 160 mas and 80 mas per spaxel for very bright guide star AO with substantial increase of enclosed energy. Over the last two years PALAO was upgraded to PALM-3000: an extreme, high-order adaptive optics system with two deformable mirrors with more than 3000 actuators, promising diffraction limited performance in SWIFT's wavelength range. In order to take advantage of this increased spatial resolution we upgraded SWIFT with new pre-optics allowing us to spatially Nyquist sample the diffraction limited PALM-3000 point spread function with 16 mas resolution, reducing the spaxel scale by another factor of 5×. We designed, manufactured, integrated and tested the new pre-optics in the first half of 2011 and commissioned it in December 2011. Here we present the opto-mechanical design and assembly of the new scale changing optics, as well as laboratory and on-sky commissioning results. In optimal observing conditions we achieve substantial Strehl ratios, delivering the near diffraction limited spatial resolution in the I and z bands.

HIGH-PRECISION RADIO AND INFRARED ASTROMETRY OF LSPM J1314+1320AB. I. PARALLAX, PROPER MOTIONS, AND LIMITS ON PLANETS

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

Forbrich, Jan; Dupuy, Trent J.; Rizzuto, Aaron

2016-08-10

We present multi-epoch astrometric radio observations with the Very Long Baseline Array (VLBA) of the young ultracool-dwarf binary LSPM J1314+1320AB. The radio emission comes from the secondary star. Combining the VLBA data with Keck near-infrared adaptive-optics observations of both components, a full astrometric fit of parallax (π {sub abs} = 57.975 ± 0.045 mas, corresponding to a distance of d = 17.249 ± 0.013 pc), proper motion (μ {sub α} {sub cos} {sub δ} = −247.99 ± 0.10 mas yr{sup −1}, μ {sub δ} = −183.58 ± 0.22 mas yr{sup −1}), and orbital motion is obtained. Despite the fact thatmore » the two components have nearly identical masses to within ±2%, the secondary’s radio emission exceeds that of the primary by a factor of ≳30, suggesting a difference in stellar rotation history, which could result in different magnetic field configurations. Alternatively, the emission could be anisotropic and beamed toward us for the secondary but not for the primary. Using only reflex motion, we exclude planets of mass 0.7–10 M {sub jup} with orbital periods of 600–10 days, respectively. Additionally, we use the full orbital solution of the binary to derive an upper limit for the semimajor axis of 0.23 au for stable planetary orbits within this system. These limits cover a parameter space that is inaccessible with, and complementary to, near-infrared radial velocity surveys of ultracool dwarfs. Our absolute astrometry will constitute an important test for the astrometric calibration of Gaia .« less

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.

A novel geometry-dosimetry label fusion method in multi-atlas segmentation for radiotherapy: a proof-of-concept study

NASA Astrophysics Data System (ADS)

Chang, Jina; Tian, Zhen; Lu, Weiguo; Gu, Xuejun; Chen, Mingli; Jiang, Steve B.

2017-05-01

Multi-atlas segmentation (MAS) has been widely used to automate the delineation of organs at risk (OARs) for radiotherapy. Label fusion is a crucial step in MAS to cope with the segmentation variabilities among multiple atlases. However, most existing label fusion methods do not consider the potential dosimetric impact of the segmentation result. In this proof-of-concept study, we propose a novel geometry-dosimetry label fusion method for MAS-based OAR auto-contouring, which evaluates the segmentation performance in terms of both geometric accuracy and the dosimetric impact of the segmentation accuracy on the resulting treatment plan. Differently from the original selective and iterative method for performance level estimation (SIMPLE), we evaluated and rejected the atlases based on both Dice similarity coefficient and the predicted error of the dosimetric endpoints. The dosimetric error was predicted using our previously developed geometry-dosimetry model. We tested our method in MAS-based rectum auto-contouring on 20 prostate cancer patients. The accuracy in the rectum sub-volume close to the planning tumor volume (PTV), which was found to be a dosimetric sensitive region of the rectum, was greatly improved. The mean absolute distance between the obtained contour and the physician-drawn contour in the rectum sub-volume 2 mm away from PTV was reduced from 3.96 mm to 3.36 mm on average for the 20 patients, with the maximum decrease found to be from 9.22 mm to 3.75 mm. We also compared the dosimetric endpoints predicted for the obtained contours with those predicted for the physician-drawn contours. Our method led to smaller dosimetric endpoint errors than the SIMPLE method in 15 patients, comparable errors in 2 patients, and slightly larger errors in 3 patients. These results indicated the efficacy of our method in terms of considering both geometric accuracy and dosimetric impact during label fusion. Our algorithm can be applied to different tumor sites and radiation treatments, given a specifically trained geometry-dosimetry model.

A novel geometry-dosimetry label fusion method in multi-atlas segmentation for radiotherapy: a proof-of-concept study.

PubMed

Chang, Jina; Tian, Zhen; Lu, Weiguo; Gu, Xuejun; Chen, Mingli; Jiang, Steve B

2017-05-07

Multi-atlas segmentation (MAS) has been widely used to automate the delineation of organs at risk (OARs) for radiotherapy. Label fusion is a crucial step in MAS to cope with the segmentation variabilities among multiple atlases. However, most existing label fusion methods do not consider the potential dosimetric impact of the segmentation result. In this proof-of-concept study, we propose a novel geometry-dosimetry label fusion method for MAS-based OAR auto-contouring, which evaluates the segmentation performance in terms of both geometric accuracy and the dosimetric impact of the segmentation accuracy on the resulting treatment plan. Differently from the original selective and iterative method for performance level estimation (SIMPLE), we evaluated and rejected the atlases based on both Dice similarity coefficient and the predicted error of the dosimetric endpoints. The dosimetric error was predicted using our previously developed geometry-dosimetry model. We tested our method in MAS-based rectum auto-contouring on 20 prostate cancer patients. The accuracy in the rectum sub-volume close to the planning tumor volume (PTV), which was found to be a dosimetric sensitive region of the rectum, was greatly improved. The mean absolute distance between the obtained contour and the physician-drawn contour in the rectum sub-volume 2 mm away from PTV was reduced from 3.96 mm to 3.36 mm on average for the 20 patients, with the maximum decrease found to be from 9.22 mm to 3.75 mm. We also compared the dosimetric endpoints predicted for the obtained contours with those predicted for the physician-drawn contours. Our method led to smaller dosimetric endpoint errors than the SIMPLE method in 15 patients, comparable errors in 2 patients, and slightly larger errors in 3 patients. These results indicated the efficacy of our method in terms of considering both geometric accuracy and dosimetric impact during label fusion. Our algorithm can be applied to different tumor sites and radiation treatments, given a specifically trained geometry-dosimetry model.

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

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'.

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.

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.

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 randomized, double-blind study of SHP465 mixed amphetamine salts extended-release in adults with ADHD using a simulated adult workplace design.

PubMed

Wigal, Timothy; Brams, Matthew; Frick, Glen; Yan, Brian; Madhoo, Manisha

2018-06-18

The objective of this paper was to evaluate the efficacy, duration of effect, and tolerability of SHP465 mixed amphetamine salts (MAS) extended-release versus placebo and immediate-release MAS (MAS IR) in adults with attention-deficit/hyperactivity disorder (ADHD). Adults with ADHD Rating Scale, Version IV (ADHD-RS-IV) scores ≥24 were randomized to SHP465 MAS (50 or 75 mg), placebo, or 25 mg MAS IR in a double-blind, three-period, crossover study using a simulated adult workplace environment. On the final day of each 7-day treatment period, efficacy was assessed for 16 h postdose. Primary efficacy analyses for Permanent Product Measure of Performance (PERMP) total score averaged across all postdose assessments and each postdose time point were conducted in the intent-to-treat population using a mixed linear model. Secondary end-points included PERMP problems attempted and answered correctly and ADHD-RS-IV scores based on clinician ratings of counselor observations using the Time Segment Rating System and participant self-report. Tolerability assessments included treatment-emergent adverse events (TEAEs) and vital signs. Least squares mean (95% CI) treatment differences (combined 50/75 mg SHP465 MAS-placebo) significantly favored SHP465 MAS over placebo for PERMP total score averaged across all postdose assessments (18.38 [11.28, 25.47]; P < .0001) and at each postdose assessment (all P < .02). Nominal superiority of MAS IR over placebo for PERMP total score averaged across all postdose assessments was observed (nominal P = .0001); treatment differences between SHP465 MAS and MAS IR were not significant (nominal P = .2443). The two most frequently reported TEAEs associated with SHP465 MAS were insomnia (36.5%) and anorexia (21.2%). Mean increases in pulse and blood pressure with SHP465 MAS exceeded those of placebo. SHP465 MAS (combined 50/75 mg) significantly improved PERMP total score versus placebo, with superiority observed from 2 to 16 h postdose. The tolerability profile of SHP465 MAS was similar to previous reports of SHP465 MAS in adults with ADHD. https://clinicaltrials.gov/ct2/show/NCT00928148 identifier is NCT00928148.

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.

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.

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.

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.

Pulmonary Hypertension and Other Potentially Fatal Pulmonary Complications in Systemic Juvenile Idiopathic Arthritis

PubMed Central

Kimura, Yukiko; Weiss, Jennifer E.; Haroldson, Kathryn L.; Lee, Tzielan; Punaro, Marilynn; Oliveira, Sheila; Rabinovich, Egla; Riebschleger, Meredith; Antón, Jordi; Blier, Peter R.; Gerloni, Valeria; Hazen, Melissa M; Kessler, Elizabeth; Onel, Karen; Passo, Murray H; Rennebohm, Robert M; Wallace, Carol A; Woo, Patricia; Wulffraat, Nico

2015-01-01

Objectives Systemic Juvenile Idiopathic Arthritis (sJIA) is characterized by fevers, rash and arthritis, for which IL1 and IL6 inhibitors appear effective. Pulmonary artery hypertension (PAH), interstitial lung disease (ILD) and alveolar proteinosis (AP) have been recently reported in sJIA patients with increased frequency. Our aim was to characterize and compare these cases to a larger cohort of sJIA patients. Methods sJIA patients who developed PAH, ILD and/or AP were identified through an electronic listserv, and their demographic, sJIA and pulmonary disease characteristics, and medication exposure information were collected. These features were compared to a cohort of sJIA patients enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry. Results Patients (N=25) were significantly (p<0.05) more likely than the CARRA registry cohort (N=389) to be female, have more systemic features, and to have been exposed to an IL-1 inhibitor, tocilizumab, infliximab, corticosteroids, intravenous immunoglobulin, cyclosporine and cyclophosphamide. Eighty% were diagnosed after 2004. Twenty (80%) patients had MAS during their disease course and 15 (60%) had MAS at pulmonary diagnosis. Sixteen patients had PAH, 5 AP and 7 ILD. Seventeen (68%) patients were taking or recently (≤1 month) discontinued a biologic agent at pulmonary symptom onset; 12 (48%) were taking anti-IL1 therapy (primarily anakinra). Seventeen (68%) patients died at a mean of 8.8 months from pulmonary diagnosis. Conclusions PAH, AP and ILD are under-recognized complications of sJIA which are frequently fatal. These may be the result of severe uncontrolled systemic disease activity, and may be influenced by medication exposure. PMID:23139240

THE SOLAR NEIGHBORHOOD. XXVI. AP Col: THE CLOSEST (8.4 pc) PRE-MAIN-SEQUENCE STAR

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

Riedel, Adric R.; Henry, Todd J.; Jao, Wei-Chun

2011-10-15

We present the results of a multi-technique investigation of the M4.5Ve flare star AP Col, which we discover to be the nearest pre-main-sequence star. These include astrometric data from the CTIO 0.9 m, from which we derive a proper motion of 342.0 {+-} 0.5 mas yr{sup -1}, a trigonometric parallax of 119.21 {+-} 0.98 mas (8.39 {+-} 0.07 pc), and photometry and photometric variability at optical wavelengths. We also provide spectroscopic data, including radial velocity (22.4 {+-} 0.3 km s{sup -1}), lithium equivalent width (EW) (0.28 {+-} 0.02 A), H{alpha} EW (-6.0 to -35 A), vsin i (11 {+-} 1more » km s{sup -1}), and gravity indicators from the Siding Spring 2.3 m WiFeS, Lick 3 m Hamilton echelle, and Keck-I HIRES echelle spectrographs. The combined observations demonstrate that AP Col is the closer of only two known systems within 10 pc of the Sun younger than 100 Myr. Given its space motion and apparent age of 12-50 Myr, AP Col is likely a member of the recently proposed {approx}40 Myr old Argus/IC 2391 Association.« less

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…

Pharmacological significance of the interplay between angiotensin receptors: MAS receptors as putative final mediators of the effects elicited by angiotensin AT1 receptors antagonists.

PubMed

Pernomian, Larissa; Pernomian, Laena; Gomes, Mayara S; da Silva, Carlos H T P

2015-12-15

The interplay between angiotensin AT1 receptors and MAS receptors relies on several inward regulatory mechanisms from renin-angiotensin system (RAS) including the functional crosstalk between angiotensin II and angiotensin-(1-7), the competitive AT1 antagonism exhibited by angiotensin-(1-7), the antagonist feature assigned to AT1/MAS heterodimerization on AT1 signaling and the AT1-mediated downregulation of angiotensin-converting enzyme 2 (ACE2). Recently, such interplay has acquired an important significance to RAS Pharmacology since a few studies have supporting strong evidences that MAS receptors mediate the effects elicited by AT1 antagonists. The present Perspective provides an overview of the regulatory mechanisms involving AT1 and MAS receptors, their significance to RAS Pharmacology and the future directions on the interplay between angiotensin receptors. Copyright © 2015 Elsevier B.V. All rights reserved.

On the use of ultracentrifugal devices for routine sample preparation in biomolecular magic-angle-spinning NMR

PubMed Central

Mandal, Abhishek; Boatz, Jennifer C.; Wheeler, Travis; van der Wel, Patrick C. A.

2017-01-01

A number of recent advances in the field of magic-angle-spinning (MAS) solid-state NMR have enabled its application to a range of biological systems of ever increasing complexity. To retain biological relevance, these samples are increasingly studied in a hydrated state. At the same time, experimental feasibility requires the sample preparation process to attain a high sample concentration within the final MAS rotor. We discuss these considerations, and how they have led to a number of different approaches to MAS NMR sample preparation. We describe our experience of how custom-made (or commercially available) ultracentrifugal devices can facilitate a simple, fast and reliable sample preparation process. A number of groups have since adopted such tools, in some cases to prepare samples for sedimentation-style MAS NMR experiments. Here we argue for a more widespread adoption of their use for routine MAS NMR sample preparation. PMID:28229262

Des schémas équivalents pour les circuits couplés multi-enroulements

NASA Astrophysics Data System (ADS)

Keradec, J. P.; Cogitore, B.; Laveuve, E.; Bensoam, M.

1994-04-01

The aim of this paper is to represent the electrical behaviour of any number of magnetically coupled windings with couplers and inductors. Two methods, mathematicaly justified, are proposed. The second one introduces only positive inductances. As an exemple, it is applied to the representation of a three column three phase transformer. The obtained circuits supply the requisite guide to design more complete circuits which allow the high frequency behaviour of wound components to be taken into account, especialy in electronics simulation softwares. Le but de cet article est de traduire le comportement électrique d'un nombre quelconque d'enroulements magnétiquement couplés, par des coupleurs et des inductances. Deux méthodes, établies mathématiquement, sont proposées. La seconde n'introduit que des inductances positives. A titre d'exemple, elle est appliquée à la représentation d'un transformateur triphasé à trois colonnes. Les schémas obtenus fournissent l'indispensable ossature de schémas plus complets, aptes à représenter le comportement haute fréquence des composants bobinés, notamment dans un logiciel de simulation électronique.

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.

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.

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.

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.

New Evidence for the Dynamical Decay of a Multiple System in the Orion Kleinmann–Low Nebula

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

Luhman, K. L.; Robberto, M.; Gabellini, M. Giulia Ubeira

We have measured astrometry for members of the Orion Nebula Cluster with images obtained in 2015 with the Wide Field Camera 3 on board the Hubble Space Telescope . By comparing those data to previous measurements with the Near-Infrared Camera and Multi-Object Spectrometer on Hubble in 1998, we have discovered that a star in the Kleinmann–Low Nebula, source x from Lonsdale et al., is moving with an unusually high proper motion of 29 mas yr{sup −1}, which corresponds to 55 km s{sup −1} at the distance of Orion. Previous radio observations have found that three other stars in the Kleinmann–Lowmore » Nebula (the Becklin–Neugebauer object and sources I and n) have high proper motions (5–14 mas yr{sup −1}) and were near a single location ∼540 years ago, and thus may have been members of a multiple system that dynamically decayed. The proper motion of source x is consistent with ejection from that same location 540 years ago, which provides strong evidence that the dynamical decay did occur and that the runaway star BN originated in the Kleinmann–Low Nebula rather than the nearby Trapezium cluster. However, our constraint on the motion of source n is significantly smaller than the most recent radio measurement, which indicates that it did not participate in the event that ejected the other three stars.« less

New Evidence for the Dynamical Decay of a Multiple System in the Orion Kleinmann-Low Nebula

NASA Astrophysics Data System (ADS)

Luhman, K. L.; Robberto, M.; Tan, J. C.; Andersen, M.; Giulia Ubeira Gabellini, M.; Manara, C. F.; Platais, I.; Ubeda, L.

2017-03-01

We have measured astrometry for members of the Orion Nebula Cluster with images obtained in 2015 with the Wide Field Camera 3 on board the Hubble Space Telescope. By comparing those data to previous measurements with the Near-Infrared Camera and Multi-Object Spectrometer on Hubble in 1998, we have discovered that a star in the Kleinmann-Low Nebula, source x from Lonsdale et al., is moving with an unusually high proper motion of 29 mas yr-1, which corresponds to 55 km s-1 at the distance of Orion. Previous radio observations have found that three other stars in the Kleinmann-Low Nebula (the Becklin-Neugebauer object and sources I and n) have high proper motions (5-14 mas yr-1) and were near a single location ˜540 years ago, and thus may have been members of a multiple system that dynamically decayed. The proper motion of source x is consistent with ejection from that same location 540 years ago, which provides strong evidence that the dynamical decay did occur and that the runaway star BN originated in the Kleinmann-Low Nebula rather than the nearby Trapezium cluster. However, our constraint on the motion of source n is significantly smaller than the most recent radio measurement, which indicates that it did not participate in the event that ejected the other three stars. Based on observations made with the NASA/ESA Hubble Space Telescope and the NASA Infrared Telescope Facility.

How current Clinical Practice Guidelines for low back pain reflect Traditional Medicine in East Asian Countries: a systematic review of Clinical Practice Guidelines and systematic reviews.

PubMed

Cho, Hyun-Woo; Hwang, Eui-Hyoung; Lim, Byungmook; Heo, Kwang-Ho; Liu, Jian-Ping; Tsutani, Kiichiro; Lee, Myeong Soo; Shin, Byung-Cheul

2014-01-01

The aims of this study were to investigate whether there is a gap between evidence of traditional medicine (TM) interventions in East-Asian countries from the current Clinical Practice Guidelines (CPGs) and evidence from current systematic reviews and meta-analyses (SR-MAs) and to analyze the impact of this gap on present CPGs. We examined 5 representative TM interventions in the health care systems of East-Asian countries. We searched seven relevant databases for CPGs to identify whether core CPGs included evidence of TM interventions, and we searched 11 databases for SR-MAs to re-evaluate current evidence on TM interventions. We then compared the gap between the evidence from CPGs and SR-MAs. Thirteen CPGs and 22 SR-MAs met our inclusion criteria. Of the 13 CPGs, 7 CPGs (54%) mentioned TM interventions, and all were for acupuncture (only one was for both acupuncture and acupressure). However, the CPGs did not recommend acupuncture (or acupressure). Of 22 SR-MAs, 16 were for acupuncture, 5 for manual therapy, 1 for cupping, and none for moxibustion and herbal medicine. Comparing the evidence from CPGs and SR-MAs, an underestimation or omission of evidence for acupuncture, cupping, and manual therapy in current CPGs was detected. Thus, applying the results from the SR-MAs, we moderately recommend acupuncture for chronic LBP, but we inconclusively recommend acupuncture for (sub)acute LBP due to the limited current evidence. Furthermore, we weakly recommend cupping and manual therapy for both (sub)acute and chronic LBP. We cannot provide recommendations for moxibustion and herbal medicine due to a lack of evidence. The current CPGs did not fully reflect the evidence for TM interventions. As relevant studies such as SR-MAs are conducted and evidence increases, the current evidence on acupuncture, cupping, and manual therapy should be rigorously considered in the process of developing or updating the CPG system.

Mineral-resource data bases

USGS Publications Warehouse

,

1997-01-01

Data bases are essential for modern scientific research. The new and exciting work being done in the Mineral Resource Program in the U.S. Geological Survey (USGS) usually begins with the question, "Where are the known deposits?" A mineral-resource data base containing this type of information and more can be useful not just to USGS scientists, but to anyone who needs such data. Users of the data bases from outside the USGS include mining and exploration companies, environmental groups, academia, other Federal Agencies, and the general public. At present, the USGS has two large mineral-resource data bases, MRDS (Mineral Resource Data System) and MAS (Minerals Availability System). MRDS was built and is mamtained by the USGS, and MAS was built and maintained by the Bureau of Mines. In 1996, after the Bureau was abolished, MAS was transferred to the USGS. The two data bases were compiled for different purposes and contain very different mformation. For instance, MAS contains information on costs, details of mining methods, and feasibility studies. MRDS has mineralogical and geologic data that are not contained in MAS. Because they are both mineral-resource data bases, however, they contain some information in common, such as location, name(s) of sites, and commodities present. Both data bases are international in scope, and both are quite large. MRDS contains over 110,000 records, while MAS has over 220,000. One reason that MAS has more records is that it contains information on smelters, mill sites, and fossil fuel sites, as well as mineral- resource sites. The USGS is working to combine the information in both data bases. This is a large undertaking that will require some years to complete. In the interim, information from both data bases will still be available

Fast passage dynamic nuclear polarization on rotating solids

NASA Astrophysics Data System (ADS)

Mentink-Vigier, Frederic; Akbey, Ümit; Hovav, Yonatan; Vega, Shimon; Oschkinat, Hartmut; Feintuch, Akiva

2012-11-01

Magic Angle Spinning (MAS) Dynamic Nuclear Polarization (DNP) has proven to be a very powerful way to improve the signal to noise ratio of NMR experiments on solids. The experiments have in general been interpreted considering the Solid-Effect (SE) and Cross-Effect (CE) DNP mechanisms while ignoring the influence of sample spinning. In this paper, we show experimental data of MAS-DNP enhancements of 1H and 13C in proline and SH3 protein in glass forming water/glycerol solvent containing TOTAPOL. We also introduce a theoretical model that aims at explaining how the nuclear polarization is built in MAS-DNP experiments. By using Liouville space based simulations to include relaxation on two simple spin models, {electron-nucleus} and {electron-electron-nucleus}, we explain how the basic MAS-SE-DNP and MAS-CE-DNP processes work. The importance of fast energy passages and short level anti-crossing is emphasized and the differences between static DNP and MAS-DNP is explained. During a single rotor cycle the enhancement in the {electron-electron-nucleus} system arises from MAS-CE-DNP involving at least three kinds of two-level fast passages: an electron-electron dipolar anti-crossing, a single quantum electron MW encounter and an anti-crossing at the CE condition inducing nuclear polarization in- or decrements. Numerical, powder-averaged, simulations were performed in order to check the influence of the experimental parameters on the enhancement efficiencies. In particular we show that the spinning frequency dependence of the theoretical MAS-CE-DNP enhancement compares favorably with the experimental 1H and 13C MAS-DNP enhancements of proline and SH3.

The Gould’s Belt Distances Survey (GOBELINS). I. Trigonometric Parallax Distances and Depth of the Ophiuchus Complex

NASA Astrophysics Data System (ADS)

Ortiz-León, Gisela N.; Loinard, Laurent; Kounkel, Marina A.; Dzib, Sergio A.; Mioduszewski, Amy J.; Rodríguez, Luis F.; Torres, Rosa M.; González-Lópezlira, Rosa A.; Pech, Gerardo; Rivera, Juana L.; Hartmann, Lee; Boden, Andrew F.; Evans, Neal J., II; Briceño, Cesar; Tobin, John J.; Galli, Phillip A. B.; Gudehus, Donald

2017-01-01

We present the first results of the Gould’s Belt Distances Survey (GOBELINS), a project aimed at measuring the proper motion and trigonometric parallax of a large sample of young stars in nearby regions using multi-epoch Very Long Baseline Array (VLBA) radio observations. Enough VLBA detections have now been obtained for 16 stellar systems in Ophiuchus to derive their parallax and proper motion. This leads to distance determinations for individual stars with an accuracy of 0.3 to a few percent. In addition, the orbits of six multiple systems were modelled by combining absolute positions with VLBA (and, in some cases, near-infrared) angular separations. Twelve stellar systems are located in the dark cloud Lynds 1688 the individual distances for this sample are highly consistent with one another and yield a mean parallax for Lynds 1688 of \\varpi =7.28+/- 0.06 mas, corresponding to a distance d=137.3+/- 1.2 pc. This represents an accuracy greater than 1%. Three systems for which astrometric elements could be measured are located in the eastern streamer (Lynds 1689) and yield an estimate of \\varpi =6.79+/- 0.16 mas, corresponding to a distance d=147.3+/- 3.4 pc. This suggests that the eastern streamer is located about 10 pc farther than the core, but this conclusion needs to be confirmed by observations of additional sources in the eastern streamer (currently being collected). From the measured proper motions, we estimate the one-dimensional velocity dispersion in Lynds 1688 to be 2.8 ± 1.8 and 3.0 ± 2.0 km s-1, in R.A. and decl., respectively; these are larger than, but still consistent within 1σ of, those found in other studies.

Increasing brain angiotensin converting enzyme 2 activity decreases anxiety-like behavior in male mice by activating central Mas receptors

PubMed Central

Wang, Lei; de Kloet, Annette D.; Pati, Dipanwita; Hiller, Helmut; Smith, Justin A.; Pioquinto, David J.; Ludin, Jacob A.; Oh, S. Paul; Katovich, Michael J.; Frazier, Charles J.; Raizada, Mohan K.; Krause, Eric G.

2016-01-01

Over-activation of brain renin-angiotensin system (RAS) has been implicated in the etiology of anxiety disorders. Angiotensin converting enzyme (ACE2) inhibits RAS activity by converting angiotensin II, the effector peptide of RAS, to angiotensin-(1-7), which activates Mas receptors (MasR). Whether increasing brain ACE2 activity reduces anxiety by stimulating central MasR is unknown. To test the hypothesis that increasing brain ACE2 activity reduces anxiety-like behavior via central MasR stimulation, we generated male mice overexpressing ACE2 (ACE2 KI mice) and wild type littermate controls (WT). ACE2 KI mice explored the open arms of the elevated plus maze (EPM) significantly more than WT, suggesting increasing ACE2 activity is anxiolytic. Central delivery of diminazene aceturate, an ACE2 activator, to C57BL/6 mice also reduced anxiety-like behavior in the EPM, but centrally administering ACE2 KI mice A-779, a MasR antagonist, abolished their anxiolytic phenotype, suggesting that ACE2 reduces anxiety-like behavior by activating central MasR. To identify the brain circuits mediating these effects, we measured Fos, a marker of neuronal activation, subsequent to EPM exposure and found that ACE2 KI mice had decreased Fos in the bed nucleus of stria terminalis but had increased Fos in the basolateral amygdala (BLA). Within the BLA, we determined that ~62% of GABAergic neurons contained MasR mRNA and expression of MasR mRNA was upregulated by ACE2 overexpression, suggesting that ACE2 may influence GABA neurotransmission within the BLA via MasR activation. Indeed, ACE2 overexpression was associated with increased frequency of spontaneous inhibitory postsynaptic currents (indicative of presynaptic release of GABA) onto BLA pyramidal neurons and central infusion of A-779 eliminated this effect. Collectively, these results suggest that ACE2 may reduce anxiety-like behavior by activating central MasR that facilitate GABA release onto pyramidal neurons within the BLA. PMID:26767952

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.

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.

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.

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

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

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.

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.

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...

Engineered core-shell magnetic nanoparticle for MR dual-modal tracking and safe magnetic manipulation of ependymal cells in live rodents

NASA Astrophysics Data System (ADS)

Peng, Yung-Kang; Lui, Cathy N. P.; Chen, Yu-Wei; Chou, Shang-Wei; Chou, Pi-Tai; Yung, Ken K. L.; Edman Tsang, S. C.

2018-01-01

Tagging recognition group(s) on superparamagnetic iron oxide is known to aid localisation (imaging), stimulation and separation of biological entities using magnetic resonance imaging (MRI) and magnetic agitation/separation (MAS) techniques. Despite the wide applicability of iron oxide nanoparticles in T 2-weighted MRI and MAS, the quality of the images and safe manipulation of the exceptionally delicate neural cells in a live brain are currently the key challenges. Here, we demonstrate the engineered manganese oxide clusters-iron oxide core-shell nanoparticle as an MR dual-modal contrast agent for neural stem cells (NSCs) imaging and magnetic manipulation in live rodents. As a result, using this engineered nanoparticle and associated technologies, identification, stimulation and transportation of labelled potentially multipotent NSCs from a specific location of a live brain to another by magnetic means for self-healing therapy can therefore be made possible.

Size-dependent scanning parameters (kVp and mAs) for photon-counting spectral CT system in pediatric imaging: simulation study

NASA Astrophysics Data System (ADS)

Chen, Han; Danielsson, Mats; Xu, Cheng

2016-06-01

We are developing a photon-counting spectral CT detector with a small pixel size of 0.4× 0.5 mm2, offering a potential advantage for better visualization of small structures in pediatric patients. The purpose of this study is to determine the patient size dependent scanning parameters (kVp and mAs) for pediatric CT in two imaging cases: adipose imaging and iodinated blood imaging. Cylindrical soft-tissue phantoms of diameters between 10-25 cm were used to mimic patients of different ages from 0 to 15 y. For adipose imaging, a 5 mm diameter adipose sphere was assumed as an imaging target, while in the case of iodinated imaging, an iodinated blood sphere of 1 mm in diameter was assumed. By applying the geometry of a commercial CT scanner (GE Lightspeed VCT), simulations were carried out to calculate the detectability index, {{d}\\prime 2} , with tube potentials varying from 40 to 140 kVp. The optimal kVp for each phantom in each imaging case was determined such that the dose-normalized detectability index, {{d}\\prime 2}/ dose, is maximized. With the assumption that the detectability index in pediatric imaging is required the same as in typical adult imaging, the value of mAs at optimal kVp for each phantom was selected to achieve a reference detectability index that was obtained by scanning an adult phantom (30 cm in diameter) in a typical adult CT procedure (120 kVp and 200 mAs) using a modeled energy-integrating system. For adipose imaging, the optimal kVps are 50, 60, 80, and 120 kVp, respectively, for phantoms of 10, 15, 20, and 25 cm in diameter. The corresponding mAs values required to achieve the reference detectability index are only 9%, 23%, 24%, and 54% of the mAs that is used for adult patients at 120 kVp, for 10, 15, 20, and 25 cm diameter phantoms, respectively. In the case of iodinated imaging, a tube potential of 60 kVp was found optimal for all phantoms investigated, and the mAs values required to achieve the reference detectability index are 2%, 9%, 37%, and 109% of the adult mAs. The results also indicate that with the use of respective optimal kVps, the photon-counting spectral system offers up to 30% higher {{d}\\prime 2}/ dose than the modeled energy-integrating system for adipose imaging, and 70% for iodinated imaging.

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

M855A1 Enhanced Performance Round (EPR) Media Day

DTIC Science & Technology

2011-05-04

Distribution is unlimited. Other requests shall be referred to the Office of the Project Manager for Maneuver Ammunition Systems, ATTN: SFAE-AMO-MAS- SETI ... SETI ,Picatinny,NJ,07806-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S...the Project Manager for Maneuver Ammunition Systems, ATTN: SFAE- AMO-MAS- SETI , Picatinny, NJ Distribution Statement A: Approved for Public Release

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.

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

NASA Astrophysics Data System (ADS)

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

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

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.

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.

Application of High-Resolution Magic-Angle Spinning NMR Spectroscopy to Define the Cell Uptake of MRI Contrast Agents

NASA Astrophysics Data System (ADS)

Calabi, Luisella; Alfieri, Goffredo; Biondi, Luca; De Miranda, Mario; Paleari, Lino; Ghelli, Stefano

2002-06-01

A new method, based on proton high-resolution magic-angle spinning ( 1H HR-MAS) NMR spectroscopy, has been employed to study the cell uptake of magnetic resonance imaging contrast agents (MRI-CAs). The method was tested on human red blood cells (HRBC) and white blood cells (HWBC) by using three gadolinium complexes, widely used in diagnostics, Gd-BOPTA, Gd-DTPA, and Gd-DOTA, and the analogous complexes obtained by replacing Gd(III) with Dy(III), Nd(III), and Tb(III) (i.e., complexes isostructural to the ones of gadolinium but acting as shift agents). The method is based on the evaluation of the magnetic effects, line broadening, or induced lanthanide shift (LIS) caused by these complexes on NMR signals of intra- and extracellular water. Since magnetic effects are directly linked to permeability, this method is direct. In all the tests, these magnetic effects were detected for the extracellular water signal only, providing a direct proof that these complexes are not able to cross the cell membrane. Line broadening effects (i.e., the use of gadolinium complexes) only allow qualitative evaluations. On the contrary, LIS effects can be measured with high precision and they can be related to the concentration of the paramagnetic species in the cellular compartments. This is possible because the HR-MAS technique provides the complete elimination of bulk magnetic susceptibility (BMS) shift and the differentiation of extra- and intracellular water signals. Thus with this method, the rapid quantification of the MRI-CA amount inside and outside the cells is actually feasible.

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

PubMed

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

Fast passage dynamic nuclear polarization on rotating solids.

PubMed

Mentink-Vigier, Frederic; Akbey, Umit; Hovav, Yonatan; Vega, Shimon; Oschkinat, Hartmut; Feintuch, Akiva

2012-11-01

Magic Angle Spinning (MAS) Dynamic Nuclear Polarization (DNP) has proven to be a very powerful way to improve the signal to noise ratio of NMR experiments on solids. The experiments have in general been interpreted considering the Solid-Effect (SE) and Cross-Effect (CE) DNP mechanisms while ignoring the influence of sample spinning. In this paper, we show experimental data of MAS-DNP enhancements of (1)H and (13)C in proline and SH3 protein in glass forming water/glycerol solvent containing TOTAPOL. We also introduce a theoretical model that aims at explaining how the nuclear polarization is built in MAS-DNP experiments. By using Liouville space based simulations to include relaxation on two simple spin models, {electron-nucleus} and {electron-electron-nucleus}, we explain how the basic MAS-SE-DNP and MAS-CE-DNP processes work. The importance of fast energy passages and short level anti-crossing is emphasized and the differences between static DNP and MAS-DNP is explained. During a single rotor cycle the enhancement in the {electron-electron-nucleus} system arises from MAS-CE-DNP involving at least three kinds of two-level fast passages: an electron-electron dipolar anti-crossing, a single quantum electron MW encounter and an anti-crossing at the CE condition inducing nuclear polarization in- or decrements. Numerical, powder-averaged, simulations were performed in order to check the influence of the experimental parameters on the enhancement efficiencies. In particular we show that the spinning frequency dependence of the theoretical MAS-CE-DNP enhancement compares favorably with the experimental (1)H and (13)C MAS-DNP enhancements of proline and SH3. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

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

Distributed Market-Based Algorithms for Multi-Agent Planning with Shared Resources

DTIC Science & Technology

2013-02-01

1 Introduction 1 2 Distributed Market-Based Multi-Agent Planning 5 2.1 Problem Formulation...over the deterministic planner, on the “test set” of scenarios with changing economies. . . 50 xi xii Chapter 1 Introduction Multi-agent planning is...representation of the objective (4.2.1). For example, for the supply chain mangement problem, we assumed a sequence of Bernoulli coin flips, which seems

Origin of Money: Dynamic Duality Between Necessity and Unnecessity

NASA Astrophysics Data System (ADS)

Tauchi, Yuka; Kamiura, Moto; Haruna, Taichi; Gunji, Yukio-Pegio

2008-10-01

We propose a mathematical model of economic agents to study origin of money. This multi-agent model is based on commodity theory of money, which says that a commodity used as money emerges from barter transaction. Each agent has a different value system which is given by a Heyting algebra, and exchanges one's commodities based on the value system. In each value system, necessity and unnecessity of commodities are expressed by some elements and their compliments on a Heyting Algebra. Moreover, the concept of the compliment is extended. Consequently, the duality of the necessity-unnecessity is weakened, and the exchanges of the commodities are promoted. The commodities which keeps being exchanged for a long time can correspond to money.

Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Saptarshi

Multi-agent systems are widely used for constructing a desired formation shape, exploring an area, surveillance, coverage, and other cooperative tasks. This dissertation introduces novel algorithms in the three main areas of shape formation, distributed estimation, and attitude control of large-scale multi-agent systems. In the first part of this dissertation, we address the problem of shape formation for thousands to millions of agents. Here, we present two novel algorithms for guiding a large-scale swarm of robotic systems into a desired formation shape in a distributed and scalable manner. These probabilistic swarm guidance algorithms adopt an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled using tunable Markov chains. In the first algorithm - Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) - each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain that is constructed in real-time using feedback from the current swarm distribution. This PSG-IMC algorithm minimizes the expected cost of the transitions required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes, and can also be adapted for area exploration applications. In the second algorithm - Probabilistic Swarm Guidance using Optimal Transport (PSG-OT) - each agent determines its bin transition probabilities by solving an optimal transport problem, which is recast as a linear program. In the presence of perfect feedback of the current swarm distribution, this algorithm minimizes the given cost function, guarantees faster convergence, reduces the number of transitions for achieving the desired formation, and is robust to disturbances or damages to the formation. We demonstrate the effectiveness of these two proposed swarm guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees global exponential convergence of tracking errors with finite-gain Lp stability in the presence of modeling uncertainties and disturbances, and reduces the resultant disturbance torque. Further, this control law permits the use of any attitude representation and its integral control formulation eliminates any constant disturbance. Under small uncertainties, the best strategy for stabilizing the combined system is to track a fuel-optimal reference trajectory using this nonlinear control law, because it consumes the least amount of fuel. In the presence of large uncertainties, the most effective strategy is to track the derivative plus proportional-derivative based reference trajectory, because it reduces the resultant disturbance torque. The effectiveness of the proposed attitude control law is demonstrated by using results of numerical simulation based on an Asteroid Redirect Mission concept. The new algorithms proposed in this dissertation will facilitate the development of versatile autonomous multi-agent systems that are capable of performing a variety of complex tasks in a robust and scalable manner.

A new approach to assess the spasticity in hamstrings muscles using mechanomyography antagonist muscular group.

PubMed

Krueger, Eddy; Scheeren, Eduardo M; Nogueira-Neto, Guilherme N; Button, Vera Lúcia da S N; Nohama, Percy

2012-01-01

Several pathologies can cause muscle spasticity. Modified Ashworth scale (MAS) can rank spasticity, however its results depend on the physician subjective evaluation. This study aims to show a new approach to spasticity assessment by means of MMG analysis of hamstrings antagonist muscle group (quadriceps muscle). Four subjects participated in the study, divided into two groups regarding MAS (MAS0 and MAS1). MMG sensors were positioned over the muscle belly of rectus femoris (RF), vastus lateralis (VL) and vastus medialis (VM) muscles. The range of movement was acquired with an electrogoniometer placed laterally to the knee. The system was based on a LabVIEW acquisition program and the MMG sensors were built with triaxial accelerometers. The subjects were submitted to stretching reflexes and the integral of the MMG (MMG(INT)) signal was calculated to analysis. The results showed that the MMG(INT) was greater to MAS1 than to MAS0 [muscle RF (p = 0.004), VL (p = 0.001) and VM (p = 0.007)]. The results showed that MMG was viable to detect a muscular tonus increase in antagonist muscular group (quadriceps femoris) of spinal cord injured volunteers.

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.…

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

Multi-Scale Modeling of a Graphite-Epoxy-Nanotube System

NASA Technical Reports Server (NTRS)

Frankland, S. J. V.; Riddick, J. C.; Gates, T. S.

2005-01-01

A multi-scale method is utilized to determine some of the constitutive properties of a three component graphite-epoxy-nanotube system. This system is of interest because carbon nanotubes have been proposed as stiffening and toughening agents in the interlaminar regions of carbon fiber/epoxy laminates. The multi-scale method uses molecular dynamics simulation and equivalent-continuum modeling to compute three of the elastic constants of the graphite-epoxy-nanotube system: C11, C22, and C33. The 1-direction is along the nanotube axis, and the graphene sheets lie in the 1-2 plane. It was found that the C11 is only 4% larger than the C22. The nanotube therefore does have a small, but positive effect on the constitutive properties in the interlaminar region.

Clinical analysis of macrophage activation syndrome in pediatric patients with autoimmune diseases.

PubMed

Lin, Cheng-I; Yu, Hsin-Hui; Lee, Jyh-Hong; Wang, Li-Chieh; Lin, Yu-Tsan; Yang, Yao-Hsu; Chiang, Bor-Luen

2012-08-01

Macrophage activation syndrome (MAS) belongs to secondary hemophagocytic lymphohistiocytosis (HLH) syndrome. It is usually associated with rheumatic diseases. We retrospectively reviewed our hospital's medical records of 102 HLH/MAS patients from the past 20 years. Demographics, clinical data, treatment, and outcomes were analyzed. Among 102 patients, eight patients with underlying juvenile systemic lupus erythematous (two patients), mixed connective tissue disease (one patient), primary anti-phospholipid syndrome (one patient), and systemic type juvenile rheumatoid arthritis (sJRA; four patients) with 13 episodes of MAS were studied. Clinical manifestations of MAS included fever (100 %), hepatosplenomegaly (77 %), lymphadenopathy (38 %), skin rash (62 %), and neurological involvement (31 %). Laboratory features included leukopenia (54 %), anemia (46 %), thrombocytopenia (77 %), jaundice (27 %), hypofibrinogenemia (40 %), decreased erythrocyte sedimentation rate (67 %), and elevated liver enzymes (77 %), lactate dehydrogenase (100 %), ferritin (88 %), triglycerides (91 %), C-reactive protein (85 %), plasma D-dimer (50 %), and hemophagocytosis in bone marrow (83 %). The Epstein-Barr virus and adenovirus infection triggered MAS in two patients with sJRA. Methylprednisolone pulse therapy was effective in two out of three patients, and high-dose intravenous immunoglobulin (IVIG) was effective in two out of six patients. Patients with sJRA responded well to corticosteroids and cyclosporine. Complications included opportunistic infection with Pneumocystis jiroveci, multiple organ failure, and intensive care unit myopathy. The mortality rate was one out of eight (12.5 %). Our results showed that MAS could be fatal and complicate various pediatric autoimmune diseases. It generally has a good response to corticosteroids and IVIG. Prompt recognition and timely treatment can result in good outcomes.

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 5 - Phase 2 Implementation of the Concept Demonstrator

NASA Technical Reports Server (NTRS)

Batten, Adam; Dunlop, John; Edwards, Graeme; Farmer, Tony; Gaffney, Bruce; Hedley, Mark; Hoschke, Nigel; Isaacs, Peter; Johnson, Mark; Lewis, Chris;

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.

[Somatotype-dependent cardiorespiratory system adaption in children and adolsescents in the north-east of Russia].

PubMed

Bartosh, O P; Sokolov, A Ia

2006-01-01

The authors have revealed the tension of cardiovascular performance in 11-14-year-old children and adolescents with the macrosomatotype (MaS) and a lower bronchial patency in 13-14-year-old adolescents in the winter-spring period. This points to the decreased reserves of the cardiorespiratory system in the teenagers with MaS during their adaptation the environment of the north-east of Russia.

Concurrent validation of an inertial measurement system to quantify kicking biomechanics in four football codes.

PubMed

Blair, Stephanie; Duthie, Grant; Robertson, Sam; Hopkins, William; Ball, Kevin

2018-05-17

Wearable inertial measurement systems (IMS) allow for three-dimensional analysis of human movements in a sport-specific setting. This study examined the concurrent validity of a IMS (Xsens MVN system) for measuring lower extremity and pelvis kinematics in comparison to a Vicon motion analysis system (MAS) during kicking. Thirty footballers from Australian football (n = 10), soccer (n = 10), rugby league and rugby union (n = 10) clubs completed 20 kicks across four conditions. Concurrent validity was assessed using a linear mixed-modelling approach, which allowed the partition of between and within-subject variance from the device measurement error. Results were expressed in raw and standardised units for assessments of differences in means and measurement error, and interpreted via non-clinical magnitude-based inferences. Trivial to small differences were found in linear velocities (foot and pelvis), angular velocities (knee, shank and thigh), sagittal joint (knee and hip) and segment angle (shank and pelvis) means (mean difference: 0.2-5.8%) between the IMS and MAS in Australian football, soccer and the rugby codes. Trivial to small measurement errors (from 0.1 to 5.8%) were found between the IMS and MAS in all kinematic parameters. The IMS demonstrated acceptable levels of concurrent validity compared to a MAS when measuring kicking biomechanics across the four football codes. Wearable IMS offers various benefits over MAS, such as, out-of-laboratory testing, larger measurement range and quick data output, to help improve the ecological validity of biomechanical testing and the timing of feedback. The results advocate the use of IMS to quantify biomechanics of high-velocity movements in sport-specific settings. Copyright © 2018 Elsevier Ltd. All rights reserved.

Expanding the chemical diversity of natural esters by engineering a polyketide-derived pathway into Escherichia coli.

PubMed

Menendez-Bravo, Simón; Comba, Santiago; Sabatini, Martín; Arabolaza, Ana; Gramajo, Hugo

2014-07-01

Microbial fatty acid (FA)-derived molecules have emerged as promising alternatives to petroleum-based chemicals for reducing dependence on fossil hydrocarbons. However, native FA biosynthetic pathways often yield limited structural diversity, and therefore restricted physicochemical properties, of the end products by providing only a limited variety of usually linear hydrocarbons. Here we have engineered into Escherichia coli a mycocerosic polyketide synthase-based biosynthetic pathway from Mycobacterium tuberculosis and redefined its biological role towards the production of multi-methyl-branched-esters (MBEs) with novel chemical structures. Expression of FadD28, Mas and PapA5 enzymes enabled the biosynthesis of multi-methyl-branched-FA and their further esterification to an alcohol. The high substrate tolerance of these enzymes towards different FA and alcohol moieties resulted in the biosynthesis of a broad range of MBE. Further metabolic engineering of the MBE producer strain coupled this system to long-chain-alcohol biosynthetic pathways resulting in de novo production of branched wax esters following addition of only propionate. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Evolutionary Games in Multi-Agent Systems of Weighted Social Networks

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Zheng, Hao-Ran; Zhou, Hong; Hu, Mao-Bin

Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.

Skeletal muscle wasting: new role of nonclassical renin-angiotensin system.

PubMed

Cabello-Verrugio, Claudio; Rivera, Juan C; Garcia, Dominga

2017-05-01

Skeletal muscle can be affected by many physiological and pathological conditions that contribute to the development of muscle weakness, including skeletal muscle loss, inflammatory processes, or fibrosis. Therefore, research into therapeutic treatment alternatives or alleviation of these effects on skeletal muscle is of great importance. Recent studies have shown that angiotensin (1-7) [Ang-(1-7)] - a vasoactive peptide of the nonclassical axis in the renin-angiotensin system (RAS) - and its Mas receptor are expressed in skeletal muscle. Ang-(1-7), through its Mas receptor, prevents or diminishes deleterious effects induced by skeletal muscle disease or injury. Specifically, the Ang-(1-7)-Mas receptor axis modulates molecular mechanisms involved in muscle mass regulation, such as the ubiquitin proteasome pathway, the insulin-like growth factor type 1/Akt (protein kinase B) pathway, or myonuclear apoptosis, and also inflammation and fibrosis pathways. Although further research into this topic and the possible side effects of Ang-(1-7) is necessary, these findings are promising, and suggest that the Ang-(1-7)-Mas axis can be considered a possible therapeutic target for treating patients with muscular disorders.

Progress and challenges in the development of physically-based numerical models for prediction of flow and contaminant dispersion in the urban environment

NASA Astrophysics Data System (ADS)

Lien, F. S.; Yee, E.; Ji, H.; Keats, A.; Hsieh, K. J.

2006-06-01

The release of chemical, biological, radiological, or nuclear (CBRN) agents by terrorists or rogue states in a North American city (densely populated urban centre) and the subsequent exposure, deposition and contamination are emerging threats in an uncertain world. The modeling of the transport, dispersion, deposition and fate of a CBRN agent released in an urban environment is an extremely complex problem that encompasses potentially multiple space and time scales. The availability of high-fidelity, time-dependent models for the prediction of a CBRN agent's movement and fate in a complex urban environment can provide the strongest technical and scientific foundation for support of Canada's more broadly based effort at advancing counter-terrorism planning and operational capabilities.The objective of this paper is to report the progress of developing and validating an integrated, state-of-the-art, high-fidelity multi-scale, multi-physics modeling system for the accurate and efficient prediction of urban flow and dispersion of CBRN (and other toxic) materials discharged into these flows. Development of this proposed multi-scale modeling system will provide the real-time modeling and simulation tool required to predict injuries, casualties and contamination and to make relevant decisions (based on the strongest technical and scientific foundations) in order to minimize the consequences of a CBRN incident in a populated centre.

Outdoor flocking of quadcopter drones with decentralized model predictive control.

PubMed

Yuan, Quan; Zhan, Jingyuan; Li, Xiang

2017-11-01

In this paper, we present a multi-drone system featured with a decentralized model predictive control (DMPC) flocking algorithm. The drones gather localized information from neighbors and update their velocities using the DMPC flocking algorithm. In the multi-drone system, data packages are transmitted through XBee ® wireless modules in broadcast mode, yielding such an anonymous and decentralized system where all the calculations and controls are completed on an onboard minicomputer of each drone. Each drone is a double-layered agent system with the coordination layer running multi-drone flocking algorithms and the flight control layer navigating the drone, and the final formation of the flock relies on both the communication range and the desired inter-drone distance. We give both numerical simulations and field tests with a flock of five drones, showing that the DMPC flocking algorithm performs well on the presented multi-drone system in both the convergence rate and the ability of tracking a desired path. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The development, validation and application of a multi-detector CT (MDCT) scanner model for assessing organ doses to the pregnant patient and the fetus using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Gu, J.; Bednarz, B.; Caracappa, P. F.; Xu, X. G.

2009-05-01

The latest multiple-detector technologies have further increased the popularity of x-ray CT as a diagnostic imaging modality. There is a continuing need to assess the potential radiation risk associated with such rapidly evolving multi-detector CT (MDCT) modalities and scanning protocols. This need can be met by the use of CT source models that are integrated with patient computational phantoms for organ dose calculations. Based on this purpose, this work developed and validated an MDCT scanner using the Monte Carlo method, and meanwhile the pregnant patient phantoms were integrated into the MDCT scanner model for assessment of the dose to the fetus as well as doses to the organs or tissues of the pregnant patient phantom. A Monte Carlo code, MCNPX, was used to simulate the x-ray source including the energy spectrum, filter and scan trajectory. Detailed CT scanner components were specified using an iterative trial-and-error procedure for a GE LightSpeed CT scanner. The scanner model was validated by comparing simulated results against measured CTDI values and dose profiles reported in the literature. The source movement along the helical trajectory was simulated using the pitch of 0.9375 and 1.375, respectively. The validated scanner model was then integrated with phantoms of a pregnant patient in three different gestational periods to calculate organ doses. It was found that the dose to the fetus of the 3 month pregnant patient phantom was 0.13 mGy/100 mAs and 0.57 mGy/100 mAs from the chest and kidney scan, respectively. For the chest scan of the 6 month patient phantom and the 9 month patient phantom, the fetal doses were 0.21 mGy/100 mAs and 0.26 mGy/100 mAs, respectively. The paper also discusses how these fetal dose values can be used to evaluate imaging procedures and to assess risk using recommendations of the report from AAPM Task Group 36. This work demonstrates the ability of modeling and validating an MDCT scanner by the Monte Carlo method, as well as assessing fetal and organ doses by combining the MDCT scanner model and the pregnant patient phantom.

Distributed Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2005-01-01

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

NASA Astrophysics Data System (ADS)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

Application of Fuzzy State Aggregation and Policy Hill Climbing to Multi-Agent Systems in Stochastic Environments

DTIC Science & Technology

2006-03-01

represented by the set of tiles that it lies in. A variation on tile coding is Berenji and Vengerov’s [4, 5] use of fuzzy state aggregation (FSA) as a means...approximation with Q-learning is not a new or unusual concept [1, 3]. Berenji and Vengerov [4, 5] advanced this work in their application of Q-learning and... Berenji and Vengerov [4, 5]. The simplified Tileworld consists of agents, reward spikes, and deformations. The agent must select which reward to pursue

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

Coordinating Learning Agents for Active Information Collection

DTIC Science & Technology

2011-06-30

the experiments were not particularly sensitive to this parameter. By limiting the number of actions that are updated (DANT-L in black/ dark ), the...Bazzan, A. and Ossowski, S. (eds.), Applications of Agent Technology in Traffic and Transportation (Springer, 2005). [19] Mataric , M. J., Coordination...organizing market (1998), preprint cond- mat/9802177. [19] Jones, C. and Mataric , M. J., Adaptive division of labor in large-scale multi-robot systems, in IEEE