Search results for "Multi-Agent system"

showing 10 items of 154 documents

Edge-Based Missing Data Imputation in Large-Scale Environments

2021

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis

010504 meteorology & atmospheric sciencesComputer scienceDistributed computingUrban sensingMobile sensingContext (language use)Information technology02 engineering and technology01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Smart cityEdge intelligence11. Sustainability0202 electrical engineering electronic engineering information engineeringLeverage (statistics)Edge computingVoronoi tessellation0105 earth and related environmental sciencesSmart cityOut-of-order executionSettore INF/01 - InformaticaMulti-agent systemMissing data imputation020206 networking & telecommunicationsT58.5-58.64Variety (cybernetics)Multi-agent system[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Mobile deviceInformation Systems
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Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection

2015

This volume presents the papers that have been accepted for the 2015 special sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, held at University of Salamanca, Spain, at 3rd-5th June, 2015: Agents Behaviours and Artificial Markets (ABAM); Agents and Mobile Devices (AM); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and Recommender systems (WebMiRes); Learning, Agents and Formal Languages (LAFLang); Agent-based Modeling of Sustainable Behavior and Green Economies (AMSBGE); Emotional Software Agents (SSESA) and Intelligent Educational Systems (SSIES). The volume also includes the paper accepted for the Doctoral Conso…

0209 industrial biotechnologyAmbient intelligenceManagement scienceComputer scienceMulti-agent system02 engineering and technologyRecommender systemComputingMethodologies_ARTIFICIALINTELLIGENCEEngineering management020901 industrial engineering & automationWeb miningSoftware agentSustainability0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingMobile deviceDissemination
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Tracking Control of Networked Multi-Agent Systems Under New Characterizations of Impulses and Its Applications in Robotic Systems

2016

This paper examines the problem of tracking control of networked multi-agent systems with multiple delays and impulsive effects, whose results are applied to mechanical robotic systems. Four kinds of impulsive effects are taken into account: 1) both the strengths of impulsive effects and the number of nodes injected with impulses are time dependent; 2) the strengths of impulsive effects occur according to certain probabilities and the number of nodes under impulsive control is time varying; 3) the strengths of impulses are time varying, whereas the number of nodes with impulses takes place according to certain probabilities; 4) both the strengths of impulses and the number of nodes with imp…

0209 industrial biotechnologyEngineeringTracking controlControl (management)02 engineering and technologyTracking (particle physics)robotic systems020901 industrial engineering & automationControl theory0202 electrical engineering electronic engineering information engineeringmulti-agent systemsElectrical and Electronic EngineeringRobot kinematicsbusiness.industryStochastic processMulti-agent systemtime-delaysComputer Science Applications1707 Computer Vision and Pattern RecognitionControl engineeringRobotic systemsLeader-following consensusControl and Systems EngineeringControl systemLeader-following consensus; multi-agent systems; robotic systems; time-delays; Tracking control; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering020201 artificial intelligence & image processingbusinessIEEE Transactions on Industrial Electronics
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Engineering multi-agent systems using feedback loops and holarchies

2016

This paper presents a methodological approach for the engineering of Multi-Agent Systems using feedback loops as a first class concept in order to identify organizations. Feedback loops are a way for modeling complex systems that expose emergent behavior by means of a cause-effect loop between two levels called micro and macro levels of the system. The proposed approach principles consist in defining an abstract feedback loop pattern and providing activities and guidelines in order to identify and refine possible candidates for feedback loops during the analysis phase of the Aspecs methodology. This approach is illustrated by using an example drawn from the smart grid field.

0209 industrial biotechnologyLoop (graph theory)Computer scienceMulti-agent systemMulti-agent systemsMethodologyControl engineering02 engineering and technologyFeedback loopFeedback loopsField (computer science)020901 industrial engineering & automationSmart gridHolarchiesMulti-agent systemArtificial IntelligenceControl and Systems Engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingFeedback loopElectrical and Electronic EngineeringHolarchie
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Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population

2019

We consider a multi-population, represented by a network of groups of individuals. Every player of each group can choose between two options, and we study the problem of reaching consensus. The dynamics not only depend on the dynamics within the group, but they also depend on the topology of the network, so neighboring groups influence individuals as well. First, we develop a mathematical model of this networked bio-inspired evolutionary behavior and we study its steady-state. We look at the special case where the underlying network topology is a regular and unweighted graph and show that the steady-state is a consensus equilibrium. A sufficient condition for exponential stability is given.…

0209 industrial biotechnologyTheoretical computer scienceComputer scienceMulti-agent system020208 electrical & electronic engineering02 engineering and technologyNetwork topologyGroup decision-making020901 industrial engineering & automationExponential stability0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)Special caseEvolutionary dynamicsTopology (chemistry)2019 18th European Control Conference (ECC)
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Tolerating malicious monitors in detecting misbehaving robots

2008

This paper considers a multi–agent system and focuses on the detection of motion misbehavior. Previous work by the authors proposed a solution, where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors. In this work, we consider possible failure of monitors that may send incorrect information to their neighbors due to spontaneous or even malicious malfunctioning. In this context, we propose a distributed software architecture that is able to tolerate such failures. Effectiveness of the proposed solution is shown through preliminary simulation results.

0209 industrial biotechnologybusiness.industryComputer scienceDistributed computing020206 networking & telecommunicationsContext (language use)security02 engineering and technologyMotion (physics)consensus algorithm020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaWork (electrical)Embedded system0202 electrical engineering electronic engineering information engineeringRobotDistributed software architectureIntrusion detectionmulti-agent systemsSoftware architecturebusiness
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Decentralised trust-management inspired by ant pheromones

2017

Computational trust is increasingly utilised to select interaction partners in open technical systems consisting of heterogeneous, autonomous agents. Current approaches rely on centralised elements for managing trust ratings (i.e. control and provide access to aggregated ratings). Consider a grid computing application as illustrating example: agents share their computing resources and cooperate in terms of processing computing jobs. These agents are free to join and leave, and they decide on their own with whom to interact. The impact of malicious or uncooperative agents can be countered by only cooperating with agents that have shown to be benevolent: trust relationships are established. T…

0301 basic medicinebusiness.industryComputer scienceComputer Networks and CommunicationsMulti-agent systemAutonomous agent02 engineering and technologyOrganic computingGridcomputer.software_genreComputer securityManagement Information SystemsPublic-key cryptography03 medical and health sciences030104 developmental biologyGrid computingArtificial Intelligence0202 electrical engineering electronic engineering information engineeringTrust management (information system)020201 artificial intelligence & image processingComputational trustbusinesscomputerSoftwareInternational Journal of Mobile Network Design and Innovation
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Distributed channel prediction for multi-agent systems

2017

Los sistemas multiagente (MAS) se comunican a través de una red inalámbrica para coordinar sus acciones e informar sobre el estado de su misión. La conectividad y el rendimiento del sistema pueden mejorarse mediante la predicción de la ganancia del canal. Presentamos un esquema basado en regresión de procesos gaussianos (GPR) distribuidos para predecir el canal inalámbrico en términos de la potencia recibida en el MAS. El esquema combina una máquina de comité bayesiano con un esquema de consenso medio, distribuyendo así no sólo la memoria sino también la carga computacional y de comunicación. A través de simulaciones de Monte Carlo, demostramos el rendimiento del GPR propuesto. RACHEL TEC20…

:CIENCIAS TECNOLÓGICAS [UNESCO]Wireless networkComputer sciencebusiness.industryDistributed computingMulti-agent systemMonte Carlo method020206 networking & telecommunicationsBayesian committee machine02 engineering and technologyUNESCO::CIENCIAS TECNOLÓGICASKriging0202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingmulti-agent systemsbusinessgaussian process regressionSimulationCommunication channelaverage consensus scheme
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Implementation Challenges for Supporting Coworking Virtual Enterprises

2013

The creation of co working alliances is usually restricted to the coworkers in the same workspace. However, they might not necessarily be best partners to take advantage of a collaboration opportunity. To break the spatial constrains and find the best partners irrespective of their co working spaces location, our proposal is to represent and manage the co working alliances as virtual enterprises (VEs) and to develop a multi-agent system (MAS) that serves as Virtual Breeding Environment (VBE). In this paper we provide the basis for the future development of this system. Thus, we introduce the co working VEs distinguishing features and the initial proposals on how to implement the MAS to addr…

AllianceKnowledge managementComputer scienceCo workingbusiness.industryMulti-agent systemHuman resource managementPeer to peer computingWorkspacebusiness2013 IEEE 10th International Conference on e-Business Engineering
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Understanding social behavior evolutions through agent-based modeling

2012

Agent-based social simulation as a computational approach to social simulation has been largely used to explore social phenomena. The purpose of this paper is to describe a theoretical model of transmission and evolution of social behaviors in a network of artificial societies (artificial world) using agent-based modeling technology. In this model, each agent (society) is subdivided into social behaviors where individual and social learning occur. The agent-agent interactions are carried out by their social behaviors; otherwise the agent-environment interactions through consumption of ecological resources by its social behaviors in repression and satisfaction. We distinguish social behavior…

Artificial worldSocial dynamicsGlobalizationManagement scienceComputer sciencebusiness.industryMulti-agent systemArtificial intelligencebusinessSocial learningSocial heuristicsSocial behaviorSocial simulation2012 International Conference on Multimedia Computing and Systems
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