Search results for "Multiagent system"

showing 10 items of 108 documents

MECHANISM DESIGN FOR OPTIMAL CONSENSUS PROBLEMS

2006

We consider stationary consensus protocols for networks of dynamic agents with fixed and switching topologies. At each time instant, each agent knows only its and its neighbors’ state, but must reach consensus on a group decision value that is function of all the agents’ initial state.We show that our protocol design is the solution of individual optimizations performed by the agents. This notion suggests a game theoretic interpretation of consensus problems as mechanism design problems. Under this perspective a supervisor entails the agents to reach a consensus by imposing individual objectives. We prove that such objectives can be chosen so that rational agents have a unique optimal proto…

Mathematical optimizationMechanism designDynamic agentsComputer sciencemedia_common.quotation_subjectDistributed computingmechanismcontainment controlRational agentStationary consensus protocolsNetwork topologyTopologyUniform consensusComputer Science::Multiagent SystemsSwitching topologiesComputer Science::Systems and ControlDynamic agents; Protocol design; Stationary consensus protocols; Switching topologiesSettore MAT/09 - Ricerca OperativaFunction (engineering)Protocol designProtocol (object-oriented programming)Game theoryMulti agent systemsmedia_common
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Towards a Formal Analysis of MQtt Protocol in the Context of Communicating Vehicles

2017

International audience; The paper presents a formal approach to model, analyze, and verify a variant of Message Queue Telemetry Transport protocol (MQtt), dedicated to communicating vehicles (MQtt-CV) that send collected data to automotive infrastructures(subscribers). Our formal approach is based on Promela language and its system verification tool, the model checker SPIN. We propose a slight modification of MQtt protocol to reduce the big volume of data collected and sent by vehicles to infrastructures. Indeed, in the original version of MQtt protocol, when a broker receives data from publishers, it sends them directly to its subscribers without any filtration. As consequence, subscribers…

Model checkingComputer scienceDistributed computingAutomotive industryContext (language use)02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringProtocol (object-oriented programming)computer.programming_languageMQTTbusiness.industryVolume (computing)020206 networking & telecommunications020207 software engineering[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationPromela[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessMessage queuecomputerComputer network
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Deciding properties of integral relational automata

1994

This paper investigates automated model checking possibilities for CTL* formulae over infinite transition systems represented by relational automata (RA). The general model checking problem for CTL* formulae over RA is shown undecidable, the undecidability being observed already on the class of Restricted CTL formulae. The decidability result, however, is obtained for another substantial subset of the logic, called A-CTL*+, which includes all ”linear time” formulae.

Model checkingDiscrete mathematicsClass (set theory)TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESComputer scienceComputer Science::Software EngineeringDecidabilityUndecidable problemComputer Science::Multiagent SystemsCTL*TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESRelational calculusTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSComputer Science::Logic in Computer ScienceAutomata theoryTime complexityComputer Science::Formal Languages and Automata Theory
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Ontology-based multiagent systems using Inductive Recommendations - A new approach to qualify building use during the Design phase

2012

International audience; In this paper we propose a new metamodel to represent data for mutliagent-based simulations. Using this model, we also propose a method to perform the qualification of a building as soon as it is designed. The metamodel relies on semantic structures and allows representing both agents and environment. The representation of the environment use two kind of data: semantic and geometry. The qualification relies, for its part, on reasoning systems.

Ontology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA]IFC[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA]RecommendationSemanticMultiagent SystemsInduction
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Forecasting Adverse Weather Situations in the Road Network

2016

Weather is an important factor that affects traffic flow and road safety. Adverse weather situations affect the driving conditions directly; hence, drivers must be informed about the weather conditions downstream to adapt their driving. In the framework of intelligent transport systems, several systems have been developed to know the weather situations and inform drivers. However, these systems do not forecast weather in advance, and they need the support of road operators to inform drivers. This paper presents a new autonomous system to forecast weather conditions in a short time and to give users the information obtained. The system uses a set of algorithms and rules to determine the weat…

Operations researchComputer sciencemedia_common.quotation_subjectTransport per carreteraexpert systems02 engineering and technologyInvestigació0502 economics and business0202 electrical engineering electronic engineering information engineeringRoad Weather Information SystemQuality (business)MeteorologiaSet (psychology)Intelligent transportation systemDownstream (networking)media_commonintelligent transport systems (ITS)050210 logistics & transportationAdverse weatherSeguretat viàriaMechanical Engineeringmultiagent system05 social sciencesTraffic flowComputer Science ApplicationsAutomotive EngineeringAccidents Prevenció020201 artificial intelligence & image processingAutonomous system (mathematics)
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Stock markets and quantum dynamics: A second quantized description

2009

In this paper we continue our description of stock markets in terms of some non-abelian operators which are used to describe the portfolio of the various traders and other observable quantities. After a first prototype model with only two traders, we discuss a more realistic model of market involving an arbitrary number of traders. For both models we find approximated solutions for the time evolution of the portfolio of each trader. In particular, for the more realistic model, we use the stochastic limit approach and a fixed point like approximation. © 2007 Elsevier B.V. All rights reserved

Physics::Physics and SocietyStatistics and ProbabilitySecond quantizationComputer Science::Computer Science and Game TheoryQuantitative Finance - Trading and Market MicrostructureQuantum dynamicQuantum dynamicsTime evolutionObservableStock marketsFixed pointCondensed Matter PhysicsSecond quantizationTrading and Market Microstructure (q-fin.TR)FOS: Economics and businessComputer Science::Multiagent SystemsComputer Science::Computational Engineering Finance and SciencePortfolioStatistical physicsSettore MAT/07 - Fisica MatematicaMathematical economicsStock (geology)MathematicsPhysica A: Statistical Mechanics and its Applications
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On the collision property of chaotic iterations based post-treatments over cryptographic pseudorandom number generators

2018

International audience; There is not a proper mathematical definition of chaos, we have instead a quite big amount of definitions, each of one describes chaos in a more or less general context. Taking in account this, it is clear why it is hard to design an algorithm that produce random numbers, a kind of algorithm that could have plenty of concrete appliceautifat (anul)d bions. However we must use a finite state machine (e.g. a laptop) to produce such a sequence of random numbers, thus it is convenient, for obvious reasons, to redefine those aimed sequences as pseudorandom; also problems arise with floating point arithmetic if one wants to recover some real chaotic property (i.e. propertie…

Pseudorandom number generator020203 distributed computingSequenceFinite-state machineDynamical systems theoryComputer science010102 general mathematicsChaotic[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]0202 electrical engineering electronic engineering information engineering[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]0101 mathematicsBoolean functionAlgorithmRandomnessGenerator (mathematics)2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)
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Energy-Efficiency and Coverage Quality Management for Reliable Diagnostics in Wireless Sensor Networks

2020

International audience; The processing of data and signals provided by sensors aims at extracting rnrelevant features which can be used to assess and diagnose the health state rnof the monitored targets. Nevertheless, Wireless Sensor Networks (WSNs) present rna number of shortcomings that have an impact on the quality of the gathered rndata at the sink level, leading to imprecise diagnostics rnof the observed targets. To improve data accuracy, two main critical and related issues, namely the energy consumption and coverage quality, need to be considered. The goal is to maximize the network lifetime while guaranteeing the complete coverage of all the targets. Unfortunately, these performance…

Quality managementComputer scienceComputer Networks and CommunicationsReal-time computingCorrectness proofs020206 networking & telecommunicationsEnergy consumption02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science Applications[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Distributed algorithmControl and Systems Engineering[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Data accuracy0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Electrical and Electronic Engineering[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Wireless sensor networkEfficient energy use
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On Analytical vs . Schizophrenic Procedures for Computing Music

2009

The authors present a perspective on computer music, which is based on some particular definitions of music in relation to oral culture and cybernetics. They describe some experiments with different models of neural architectures which generate original music, and then suggest that if such neural systems are rich, effective and intuitive enough to produce ‘live’ music, the understanding of their behaviour may require the development of some ‘schizophrenic’ procedures, as well as analytical ones.

Relation (database)Computer science[ SHS.MUSIQ ] Humanities and Social Sciences/Musicology and performing arts[SCCO.COMP]Cognitive science/Computer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]050105 experimental psychology[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]03 medical and health sciences0302 clinical medicine[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC]Music information retrievalCybernetics0501 psychology and cognitive sciences[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC][ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSCognitive science[SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts[ INFO.INFO-ET ] Computer Science [cs]/Emerging Technologies [cs.ET]Artificial neural networkMulti-agent system[SCCO.NEUR]Cognitive science/Neuroscience05 social sciencesPerspective (graphical)Pop music automation[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnology[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD][ SCCO.NEUR ] Cognitive science/Neuroscience[ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA]Computer music[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.EIAH]Computer Science [cs]/Technology for Human Learning[ INFO.INFO-SD ] Computer Science [cs]/Sound [cs.SD][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgeryMusic
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A Framework to Improve the Disaster Response Through a Knowledge-Based Multi-Agent System

2017

The disaster response still faces problems of collaboration due to lack of policies concerning the information exchange during the response. Moreover, plans are prepared to respond to a disaster, but drills to apply them are limited and do not allow to determine their efficiency and conflicts with other organizations. This paper presents a framework allowing for different organizations involving in the disaster response to assess their collaboration through its simulation using an explicit representation of their knowledge. This framework is based on a multi-agent system composed of three generic agent models to represent the organizational structure of disaster response. The decision-makin…

Risk analysis (engineering)010201 computation theory & mathematicsComputer science[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]020204 information systemsMulti-agent system0202 electrical engineering electronic engineering information engineering0102 computer and information sciences02 engineering and technology[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA]Disaster response01 natural sciencesComputingMilieux_MISCELLANEOUS
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