Search results for "Multiagent Systems"

showing 10 items of 104 documents

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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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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Checkpointing Workflows for Fail-Stop Errors

2017

International audience; We consider the problem of orchestrating the exe- cution of workflow applications structured as Directed Acyclic Graphs (DAGs) on parallel computing platforms that are subject to fail-stop failures. The objective is to minimize expected overall execution time, or makespan. A solution to this problem consists of a schedule of the workflow tasks on the available processors and of a decision of which application data to checkpoint to stable storage, so as to mitigate the impact of processor failures. For general DAGs this problem is hopelessly intractable. In fact, given a solution, computing its expected makespan is still a difficult problem. To address this challenge,…

ScheduleComputer scienceworkflowDistributed computing[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]010103 numerical & computational mathematics02 engineering and technologyParallel computing[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciencesTheoretical Computer Science[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]checkpointfail-stop error0202 electrical engineering electronic engineering information engineeringOverhead (computing)[INFO]Computer Science [cs]0101 mathematicsresilienceClass (computer programming)020203 distributed computingJob shop schedulingProbabilistic logic020206 networking & telecommunications[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationDynamic programmingTask (computing)[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF]WorkflowComputational Theory and MathematicsHardware and Architecture[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Task analysis[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Software
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Serial In-network Processing for Large Stationary Wireless Sensor Networks

2017

International audience; In wireless sensor networks, a serial processing algorithm browses nodes one by one and can perform different tasks such as: creating a schedule among nodes, querying or gathering data from nodes, supplying nodes with data, etc. Apart from the fact thatserial algorithms totally avoid collisions, numerous recent works have confirmed that these algorithms reduce communications andconsiderably save energy and time in large-dense networks. Yet, due to the path construction complexity, the proposed algorithmsare not optimal and their performances can be further enhanced. To do so, in the present paper, we propose a new serial processing algorithm that, in most of the case…

ScheduleVisual sensor networkbusiness.industryComputer science020206 networking & telecommunications02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation020202 computer hardware & architectureSerial memory processing[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingKey distribution in wireless sensor networks[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Sensor nodeScalability0202 electrical engineering electronic engineering information engineeringMobile wireless sensor network[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkComputer network
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Chaotic multiagent system approach for MRF-based image segmentation

2005

In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.

Segmentation-based object categorizationbusiness.industryComputer scienceMulti-agent systemCrossoverComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONChaoticScale-space segmentationImage segmentationComputingMethodologies_ARTIFICIALINTELLIGENCENonlinear Sciences::Chaotic DynamicsComputer Science::Multiagent SystemsComputerSystemsOrganization_MISCELLANEOUSComputer Science::Computer Vision and Pattern RecognitionIterated conditional modesSegmentationComputer visionArtificial intelligencebusinessISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.
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