Search results for "Multiagent system"

showing 10 items of 108 documents

Robust dynamic cooperative games

2009

Classical cooperative game theory is no longer a suitable tool for those situations where the values of coalitions are not known with certainty. Recent works address situations where the values of coalitions are modelled by random variables. In this work we still consider the values of coalitions as uncertain, but model them as unknown but bounded disturbances. We do not focus on solving a specific game, but rather consider a family of games described by a polyhedron: each point in the polyhedron is a vector of coalitions’ values and corresponds to a specific game. We consider a dynamic context where while we know with certainty the average value of each coalition on the long run, at each t…

Statistics and ProbabilityBondareva–Shapley theoremEconomics and EconometricsNon-cooperative gameComputer Science::Computer Science and Game TheoryMSC-91A12Sequential gameMSC-91A25Computer scienceCooperative games Dynamic games Joint replenishmentCombinatorial game theoryTheoryofComputation_GENERALCooperative game theoryMETIS-263773Computer Science::Multiagent SystemsMathematics (miscellaneous)Example of a game without a valueEWI-15215Repeated gameIR-62781Simultaneous gameStatistics Probability and UncertaintyMathematical economicsSocial Sciences (miscellaneous)International journal of game theory
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Selfish vs. Unselfish Optimization of Network Creation

2005

We investigate several variants of a network creation model: a group of agents builds up a network between them while trying to keep the costs of this network small. The cost function consists of two addends, namely (i) a constant amount for each edge an agent buys and (ii) the minimum number of hops it takes sending messages to other agents. Despite the simplicity of this model, various complex network structures emerge depending on the weight between the two addends of the cost function and on the selfish or unselfish behaviour of the agents.

Statistics and ProbabilityNetworking and Internet Architecture (cs.NI)FOS: Computer and information sciencesGroup (mathematics)Computer sciencemedia_common.quotation_subjectStatistical and Nonlinear PhysicsFunction (mathematics)Complex networkTopologyComputer Science - Networking and Internet ArchitectureHardware Architecture (cs.AR)Computer Science - Multiagent SystemsSimplicityEnhanced Data Rates for GSM EvolutionStatistics Probability and UncertaintyConstant (mathematics)Computer Science - Hardware Architecturemedia_commonMultiagent Systems (cs.MA)
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Distributed Consensus for Discrete-Time Directed Networks of Multiagents with Time-Delays and Random Communication Links

2013

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/158731 Open Access This paper is concerned with the leader-following consensus problem in mean-square for a class of discrete-time multiagent systems. The multiagent systems under consideration are the directed and contain arbitrary discrete time-delays. The communication links are assumed to be time-varying and stochastic. It is also assumed that some agents in the network are well informed and act as leaders, and the others are followers. By introducing novel Lyapunov functionals and employing some new analytical techniques, sufficient conditi…

Time delaysClass (set theory)Mathematical optimizationArticle Subjectlcsh:MathematicsApplied MathematicsMulti-agent systemlcsh:QA1-939Computer Science::Multiagent SystemsDiscrete time and continuous timeConsensusLyapunov functionalControl theoryVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Analyse: 411State (computer science)AnalysisMathematicsAbstract and Applied Analysis
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Semantic oriented data structuration for MABS Application to BIM

2013

International audience; This paper presents a multiagent-based simulation approach to qualify the usage of buildings from the design phase. Our approach combines ontology and evolution process based on machine learning algorithms. The ontology relies on semantic data structures for the representation of environment components, agent knowledge and all data generated during the simulation.

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationComputer scienceProcess (engineering)0211 other engineering and technologies020101 civil engineering02 engineering and technologyOntology (information science)Semantic data modelcomputer.software_genre0201 civil engineering021105 building & constructionUpper ontologyRepresentation (mathematics)business.industryOntology-based data integration[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationDesign phaseBuilding information modeling[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationData miningbusinessSoftware engineeringcomputer
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A spatially explicit model to simulate soil microbial communities’ dynamics at an agricultural landscape scale

2021

Soil microorganisms play a major role in soil functions and are an efficient indicator to evaluate the impact of agricultural practices on soil quality. Biogeographical studies over wide scales ranging from landscape to countries have concluded that soil microbial abundance and soil prokaryotic richness is following a heterogeneous distribution in space under the dependence of soil properties (e.g. pH, soil texture, organic matter content) and agricultural practices. The goal of this study is the creation of a model that can predict dynamics of soil microbial communities depending on the agricultural management over time. For this, we focus on a monitored landscape (Fénay landscape, 1.200 h…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Agent-based modelAgricultural landscapeParticipatory[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationSoil microbial communities
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An ABM to support collective reflection on the evolution of mobility

2021

International audience; Transport infrastructures play a large part in defining a smart, sustainable and resilient city. Planning transportation systems traditionally rely on well-known evolutions of roads or public transportation (roundabouts for security, etc.). Yet, infrastructures might also benefit from, or may have to adapt to, recent disruptive innovations concerning modalities, technologies and societal organization (autonomous cars, smart infrastructure, homeworking, etc.). However, innovative urban policies might either facilitate mobility and increase citizen well-being, or create negative side effects. Urban planning therefore requires the city to assess the impact of these disr…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Traffic simulation[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationCollective reflection supportProspective simulation[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Urban mobility
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Scheduling independent stochastic tasks under deadline and budget constraints

2018

This article discusses scheduling strategies for the problem of maximizing the expected number of tasks that can be executed on a cloud platform within a given budget and under a deadline constraint. The execution times of tasks follow independent and identically distributed probability laws. The main questions are how many processors to enroll and whether and when to interrupt tasks that have been executing for some time. We provide complexity results and an asymptotically optimal strategy for the problem instance with discrete probability distributions and without deadline. We extend the latter strategy for the general case with continuous distributions and a deadline and we design an ef…

[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]Mathematical optimizationOperations researchComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Cloud computing[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technologyExpected valueTheoretical Computer ScienceScheduling (computing)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]deadline0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]schedulingComputer Science::Operating SystemsComputingMilieux_MISCELLANEOUSBudget constraint020203 distributed computingcloud platformindependent tasksbusiness.industry[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationstochastic costAsymptotically optimal algorithmContinuous distributions[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Hardware and ArchitectureProbability distribution[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processingInterrupt[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessSoftwarebudget
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Probability and algorithmics: a focus on some recent developments

2017

Jean-François Coeurjolly, Adeline Leclercq-Samson Eds.; International audience; This article presents different recent theoretical results illustrating the interactions between probability and algorithmics. These contributions deal with various topics: cellular automata and calculability, variable length Markov chains and persistent random walks, perfect sampling via coupling from the past. All of them involve discrete dynamics on complex random structures.; Cet article présente différents résultats récents de nature théorique illustrant les interactions entre probabilités et algorithmique. Ces contributions traitent de sujets variés : automates cellulaires et calculabilité, chaînes de Mark…

[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]T57-57.97Focus (computing)Applied mathematics. Quantitative methodsTheoretical computer scienceMarkov chainComputer science[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]Variable lengthRandom walkCellular automaton[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Perfect sampling[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Coupling from the past[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Algorithmics[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]QA1-939Mathematics
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Automated detection of contextuality proofs with intermediate numbers of observables

2021

<div style=""&gt<font face="arial, helvetica"&gt<span style="font-size: 13px;"&gtQuantum contextuality takes an important place amongst the concepts of quantum computing that bring an advantage over its classical counterpart. For a large class of contextuality </span&gt</font&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtproofs, aka. observable-based proofs of the Kochen-Specker Theorem, we first formulate the</span&gt</div&gt<div style=""&gt<font face="arial, helvetica"&gt<span style="font-size: 13px;"&gtcontextuality property as the absence of solutions to a linear system. Then we explain why </span&gt</font&gt<span style="font-size: 13px; font-family: arial, helvetica…

[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC][INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
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A Route toward Protein Sequencing using Solid-State Nanopores Assisted by Machine Learning

2022

Solid-State Nanopores made of 2-D materials such as MoS2 have emerged as one of the most versatile sensors for single-biomolecule detection, which is essential for early disease diagnosis (biomarker detection). One of the most promising applications of SSN is DNA and protein sequencing, at a low cost and faster than the current standard methods. The detection principle relies on measuring the relatively small variations of ionic current as charged biomolecules immersed in an electrolyte traverse the nanopore, in response to an external voltage applied across the membrane. The passage of a biomolecule through the pore yields information about its structure and chemical properties, as demonst…

[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC][INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
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