Search results for "Consensus protocols"

showing 4 items of 14 documents

Consensus in inventory games

2008

This paper studies design, convergence, stability and optimality of a distributed consensus protocol for n-player repeated non cooperative games under incomplete information. Information available to each player concerning the other players' strategies evolves in time. At each stage (time period), the players select myopically their best binary strategy on the basis of a payoff, defined on a single stage, monotonically decreasing with the number of active players. The game is specialized to an inventory application, where fixed costs are shared among all retailers, interested in reordering or not from a common warehouse. As information evolves in time, the number of active players changes t…

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game TheoryInventoryMulti-agent systemsStochastic gameComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALConsensus protocols; Game theory; Inventory; Multi-agent systemsOutcome (game theory)Consensus protocolssymbols.namesakeBayesian gameNash equilibriumBest responsesymbolsRepeated gameEconomicsCoordination gameMathematical economicsGame theoryGame theoryProceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
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Noncooperative dynamic games for inventory applications: A consensus approach

2008

We focus on a finite horizon noncooperative dynamic game where the stage cost of a single player associated to a decision is a monotonically nonincreasing function of the total number of players making the same decision. For the single-stage version of the game, we characterize Nash equilibria and derive a consensus protocol that makes the players converge to the unique Pareto optimal Nash equilibrium. Such an equilibrium guarantees the interests of the players and is also social optimal in the set of Nash equilibria. For the multi-stage version of the game, we present an algorithm that converges to Nash equilibria, unfortunately not necessarily Pareto optimal. The algorithm returns a seque…

TheoryofComputation_MISCELLANEOUSDynamic gamesComputer Science::Computer Science and Game TheoryMathematical optimizationCorrelated equilibriumSequential gameConsensus ProtocolsComputer scienceA-priori; Consensus protocols; Dynamic games; Finite horizons; Inventory; Inventory systems; Joint decisions; Multi stages; Nash equilibrium; Pareto-optimal; Single stages; Unilateral improvementsSymmetric equilibriumOutcome (game theory)Joint decisionsNash equilibriumFinite horizonsMulti stagessymbols.namesakeBayesian gameSettore ING-INF/04 - AutomaticaPareto-optimalA-prioriCoordination gameFolk theoremPrice of stabilityRisk dominanceNon-credible threatConsensus Protocols Dynamic Programming Game Theory InventoryInventory systemsTraveler's dilemmaNormal-form gameStochastic gameInventoryComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALMinimaxConsensus protocolsEquilibrium selectionNash equilibriumBest responseSingle stagesRepeated gamesymbolsEpsilon-equilibriumSettore MAT/09 - Ricerca OperativaSolution conceptDynamic Programming Game TheoryUnilateral improvementsMathematical economicsGame theoryConsensus Protocols; Dynamic Programming Game Theory; Inventory
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LPV model identification for gain scheduling control: An application to rotating stall and surge control problem

2006

Abstract We approach the problem of identifying a nonlinear plant by parameterizing its dynamics as a linear parameter varying (LPV) model. The system under consideration is the Moore–Greitzer model which captures surge and stall phenomena in compressors. The control task is formulated as a problem of output regulation at various set points (stable and unstable) of the system under inputs and states constraints. We assume that inputs, outputs and scheduling parameters are measurable. It is worth pointing out that the adopted technique allows for identification of an LPV model's coefficients without the requirements of slow variations amongst set points. An example of combined identification…

decentralized controlEngineeringbusiness.industryApplied MathematicsSystem identificationStall (fluid mechanics)Control engineeringconsensus protocolOptimal controlconsensus protocolsDecentralised systemComputer Science Applicationsoptimal controlNonlinear systemGain schedulingControl and Systems EngineeringControl theorynetworksSettore MAT/09 - Ricerca OperativaElectrical and Electronic EngineeringSurgebusinessSurge controlconsensus protocols; decentralized control; optimal control; networksControl Engineering Practice
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Decentralized classification in societies of autonomous and heterogenous robots

2011

This paper addresses the classification problem for a set of autonomous robots that interact with each other. The objective is to classify agents that “behave” in “different way”, due to their own physical dynamics or to the interaction protocol they are obeying to, as belonging to different “species”. This paper describes a technique that allows a decentralized classification system to be built in a systematic way, once the hybrid models describing the behavior of the different species are given. This technique is based on a decentralized identification mechanism, by which every agent classifies its neighbors using only local information. By endowing every agent with such a local classifie…

distributed algorithm0106 biological sciencesSpecies classification0209 industrial biotechnologyEngineeringbusiness.industrymulti-robot systemInteraction protocolRoboticsMobile robot02 engineering and technologyAutonomous robotconsensus protocols010603 evolutionary biology01 natural sciencesComputer Science::Multiagent SystemsIdentification (information)020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaRobotArtificial intelligenceSet (psychology)businessClassifier (UML)2011 IEEE International Conference on Robotics and Automation
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