6533b86efe1ef96bd12cb616

RESEARCH PRODUCT

Consensus in Noncooperative Dynamic Games: a Multi-Retailer Inventory Application

Raffaele PesentiDario BausoLaura Giarre

subject

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game TheoryCorrelated equilibriumSequential gameComputer scienceDynamic programmingSubgame perfect equilibriumsymbols.namesakeCoordination gameElectrical and Electronic EngineeringRisk dominanceFolk theoremPrice of stabilityNon-credible threatGame theoryCentipede gameImplementation theoryNon-cooperative gameInventoryNormal-form gameStochastic gameComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALComputer Science ApplicationsConsensus protocols; Dynamic programming; Game theory; InventoryConsensus protocolsZero-sum gameControl and Systems EngineeringNash equilibriumEquilibrium selectionBest responsesymbolsRepeated gameEpsilon-equilibriumConsensus protocols; Dynamic programming; Game theory; Inventory;Potential gameSolution conceptMathematical economicsGame theory

description

We focus on Nash equilibria and Pareto optimal Nash equilibria for a finite horizon noncooperative dynamic game with a special structure of the stage cost. We study the existence of these solutions by proving that the game is a potential game. For the single-stage version of the game, we characterize the aforementioned solutions 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 multistage version of the game, we present an algorithm that converges to Nash equilibria, unfortunately, not necessarily Pareto optimal. The algorithm returns a sequence of joint decisions, each one obtained from the previous one by an unilateral improvement on the part of a single player. We also specialize the game to a multiretailer inventory system.

10.1109/tac.2008.919546https://hdl.handle.net/11380/1123512