Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/101796
Title: Approximate public-signal correlated equilibria for nonzero-sum differential games
Authors: Averboukh, Y.
Issue Date: 2019
Publisher: Society for Industrial and Applied Mathematics Publications
Citation: Averboukh Y. Approximate public-signal correlated equilibria for nonzero-sum differential games / Y. Averboukh. — DOI 10.1137/17M1161403 // SIAM Journal on Control and Optimization. — 2019. — Vol. 57. — Iss. 1. — P. 743-772.
Abstract: We construct an approximate public-signal correlated equilibrium for a nonzero-sum differential game in the class of stochastic strategies with memory. The construction is based on a solution of an auxiliary nonzero-sum continuous-time stochastic game. This class of games includes stochastic differential games and continuous-time Markov games. Moreover, we study the limit of approximate equilibrium outcomes in the case when the auxiliary stochastic games tend to the original deterministic one. We show that it lies in the convex hull of the set of equilibrium values provided by deterministic punishment strategies. © 2019 Society for Industrial and Applied Mathematics.
Keywords: APPROXIMATE EQUILIBRIUM
CONTROL WITH MODEL
NONZERO-SUM DIFFERENTIAL GAMES
PUBLIC-SIGNAL CORRELATED STRATEGIES
CONTINUOUS TIME SYSTEMS
GAME THEORY
APPROXIMATE EQUILIBRIUMS
CONTINUOUS-TIME
CORRELATED EQUILIBRIA
EQUILIBRIUM VALUE
NONZERO-SUM DIFFERENTIAL GAME
PUBLIC-SIGNAL CORRELATED STRATEGIES
STOCHASTIC DIFFERENTIAL GAME
STOCHASTIC GAME
STOCHASTIC SYSTEMS
URI: http://hdl.handle.net/10995/101796
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85062696663
PURE ID: 9169671
4ccc70a5-5ee8-4c08-9044-dd16fc530100
ISSN: 3630129
DOI: 10.1137/17M1161403
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

Files in This Item:
File Description SizeFormat 
2-s2.0-85062696663.pdf399,74 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.