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000928580 019__ $$a1137817388$$a1139947986$$a1142709019
000928580 020__ $$a9783030357207$$q(electronic book)
000928580 020__ $$a3030357201$$q(electronic book)
000928580 020__ $$z3030357198
000928580 020__ $$z9783030357191
000928580 0247_ $$a10.1007/978-3-030-35
000928580 0247_ $$a10.1007/978-3-030-35720-7$$2doi
000928580 035__ $$aSP(OCoLC)on1139271597
000928580 035__ $$aSP(OCoLC)1139271597$$z(OCoLC)1137817388$$z(OCoLC)1139947986$$z(OCoLC)1142709019
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000928580 049__ $$aISEA
000928580 050_4 $$aQA274.7
000928580 08204 $$a519.2/33$$223
000928580 1001_ $$aMinjárez-Sosa, J. Adolfo.
000928580 24510 $$aZero-sum discrete-time Markov games with unknown disturbance distribution :$$bdiscounted and average criteria /$$cJ. Adolfo Minjárez-Sosa.
000928580 260__ $$aCham :$$bSpringer,$$c2020.
000928580 300__ $$a1 online resource
000928580 336__ $$atext$$btxt$$2rdacontent
000928580 337__ $$acomputer$$bc$$2rdamedia
000928580 338__ $$aonline resource$$bcr$$2rdacarrier
000928580 347__ $$atext file$$bPDF$$2rda
000928580 4901_ $$aSpringerBriefs in probability and mathematical statistics
000928580 504__ $$aIncludes bibliographical references and index.
000928580 5050_ $$aZero-sum Markov games -- Discounted optimality criterion -- Average payoff criterion -- Empirical approximation-estimation algorithms in Markov games -- Difference-equation games: examples -- Elements from analysis -- Probability measures and weak convergence -- Stochastic kernels -- Review on density estimation.
000928580 506__ $$aAccess limited to authorized users.
000928580 520__ $$aThis SpringerBrief deals with a class of discrete-time zero-sum Markov games with Borel state and action spaces, and possibly unbounded payoffs, under discounted and average criteria, whose state process evolves according to a stochastic difference equation. The corresponding disturbance process is an observable sequence of independent and identically distributed random variables with unknown distribution for both players. Unlike the standard case, the game is played over an infinite horizon evolving as follows. At each stage, once the players have observed the state of the game, and before choosing the actions, players 1 and 2 implement a statistical estimation process to obtain estimates of the unknown distribution. Then, independently, the players adapt their decisions to such estimators to select their actions and construct their strategies. This book presents a systematic analysis on recent developments in this kind of games. Specifically, the theoretical foundations on the procedures combining statistical estimation and control techniques for the construction of strategies of the players are introduced, with illustrative examples. In this sense, the book is an essential reference for theoretical and applied researchers in the fields of stochastic control and game theory, and their applications.
000928580 650_0 $$aMarkov processes.
000928580 650_0 $$aDifferential games.
000928580 77608 $$iPrint version: $$z3030357198$$z9783030357191$$w(OCoLC)1125354855
000928580 830_0 $$aSpringerBriefs in probability and mathematical statistics.
000928580 852__ $$bebk
000928580 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-35720-7$$zOnline Access$$91397441.1
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000928580 980__ $$aEBOOK
000928580 980__ $$aBIB
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000928580 983__ $$aOnline
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