书目名称 | Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution |
副标题 | Discounted and Avera |
编辑 | J. Adolfo Minjárez-Sosa |
视频video | |
概述 | First book providing a study on discrete-time Markov games with unknown disturbance distribution.Presents a systematic analysis on recent developments of estimation and control procedures in Markov ga |
丛书名称 | SpringerBriefs in Probability and Mathematical Statistics |
描述 | This 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 refer |
出版日期 | Book 2020 |
关键词 | zero-sum Markov games; Markov games; difference-equation games; probability measures and weak convergen |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-030-35720-7 |
isbn_softcover | 978-3-030-35719-1 |
isbn_ebook | 978-3-030-35720-7Series ISSN 2365-4333 Series E-ISSN 2365-4341 |
issn_series | 2365-4333 |
copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 |