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  • 标题:A DYNAMIC PROGRAMMING ALGORITHM FOR OPTIMIZING BASEBALL STRATEGIES
  • 本地全文:下载
  • 作者:Akifumi Kira ; Keisuke Inakawa ; Toshiharu Fujita
  • 期刊名称:日本オペレーションズ・リサーチ学会論文誌
  • 印刷版ISSN:0453-4514
  • 电子版ISSN:2188-8299
  • 出版年度:2019
  • 卷号:62
  • 期号:2
  • 页码:64-82
  • DOI:10.15807/jorsj.62.64
  • 出版社:Japan Science and Technology Information Aggregator, Electronic
  • 摘要:In this paper, baseball is formulated as a finite non-zero-sum Markov game with approximately 6.45 million states. We give an effective dynamic programming algorithm which computes equilibrium strategies and the equilibrium winning percentages for both teams in less than 2 second per game. Optimal decision making can be found depending on the situation—for example, for the batting team, whether batting for a hit, stealing a base or sacrifice bunting will maximize their win percentage, or for the fielding team, whether to pitch to or intentionally walk a batter, yields optimal results. Based on this model, we discuss whether the last-batting team has an advantage. In addition, we compute the optimal batting order, in consideration of the decision making in a game.
  • 关键词:Dynamic programming;OR in sports;Markov perfect equilibrium;advantage of the last-batting team;optimal lineup
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