文章基本信息

标题：A DYNAMIC PROGRAMMING ALGORITHM FOR OPTIMIZING BASEBALL STRATEGIES
本地全文：下载
作者：Akifumi Kira ; Keisuke Inakawa ; Toshiharu Fujita 等
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