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Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion
March 20, 2024, 4:42 a.m. | Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng
cs.LG updates on arXiv.org arxiv.org
Abstract: In the dynamic and rapid tactic involvements of turn-based sports, badminton stands out as an intrinsic paradigm that requires alter-dependent decision-making of players. While the advancement of learning from offline expert data in sequential decision-making has been witnessed in various domains, how to rally-wise imitate the behaviors of human players from offline badminton matches has remained underexplored. Replicating opponents' behavior benefits players by allowing them to undergo strategic development with direction before matches. However, directly …
abstract advancement arxiv behavior cs.ai cs.lg data decision domains dynamic expert intrinsic making offline paradigm sports type via
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