佯攻行为与策略：形式化、实现与评估
Feint Behaviors and Strategies: Formalization, Implementation and Evaluation
AI总结：
本文首次从动作与策略层面形式化佯攻行为，提出回文导向模板、双行为模型及 MARL 统一实现方案，实验证明其可提升奖励与多样性且开销极低。
摘要：
佯攻行为指的是一组以微妙方式呈现的欺骗性行为，使玩家能够在竞技游戏中获得相对于对手的时间和空间优势。此类行为是大多数竞技多人游戏（如拳击、击剑、篮球、赛车等）中的关键战术。然而，现有文献并未对佯攻行为及其对游戏策略的影响提供全面（和/或具体）的形式化。在本工作中，我们首次在动作层面和策略层面对佯攻行为进行了全面形式化，并在多人游戏中对其进行具体实现和定量评估。我们工作的核心思想是：（1）通过 Palindrome-directed templates（回文导向模板）自动生成佯攻行为，并通过 Dual-Behavior Model（双行为模型）将其组合成有意义的行为序列；（2）分别从时间、空间及其集体影响方面，将我们对佯攻的形式化在游戏策略上的含义具体化；（3）在现有 MARL 框架中提供统一的佯攻行为实现方案。实验结果表明，我们设计的佯攻行为能够：（1）大幅提升游戏奖励收益；（2）显著提高多人游戏的多样性；（3）在时间消耗方面仅产生可忽略不计的开销。
英文摘要：
Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games. Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.). However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors, and their implications on game strategies. In this work, we introduce the first comprehensive formalization of Feint behaviors at both action-level and strategy-level, and provide concrete implementation and quantitative evaluation of them in multi-player games. The key idea of our work is to (1) allow automatic generation of Feint behaviors via Palindrome-directed templates, combine them into meaningful behavior sequences via a Dual-Behavior Model; (2) concertize the implications from our formalization of Feint on game strategies, in terms of temporal, spatial and their collective impacts respectively; and (3) provide a unified implementation scheme of Feint behaviors in existing MARL frameworks. The experimental results show that our design of Feint behaviors can (1) greatly improve the game reward gains; (2) significantly improve the diversity of Multi-Player Games; and (3) only incur negligible overheads in terms of time consumption.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
