想研究格斗游戏AI？这个新基准FootsiesGym基于极简游戏Footsies，自带高效模拟器，适合强化学习训练和对比。
FootsiesGym 是基于 HiFight 的极简 2D 格斗游戏 Footsies 构建的开源环境，用于研究双人零和不完美信息游戏中的循环非传递策略互动。该环境提供向量化模拟器，可在标准硬件上实现高吞吐量训练。论文对多种强化学习算法进行了基准测试，并讨论了开放研究方向。代码已开源在 GitHub。
FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games
We present FootsiesGym, an open-source environment for learning in a non-trivial two-player, zero-sum, imperfect-information game. Built on HiFight's minimalist 2D fighting game Footsies, it isolates the cyclic, non-transitive strategic interactions of fighting game neutral play while remaining simple enough for efficient analysis. We provide a vectorized simulator that enables high-throughput training on standard hardware, making the environment accessible and reproducible. We describe the design of the environment, benchmark several reinforcement learning algorithms, and discuss open research directions it enables. The code is available at https://github.com/como-research/FootsiesGym.