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FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games

2026-07-07 · arXiv: 2607.06514

One-line summary

An AI research paper on FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games.

Engineering notes

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Chinese explanation / 中文解读

中文解读待补充:本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

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.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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