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 researc
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- LinkedLinked via arxiv author · 85%Chase McDonald →
“FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games”
- LinkedLinked via arxiv author · 85%Nathan Tsang →
“FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games”
- LinkedLinked via arxiv author · 85%Wesley N. Kerr →
“FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games”
- FuzzySimilar title/name (fuzzy) · 59%jeinlee1991/chinese-llm-benchmark →
“Fuzzy title match (0.73): “FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-S” ≈ “jeinlee1991/chinese-llm-benchmark””