This environment offers researchers a reproducible, computationally efficient testbed for developing and evaluating RL algorithms in strategic games with hidden information and cyclic non-transitive dynamics—properties common in real-world competitive scenarios.
FootsiesGym is an open-source environment for training AI agents in a simplified 2D fighting game with imperfect information and strategic complexity. It provides a fast, accessible benchmark for studying two-player competitive interactions where neither player has complete information, enabling efficient reinforcement learning research on standard hardware.