AI RESEARCH
ShuttleEnv: An Interactive Data-Driven RL Environment for Badminton Strategy Modeling
arXiv CS.LG
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ArXi:2603.17324v1 Announce Type: cross We present ShuttleEn, an interactive and data-driven simulation environment for badminton, designed to reinforcement learning and strategic behavior analysis in fast-paced adversarial sports. The environment is grounded in elite-player match data and employs explicit probabilistic models to simulate rally-level dynamics, enabling realistic and interpretable agent-opponent interactions without relying on physics-based simulation.