ShuttleEnv: An Interactive Data-Driven RL Environment for Badminton Strategy Modeling

• URL: http://arxiv.org/abs/2603.17324v1
• Date: Wed, 18 Mar 2026 03:37:39 GMT
• Title: ShuttleEnv: An Interactive Data-Driven RL Environment for Badminton Strategy Modeling
• Abstract summary: We present ShuttleEnv, an interactive and data-driven simulation environment for badminton.<n>ShuttleEnv supports reinforcement learning and strategic behavior analysis in fast-paced adversarial sports.<n>We showcase multiple trained agents within ShuttleEnv and provide live, step-by-step visualization of badminton rallies.
• Score: 22.470701364501604
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present ShuttleEnv, an interactive and data-driven simulation environment for badminton, designed to support 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. In this demonstration, we showcase multiple trained agents within ShuttleEnv and provide live, step-by-step visualization of badminton rallies, allowing attendees to explore different play styles, observe emergent strategies, and interactively analyze decision-making behaviors. ShuttleEnv serves as a reusable platform for research, visualization, and demonstration of intelligent agents in sports AI. Our ShuttleEnv demo video URL: https://drive.google.com/file/d/1hTR4P16U27H2O0-w316bR73pxE2ucczX/view

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