MyoChallenge 2025: Towards Human Athletic Intelligence

Athletic performance represents the pinnacle of human decision-making. It demands rapid choices, precise motor control, agility, and coordinated physical execution. Such a combination of capabilities remains elusive in current artificial intelligence and robotic systems.Building on the momentum of the MyoChallenge at NeurIPS 2022, 2023, and 2024, the 4th edition of our MyoChallenge series -- Towards Human Athletic Intelligence-- moves toward capturing the full expressivity and agility of human athletic performance. Participants will develop behaviors for physiologically realistic musculoskeletal models performing fast-paced, and high-skill athletic tasks.The challenge will feature two tracks. First, a Soccer shootout. A full-body musculoskeletal model must dynamically approach and shoot a ball past a moving goalkeeper. Success requires balance, foot targeting, force generation, and rapid whole-body coordination. Second, a Table Tennis competition. A musculoskeletal model of the upper body (arm and trunk) must track, strike, and return balls in a fast-paced table tennis rally against an AI opponent. These challenges go far beyond static or repetitive motions. They demand generalization via reactive and adaptive embodied behavior grounded in the physics of muscle, tendon, and joint dynamics, with real-time perception-action loops capable of agile motor control. The challenge will be staged in the commonly used MyoSuite framework, which offers physiologically accurate, state-of-the-art musculoskeletal models, an intuitive interface to scalable reinforcement learning and control libraries. The framework also enables easy onboarding via extensive tutorials and getting-started materials, and access to multiple baseline libraries needed for the challenge.The competition aims to engage diverse research communities: biomechanics, motor neuroscience, reinforcement learning, control theory, and more. As in previous years, it will prioritize scalability, reproducibility, and generalization, and be open-sourced following best engineering and academic practices to advance physiological control and bring us closer to replicating human athletic intelligence.