“AlphaGo”杀进足球场!自我对弈140年,机器人成“梅西终结者”
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TL;DR - Skild AI demonstrated Messinator, a humanoid robot that learned soccer skills through reinforcement learning and 140 simulated years of self-play. The result suggests self-play can generate complex physical behaviors without engineers explicitly rewarding each skill.
- Messinator combines Skild’s S1/Skild Brain foundation model for body control with self-play for strategic improvement.
- Training in NVIDIA Isaac Sim used scoring goals as the primary objective; dribbling, shielding, tackling, shooting, and recovering from falls emerged without separate rewards.
- The robot trained against earlier versions of itself, creating progressively stronger opponents, then transferred its learned strategies to real-world human-robot play.
- The demonstration extends Skild’s broader cross-hardware approach, previously trained across roughly 100,000 simulated robot body configurations.
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“AlphaGo”杀进足球场!自我对弈140年,机器人成“梅西终结者”
Public signals
N/A
TL;DR - Skild AI demonstrated Messinator, a humanoid robot that learned soccer skills through reinforcement learning and 140 simulated years of self-play. The result suggests self-play can generate complex physical behaviors without engineers explicitly rewarding each skill.
- Messinator combines Skild’s S1/Skild Brain foundation model for body control with self-play for strategic improvement.
- Training in NVIDIA Isaac Sim used scoring goals as the primary objective; dribbling, shielding, tackling, shooting, and recovering from falls emerged without separate rewards.
- The robot trained against earlier versions of itself, creating progressively stronger opponents, then transferred its learned strategies to real-world human-robot play.
- The demonstration extends Skild’s broader cross-hardware approach, previously trained across roughly 100,000 simulated robot body configurations.