“AlphaGo”杀进足球场！自我对弈140年，机器人成“梅西终结者”

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.