Self-play is a training technique used primarily in artificial intelligence and machine learning, particularly in the development of algorithms for games and strategic decision-making. In self-play, an AI system plays against itself instead of competing against human opponents or other external agents. This approach allows the AI to explore a wide range of strategies and scenarios without the need for external data.
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