Self-Play Fuels AI Agent Evolution

The ArXiv article likely presents research on AI agents that improve their performance through self-play techniques. This approach allows agents to learn and adapt without external human supervision, potentially leading to more robust and capable AI systems.

• •Self-play is a training method where AI agents compete against copies of themselves.
• •This approach enables agents to discover optimal strategies without external guidance.
• •The research likely explores various self-play algorithms and their impact on agent performance.