Learning Agent

Learning agents are artificial intelligence systems that learn to make decisions and achieve goals through interaction with their environment, often employing reinforcement learning techniques. Current research emphasizes improving agent performance through methods like policy space response oracles (PSRO) for multi-agent systems, maximally permissive reward machines for efficient learning, and adaptive incentive designs to guide behavior towards socially optimal outcomes. This field is crucial for advancing AI safety, improving decision-making in complex systems (e.g., economics, healthcare), and developing more interpretable and verifiable AI agents for real-world applications.