Agent Alignment

Agent alignment focuses on ensuring that artificial intelligence systems, particularly those exhibiting advanced capabilities like large language models and deep reinforcement learning agents, behave in ways consistent with human values and intentions. Current research emphasizes developing methods to evaluate and improve alignment, exploring techniques like reward shaping, power regularization in multi-agent systems, and interpretable frameworks for analyzing agent behavior across diverse tasks. This field is crucial for building trustworthy and beneficial AI systems, impacting both the safety and ethical considerations of AI deployment and the development of more robust and human-centered AI applications.