Strategic Interaction

Strategic interaction research explores how rational agents make decisions when outcomes depend on the actions of others, aiming to understand and predict behavior in diverse settings. Current work focuses on modeling these interactions using game theory, often incorporating large language models (LLMs) to simulate human-like strategic behavior and employing reinforcement learning to optimize agent performance in complex scenarios. This research is significant for advancing our understanding of decision-making in multi-agent systems, with implications for designing more effective AI agents and informing policy in areas like online markets and transportation.