Social Simulation

Social simulation uses computational models to study complex social phenomena, aiming to understand and predict human behavior in various contexts. Current research heavily utilizes large language models (LLMs) as agents within these simulations, focusing on improving agent realism through techniques like integrating symbolic reasoning, incorporating personality traits, and enriching agent profiles beyond demographics to include values and motivations. This approach offers valuable insights into social dynamics, informing fields like urban planning (e.g., autonomous vehicle integration), game theory, and the design of more human-centered AI systems.