Multi Agent Simulation

Multi-agent simulation (MAS) models complex systems by simulating the interactions of numerous autonomous agents, aiming to understand emergent behavior and system-level properties. Current research emphasizes scalability, particularly leveraging advancements in large language models and distributed computing architectures to handle increasingly large numbers of agents with diverse capabilities and limited information. Applications span diverse fields, including finance (modeling opaque markets), autonomous driving (validating safety and interaction strategies), and social sciences (investigating the impact of values and norms on collective behavior). These simulations provide valuable insights for designing robust and efficient systems and for testing hypotheses in scenarios difficult or impossible to replicate in the real world.