Population Game

Population games model strategic interactions within large groups of agents, aiming to understand how individual choices and learning processes lead to emergent collective behaviors and equilibria. Current research focuses on analyzing the impact of altruism, imperfect information (e.g., payoff estimation errors), and heterogeneous agent interactions (including cooperative-competitive scenarios) on equilibrium outcomes, often employing mean-field game theory, reinforcement learning (particularly deep RL), and evolutionary game theory frameworks. These studies are significant for advancing our understanding of complex systems in various domains, from resource allocation and task assignment to federated learning and multi-agent robotics, by providing analytical tools and algorithms for predicting and influencing collective behavior.