Coalition Game

Coalition game theory studies how rational agents form groups (coalitions) to maximize their collective benefit, focusing on optimal coalition structure generation and fair payoff distribution. Current research emphasizes efficient algorithms for finding optimal coalitions, particularly in large-scale systems like federated learning and multi-robot collectives, often employing techniques like dynamic programming, Shapley values, and game-theoretic frameworks (e.g., Stackelberg and hedonic games). These advancements have significant implications for resource allocation in distributed systems, collaborative task completion in robotics, and the design of incentive mechanisms in decentralized machine learning.