Allocation Game

Allocation games model the strategic distribution of limited resources among competing agents, aiming to understand equilibrium outcomes and optimize overall system performance. Current research focuses on developing algorithms for learning equilibria in settings with imperfect information and designing mechanisms to achieve desirable outcomes, such as fairness or efficiency, even with selfish agents, often employing techniques from game theory, online learning, and multi-agent systems. These studies have implications for diverse applications including resource management, task allocation in crowdsourcing, and the design of cooperative multi-agent systems, particularly in contexts involving human-machine interaction. The development of generalized performance evaluation metrics and the exploration of different agent behaviors (e.g., contention-aversion, homophily) are also significant trends.