RI: Small: Cooperative Coevolutionary Design and Multiagent Systems

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Cooperative coevolution is a potent approach to doing large-scale stochastic optimization. The unsolved game-theoretic challenges inherent in this computational method are complex and of significant interest to the evolutionary computation community. This project is advancing the state of the art in coevolution and is applying it to significantly larger problems than commonly found in the literature. These challenges, and their solution, have potentially transformative impact on other co-adaptive environments such as multiagent reinforcement learning, estimation of distribution algorithms, agent modeling, and swarm robotics. Coevolution has strong applicability to fields that use multiagent system models, including multirobotics, biology, economics, land use, and political science. Better models in these fields can positively affect society, policy, homeland security, and the environment.