Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...

Abstract: Motivated by multi-agent Q-learning scenarios, this paper introduces a distributed action selection algorithm that relies on individual agents interacting with local neighbors to learn a ...