—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. E ective agent interactions in such domains raise some of most fundamental research...
This paper deals with a cooperative control method for a multi-agent system in dynamic environment. This method enables a robot to perform flexible cooperation based on the global ...