Optimal Containment of Multiagent Systems With Multistep Policy Gradient Reinforcement Learning.
This article analyzes the optimal containment control problem of discrete-time multiagent systems (MASs) and proposes an online off-policy multistep PG algorithm that achieves optimal control performance under completely unknown system dynamics and accommodates asynchronous policy updates among agents.