Liqiang Tian

MARRGM: Learning Framework for Multi-Agent Reinforcement Learning via Reinforcement Recommendation and Group Modification

Sample usage efficiency is an important factor affecting the convergence speed of multi-agent deep reinforcement learning (MADRL) algorithms. Most existing experience replay (ER) methods manually select experience samples to update the agent's policy. It is difficult to give suitable and efficient e