R2D-RL: A RoboCup 2D Soccer Environment for Multi-Agent Reinforcement Learning

Haobin Qin, Baofeng Zhang, Hidehisa Akiyama +1

Robot soccer is a challenging testbed for multi-agent reinforcement learning because it combines partial observability, cooperative and adversarial interaction, sparse rewards, and…