Greedy Action Selection and Pessimistic Q-Value Updating in Multi-Agent Reinforcement Learning with Sparse Interaction
Although multi-agent reinforcement learning (MARL) is a promising method for learning a collaborative action policy, enabling each agent to accomplish specified tasks, MARL has a problem of exponentially increasing state-action space.This state-action space can be dramatically reduced by assuming sparse interaction.We previously proposed three meth