Lesong Tao

POAQL: A Partially Observable Altruistic Q-Learning Method for Cooperative Multi-Agent Reinforcement Learning

Multi-Agent Path Finding (MAPF) is an important issue in multi-agent cooperation. Many studies apply MultiAgent Reinforcement Learning (MARL) to solve MAPF in partially observable settings. The objective of cooperative MARL is to maximize the cumulative team reward. Nevertheless, in partially observ…