A Study of Multiagent Reinforcement Learning based on Quantum Theory
Meng Xiangping, Yuzhen Pi, Yuan Quande, Pan Ying · 2006
In this paper, we present a novel multiagent reinforcement learning algorithm based on Q-learning and quantum theory. As in reinforcement learning algorithm, when the number of agents or/and agent's action is large enough, all of the action selection methods will be failed: the speed of learning is decreased sharply, we try to combine the quantum theory with Q-learning, hoping that the problem will be resolved with our proposed.