A Quantum Reinforcement Learning Method for Repeated Game Theory
Chunlin Chen, Daoyi Dong, Yu Dong, Qiong Shi · 2006
In this paper, a quantum reinforcement learning method is proposed for repeated game theory. First, the quantum reinforcement learning algorithm is introduced based on quantum state superposition principle and its superiority is analyzed. Then, it is applied to repeated games and the experiments show its effectiveness. Related issues are also discussed before the conclusion is given