Temporal Difference Learning in Chinese Chess

  title={Temporal Difference Learning in Chinese Chess},
  author={Thong B. Trinh and Anwer S. Bashi and Nikhil Deshpande},
Reinforcement learning, in general, has not been totally successful at solving complex realworld problems which can be described by nonlinear functions. However, temporal difference learning is a type of reinforcement learning algorithm that has been researched and applied to various prediction problems with promising results. This paper discusses the application of temporal-difference learning in the training of a neural network to play a scaled-down version of the board game Chinese Chess… CONTINUE READING