Automatic game AI design by the use of UCT for Dead-End

Video game AI aims at generating an intelligent game opponent which is to compete with player, so game AI design plays an important role in the development of game. Nowadays, most of the game AI is implemented by FSM. But this mechanism has some drawbacks, so we need a mechanism to design game AI automatically instead of FSM. The process of automatic game AI design by UCT is introduced in this paper. In this process, we only take the meta-rules into consideration, while those many complicated detail knowledge is acquired by simulation. Here we propose the approach of UCT-controlled NPC based on CI (computational intelligence). However, this approach will consume lots of computational resources, and the acquired knowledge cannot be stored. To solve this problem, we train Artificial Neural Network (ANN) to make it reusable. The whole design process is validated on the Test-Bed of the game Dead-End. We conclude that from both the simplification of implementation and the reusability, this process outperforms FSM.