Modifying the learning process of the Expert Iteration algorithm
Johan Sjöblom · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2019
This thesis sets out to improve the performance of the Expert Iteration (EXIT) algorithm a simulation-based learning process to train an AI. EXIT and four different modifications are implemented and evaluated through a tournament of the board game Hex. The results suggest that the training pipeline of EXIT could be significantly simplified without a loss of performance.