Automatic Learning for Acquisition of Tetris's Skills using Fuzzy Inference Neural Networks

Abstract

In this paper, we propose a method to learn skills automatically by using operation data which human carried out. Tetris is used as an example to study skills. The acquisition and improvement of skills are essential for learning in humans. As for machine learning, the research on examining learning process of human by computer simulations has been carried out. Our objective is to examine acquisition and improvement of skills for Tetris by using Fuzzy Inference Neural Networks(FINNs). FINNs can express the acquired knowledge of the neural network with if-then rules. The rules can be generated automatically by giving the operation data to the proposed system. The skills can be improved by using more operation data. We can analyze acquired skills by examining the rules generated from FINNs. We confirmed the improvement of skills by using more operation data. We could express skills explicitly by the rules that FINNs generated. Also we examined the difference of skills between a veteran and a beginner, and it is suggested that a veteran was doing Tetris considering further steps.