Learning fuzzy inference model and investigation of acquired knowledge

Fuzzy inference models can conduct advanced inference using knowledge which is easily understood by humans. In this paper, we propose a leaning fuzzy inference model. The model can learn with experience data obtained by trial-and-error of a task. The learning of the model is executed after each trial of the task. Hence, it is expected that the achievement rate increases with repetition of the trials, and that the model adapts to change of environment. We confirm the performance of the model by experiences and the validity of learning by investigation of the knowledge acquired by the learning.