Fuzzy inference model for learning based on experiences ○ 郷古学 菅谷至寛 阿曽弘具 ○
نویسندگان
چکیده
Fuzzy inference models can conduct advanced inference using knowledge which is easily understood by humans. In this paper, we propose a fuzzy inference model for learning based on experiences. The proposed model executes learning with input/output (I/O) data of the model and their evaluations obtained by trial-and-error of a task. Such a learning is executed after each end of a trial. Hence, it is expected that the achievement rate increases with repetition of trials, and that the model adapts to change of environment. We confirm performance of the model using a mobile robot navigation task simulation. It confirmed that the model acqires the knowledge that was effective in the task achievement.
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تاریخ انتشار 2005