Modeling Intrinsic Motivation with ACT-R

Abstract

A development of autonomous agents requires not only learning by external rewards but also a mechanism for generating spontaneous rewards from the inside. Specifically, reinforcement learning methods using intrinsic motivation have been studied. In this study, we propose a method to express it by ACT-R, a general-purpose cognitive architecture. The proposed method focuses on a compilation of pattern matching in ACT-R and regards pattern discovery as a source of intrinsic motivation.