環境との相互作用を用いた自律移動ロボットの識別能力の実現

抄録

Conventional artificial intelligence and cognitive science approaches have been arguing the emergence of intelligence by completely separating the cognitive agent from its environment. In this paper, we intensively investigate and analyze the role of the system-environment interaction through the comparison between the information processing and embodied cognitive approaches. By taking account of this interaction, we experimentally show some of the hard classification problems suffering from the large input space and the ambiguities due to the perceptual aliasing problem can be greatly alleviated. To demonstrate this concept, we apply to a garbage-collecting task as a practical example.