身体性認知研究の強力な味方としてのロボット：ボトムアップアプローチ
Robots as Powerful Allies for the Study of Embodied Cognition from the Bottom Up
ロボットの身体構造や制御を自在に変えられる利点を活かし、歩行などの低次行動から感覚運動学習、人間的認知までを段階的に再現する発達的アプローチを提唱し、認知理解とロボットの自律性向上の相互利益を示した。
著者: Matej Hoffmann, Rolf Pfeifer
分類: cs.AI, cs.RO, q-bio.NC
原文アブストラクト
A large body of compelling evidence has been accumulated demonstrating that embodiment - the agent's physical setup, including its shape, materials, sensors and actuators - is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool of investigation. We present a robotic bottom-up or developmental approach, focusing on three stages: (a) low-level behaviors like walking and reflexes, (b) learning regularities in sensorimotor spaces, and (c) human-like cognition. We also show that robotic based research is not only a productive path to deepening our understanding of cognition, but that robots can strongly benefit from human-like cognition in order to become more autonomous, robust, resilient, and safe.
