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Embodied Symbol Emergence Based on Mimesis Theory

Department of Mechano-Informatics Graduate School of Information Science and Technology University of Tokyo, Japan

Iwaki Toshima

Department of Mechano-Informatics Graduate School of Information Science and Technology University of Tokyo, Japan

Hiroaki Tanie

Department of Mechano-Informatics Graduate School of Information Science and Technology University of Tokyo, Japan

Yoshihiko Nakamura

Department of Mechano-Informatics Graduate School of Information Science and Technology University of Tokyo, Japan and CREST program Japan Science and Technology Agency Japan

"Mimesis" theory focused in the cognitive science field and "mirror neurons" found in the biology field show that the behavior generation process is not independent of the behavior cognition process. The generation and cognition processes have a close relationship with each other. During the behavioral imitation period, a human being does not practice simple joint coordinate transformation, but will acknowledge the parents’ behavior. It understands the behavior after abstraction as symbols, and will generate its self-behavior. Focusing on these facts, we propose a new method which carries out the behavior cognition and behavior generation processes at the same time. We also propose a mathematical model based on hidden Markov models in order to integrate four abilities: (1) symbol emergence; (2) behavior recognition; (3) self-behavior generation; (4) acquiring the motion primitives. Finally, the feasibility of this method is shown through several experiments on a humanoid robot.

Key Words: imitation learning • symbol emergence • hidden Markov models • dynamics abstraction • mirror neurons

The International Journal of Robotics Research, Vol. 23, No. 4-5, 363-377 (2004)
DOI: 10.1177/0278364904042199


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