Presentation 2003/10/17
Imitation Learning by Estimating Intention of Demonstrator
Norikazu SUGIMOTO, Kenji DOYA, Mitsuo KAWATO,
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Abstract(in English) In imitation learning, it is critical that the imitator estimate not only the trajectory of the demonstrator but also its itentions. This is particularly true when the physical parameters between them are different. In this paper we propose a new approach for imitation learning. The imitator first estimate the subgoal of the demonstrator from its trajectory, and choose it to become its own subgoal. This way, the imitator evaluates its own behaviour rather than simply copying the output of the demonstrator, and can account for differences in dynamics in a natural way.
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Keyword(in English) Continuous / Hierarchical / Module reinfocement learning / Non-linear control
Paper # PRMU2003-138,NC2003-69
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Committee NC
Conference Date 2003/10/17(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Imitation Learning by Estimating Intention of Demonstrator
Sub Title (in English)
Keyword(1) Continuous
Keyword(2) Hierarchical
Keyword(3) Module reinfocement learning
Keyword(4) Non-linear control
1st Author's Name Norikazu SUGIMOTO
1st Author's Affiliation NAra Institute of Science and Technology:ATR, Computational Neuroscience Laboratories:Creating the Brain, CREST, Japan Science and Technology Corporation()
2nd Author's Name Kenji DOYA
2nd Author's Affiliation NAra Institute of Science and Technology:ATR, Computational Neuroscience Laboratories:Creating the Brain, CREST, Japan Science and Technology Corporation
3rd Author's Name Mitsuo KAWATO
3rd Author's Affiliation NAra Institute of Science and Technology:ATR, Computational Neuroscience Laboratories
Date 2003/10/17
Paper # PRMU2003-138,NC2003-69
Volume (vol) vol.103
Number (no) 392
Page pp.pp.-
#Pages 6
Date of Issue