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Paper   IPM / Cognitive / 8800
School of Cognitive Sciences
  Title:   A biologically inspired method for conceptual imitation using reinforcement learning
  Author(s): 
1.  Hossein Mobahi
2.  Majid Ahmadabadi
3.  Babak Araabi
  Status:   Published
  Journal: Applied Artificial Intelligence
  Vol.:  21
  Year:  2007
  Pages:   155 - 183
  Supported by:  IPM
  Abstract:
Learning by imitation can provide agents with a natural and effective means for transferring knowledge when brain-to-brain connection is infeasible. Natural mechanisms for imitation demonstrate strong abstraction and conceptualization capabilities, however, computational models that have been proposed for imitative learning barely address these fundamental features Inspired by functions of human brain constituents and exploiting ideas enthused by mirror neurons and the multi-store model of memory, we propose a new model for learning by imitation capable of developing relational concepts. In our model, memory gradually organizes sensory data into concepts through reinforcement learning and consolidation, while mirror neurons maintain an extendible repertoire of familiar actions connected to corresponding concepts. We also discuss the relation between modeling behavior of concept-oriented agents in terms of mathematical functions and relevant biological evidence of mirror neurons. Eventually, we evaluate our method in a phoneme acquisition experiment through real interaction with humans.

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