CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Modeling parietal-premotor interactions in primate control of grasping
Neural Networks - Special issue on neural control and robotics: biology and technology
Biologically Inspired Framework for Learning and Abstract Representation of Attention Control
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint
IEEE Transactions on Evolutionary Computation
Conceptual Imitation Learning in a Human-Robot Interaction Paradigm
ACM Transactions on Intelligent Systems and Technology (TIST)
METAL: A framework for mixture-of-experts task and attention learning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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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.