IMITATION LEARNING AND ANCHORING THROUGH CONCEPTUAL SPACES |
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Authors: | Antonio Chella Haris Dindo Ignazio Infantino |
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Affiliation: | 1. Dip. di Ingengeria Informatica , Università degli Studi di Palermo , Palermo, Italy chella@unipa.it;3. Dip. di Ingengeria Informatica , Università degli Studi di Palermo , Palermo, Italy;4. Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche , Palermo, Italy |
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Abstract: | In order to have a robotic system able to effectively learn by imitation and not merely reproduce the movements of a human teacher, the system should have the capability to deeply understand the perceived actions to be imitated. This paper deals with the development of a cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how the same conceptual representation can be used both in a bottom-up approach, in order to learn sequences of actions by imitation learning paradigm, and in a top-down approach, in order to anchor the symbolical representations to the perceptual activities of the robotic system. Experiments concerned with the problem of teaching a humanoid robotic system simple manipulative tasks are reported. |
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