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Priming as a Means to Reduce Ambiguity in Learning from Demonstration

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Abstract

Learning from Demonstration is an established robot learning technique by which a robot acquires a skill by observing a human or robot teacher demonstrating the skill. In this paper we address the ambiguity involved in inferring the intention with one or several demonstrations. We suggest a method based on priming, and a memory model with similarities to human learning. Conducted experiments show that the developed method leads to faster and improved understanding of the intention with a demonstration by reducing ambiguity.

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Acknowledgments

This work was financed by the EU funded Initial Training Network (ITN) in the Marie-Curie People Programme (FP7): INTRO (INTeractive RObotics research network), Grant agreement no. 238486.

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Authors and Affiliations

  1. Department of Computing Science, Umeå University, 901 87, Umeå, Sweden

    Benjamin Fonooni, Thomas Hellström & Lars-Erik Janlert

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  1. Benjamin Fonooni
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  2. Thomas Hellström
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  3. Lars-Erik Janlert
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Correspondence to Benjamin Fonooni.

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Fonooni, B., Hellström, T. & Janlert, LE. Priming as a Means to Reduce Ambiguity in Learning from Demonstration. Int J of Soc Robotics 8, 5–19 (2016). https://doi.org/10.1007/s12369-015-0292-0

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