Human breeders for evolving robots |
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Authors: | Orazio Miglino Onofrio Gigliotta Michela Ponticorvo Henrik H Lund |
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Affiliation: | (1) Department of Relational Sciences, University of Naples “Federico II”, Naples, 80133, Italy;(2) Institute of Cognitive Sciences and Technologies, National Research Council, Rome, 00185, Italy;(3) Department of Psychology, University of Palermo, Palermo, 90100, Italy;(4) The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, DK-5230, Denmark |
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Abstract: | In this article we describe a new approach in evolutionary robotics according to which human breeders are involved in the
evolutionary process. While traditionally robots are selected to reproduce automatically according to a fitness formula, which
is a quantitative and strictly defined measure, human breeders can operate selection based on qualitative criteria, and rewarding
behaviors that can slip between the meshes woven by the fitness formula. In authors’ opinion this may bring advantages to
the evolutionary robotics methodology, allowing the production of robots that display more, and more multiform, behaviors.
In order to illustrate this approach, the software Breedbot was developed in which human breeders can intervene in evolving
robots, complementing the automatic evaluation. After describing the software, some results on sample evolutionary processes
are reported showing that the joint use of human and artificial selection on an exploration task generates robots with a higher
performance and in a shorter time compared with the exclusive action of each breeding method. Future work will explore this
hypothesis further.
This work was presented in part at the First European Workshop on Artificial Life and Robotics, Vienna, Austria, July 12–13,
2007 |
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Keywords: | User-guided evolutionary robotics Human-robot interaction Fitness function |
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