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Evolutionary Intelligence
Erschienen in: Evolutionary Intelligence 2/2014

01.08.2014 | Special Issue

Simultaneous versus incremental learning of multiple skills by modular robots

verfasst von: C. Rossi, A. E. Eiben

Erschienen in: Evolutionary Intelligence | Ausgabe 2/2014

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Abstract

This paper is concerned with the problem of learning multiple skills by modular robots. The main question we address is whether it is better to learn multiple skills simultaneously (all-at-once) or incrementally (one-by-one). We conduct an experimental study with modular robots of various morphologies that need to acquire three different but correlated skills, efficient locomotion, navigation towards a target point, and obstacle avoidance, using a real-time, on-board evolution as the learning method. The results indicate that the one-by-one strategy is more efficient and more stable than the all-at-once strategy.
Vorheriger Artikel An evolutionary robotics approach for the distributed control of satellite formations

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Fußnoten
1
Webots system by Cyberbotics, www.​cyberbotics.​com.
 
2
Early work on such learning strategy for the problem at hand has shown that an individual mutation rate for each gene does not provide an advantage, w.r.t having a common mutation rate for all genes, see [28].
 
3
Recall that the Infancy stage is part of a cycle—the Triangle of Life—where individuals mate sto generate new offspring.
 
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Metadaten
Titel
Simultaneous versus incremental learning of multiple skills by modular robots
verfasst von
C. Rossi
A. E. Eiben
Publikationsdatum
01.08.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Evolutionary Intelligence / Ausgabe 2/2014
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI
https://doi.org/10.1007/s12065-014-0109-3

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