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Detached tool use in evolutionary robotics: Evolving tool use skills
University of Skövde, School of Humanities and Informatics.
2006 (English)Independent thesis Advanced level (degree of Master (One Year)), 25 credits / 37,5 HE creditsStudent thesis
Abstract [en]

This master thesis investigates the principal capability of artificial evolution to produce tool use behavior in adaptive agents, excluding the application of life-time learning or adaptation mechanisms. Tool use is one aspect of complex behavior that is expected from autonomous agents acting in real-world environments. In order to achieve tool use behavior an agent needs to identify environmental objects as potential tools before it can use the tools in a problem-solving task. Up to now research in robotics has focused on life-time learning mechanisms in order to achieve this. However, these techniques impose great demands on resources, e.g. in terms of memory or computational power. All of them have shown limited results with respect to a general adaptivity. One might argue that even nature does not present any kind of omni-adaptive agent. While humans seem to be a good example of natural agents that master an impressive variety of life conditions and environments (at least from a human perspective, other examples are spectacular survivability observations of octopuses, scorpions or various viruses) even the most advanced engineering approaches can hardly compete with the simplest life-forms in terms of adaptation. This thesis tries to contribute to engineering approaches by promoting the application of artificial evolution as a complementing element with the presentation of successful pioneering experiments. The results of these experiments show that artificial evolution is indeed capable to render tool use behavior at different levels of complexity and shows that the application of artificial evolution might be a good complement to life-time approaches in order to create agents that are able to implicitly extract concepts and display tool use behavior. The author believes that off-loading at least parts of the concept retrieval process to artificial evolution will reduce resource efforts at life-time when creating autonomous agents with complex behavior such as tool use. This might be a first step towards the vision of a higher level of autonomy and adaptability. Moreover, it shows the demand for an experimental verification of commonly accepted limits between qualities of learned and evolved tool use capabilities.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2006. , 39 p.
Keyword [en]
adaptive robotics, evolutionary robotics, tool use behavior, autonomous agents, simulated experiments, artificial evolution, tool use, skill inheritance, intelligence
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-12OAI: oai:DiVA.org:his-12DiVA: diva2:2328
Presentation
(English)
Uppsok
Technology
Supervisors
Examiners
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2010-02-09

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fulltext(3542 kB)334 downloads
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08aeab011332f363648745722e1b5574d2b608e00abfbaaf26a96aaa1fb3ff7eb6e88866
Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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