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Part I - Correspondence problems and mechanisms

Published online by Cambridge University Press:  10 December 2009

Chrystopher L. Nehaniv
Affiliation:
Research Professor of Mathematical and Evolutionary Computer Sciences in the School of Computer Science, University of Hertfordshire, Adaptive Systems & Algorithms Research Groups, Hertfordshire
Kerstin Dautenhahn
Affiliation:
Research Professor of Artificial Intelligence in the School of Computer Science, University of Hertfordshire, Adaptive Systems Research Group
Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire
Kerstin Dautenhahn
Affiliation:
University of Hertfordshire
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Summary

The problem for one individual of producing behaviour that matches, in some aspect, with behaviour it observes in another comprises an instance of the correspondence problem (compare Part IV, Development and embodiment, this volume; Nehaniv and Dautenhahn, 2002). The particular nature of the kind of similarity that is matched determines different classes of correspondence problems. The bodies and affordances available to the two individuals are in general not the same, so the problem is non-trivial – even ignoring the complexities of perception in registering the observed behaviour. Mechanisms for solving these correspondence problems are numerous, and, while generally occurring in a social context, they may or may not involve learning. On the other hand, every social learning mechanism solves a particular class of correspondence problems.

Geoffrey Bird and Cecilia Heyes discuss several alternative mechanisms for solving correspondence problems in which the observer must generate motor commands to match visual input. Of particular interest due to the complexity of mechanism they appear to require for their solution are cases in which the perceptual discrepancies cannot be used as simple feedback to guide mismatch reduction and achieve matching behaviour. Various levels of such perceptual opacity occur when the visual experience in observing another individual and the experience which occurs when carrying out the ‘same’ actions are dissimilar, as in a curtsy bow or in playing tennis.

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Imitation and Social Learning in Robots, Humans and Animals
Behavioural, Social and Communicative Dimensions
, pp. 19 - 22
Publisher: Cambridge University Press
Print publication year: 2007

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  • Correspondence problems and mechanisms
    • By Chrystopher L. Nehaniv, Research Professor of Mathematical and Evolutionary Computer Sciences in the School of Computer Science, University of Hertfordshire, Adaptive Systems & Algorithms Research Groups, Hertfordshire, Kerstin Dautenhahn, Research Professor of Artificial Intelligence in the School of Computer Science, University of Hertfordshire, Adaptive Systems Research Group
  • Edited by Chrystopher L. Nehaniv, University of Hertfordshire, Kerstin Dautenhahn, University of Hertfordshire
  • Book: Imitation and Social Learning in Robots, Humans and Animals
  • Online publication: 10 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511489808.002
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  • Correspondence problems and mechanisms
    • By Chrystopher L. Nehaniv, Research Professor of Mathematical and Evolutionary Computer Sciences in the School of Computer Science, University of Hertfordshire, Adaptive Systems & Algorithms Research Groups, Hertfordshire, Kerstin Dautenhahn, Research Professor of Artificial Intelligence in the School of Computer Science, University of Hertfordshire, Adaptive Systems Research Group
  • Edited by Chrystopher L. Nehaniv, University of Hertfordshire, Kerstin Dautenhahn, University of Hertfordshire
  • Book: Imitation and Social Learning in Robots, Humans and Animals
  • Online publication: 10 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511489808.002
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Correspondence problems and mechanisms
    • By Chrystopher L. Nehaniv, Research Professor of Mathematical and Evolutionary Computer Sciences in the School of Computer Science, University of Hertfordshire, Adaptive Systems & Algorithms Research Groups, Hertfordshire, Kerstin Dautenhahn, Research Professor of Artificial Intelligence in the School of Computer Science, University of Hertfordshire, Adaptive Systems Research Group
  • Edited by Chrystopher L. Nehaniv, University of Hertfordshire, Kerstin Dautenhahn, University of Hertfordshire
  • Book: Imitation and Social Learning in Robots, Humans and Animals
  • Online publication: 10 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511489808.002
Available formats
×