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2 - Nine billion correspondence problems

Published online by Cambridge University Press:  10 December 2009

Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire, Adaptive Systems and Algorithms Research Groups, UK
Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire
Kerstin Dautenhahn
Affiliation:
University of Hertfordshire
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Summary

Matching behaviours

Numerous insightful descriptions of mechanisms that could be responsible for generating particular examples of social learning and related phenomena in ethology and psychology have been described (see e.g. Zentall and B. G. Galef, 1988; Heyes and Galef, 1996; Tomasello and Call, 1997; Byrne and Russon, 1998; Byrne, 1999; Heyes and Ray, 2000; Dautenhahn and Nehaniv, 2002). For robotics and software, particular general methods for solving such problems have been proposed by Nehaniv and Dautenhahn (2001) and Alissandrakis et al. (2002). Despite variations in embodiments and what they afford agents (biological, software or robots), this raises the possibility for harnessing sociality and of an artificial basis for cultural transmission of skills in societies of artifacts, which might also learn from and interact with humans (Dautenhahn, 1995; Billard and Dautenhahn, 1998; Alissandrakis et al., 2003a, b; Chapter 12, this volume).

To formulate problems of matched behaviour in general, we use the following variant of Mitchell's (1987) definition of imitation for what we will call matching behaviour:

  1. A behaviour C is produced by an organism and/or machine, where

  2. C is similar to another behaviour M,

  3. Registration of M is necessary for the production of C, and

  4. C is designed to be similar to M.

Note that novelty and learning are not explicitly required here, and whether or not the entire behaviour, or its application, or its components or some combination of them is novel or being learned is left open (see Whiten, 2002b; Dautenhahn and Nehaniv, 2002).

Type
Chapter
Information
Imitation and Social Learning in Robots, Humans and Animals
Behavioural, Social and Communicative Dimensions
, pp. 35 - 46
Publisher: Cambridge University Press
Print publication year: 2007

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References

Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2002). Imitation with ALICE: learning to imitate corresponding actions across dissimilar embodiments. IEEE Transactions on Systems, Man and Cybernetics: Part A, 32(4), 482–96.CrossRefGoogle Scholar
Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2003a). Solving the correspondence problem between dissimilarly embodied robotic arms using the alice imitation mechanism. In Proceedings of the Second International Symposium on Imitation in Animals and Artifacts (K. Dautenhahn and C. L. Nehaniv, Programme Chairs). Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB).Google Scholar
Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2003b). Synchrony and perception in robotic imitation across embodiments. In IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA'03), 923–30.Google Scholar
Billard, A. and Dautenhahn, K. (1998). Grounding communication in autonomous robots: an experimental study. Robotics and Autonomous Systems, 24(1–2), 71–81.CrossRefGoogle Scholar
Byrne, R. W. (1999). Imitation without intentionality: using string parsing to copy the organization of behaviour. Animal Cognition, 2, 63–72.CrossRefGoogle Scholar
Byrne, R. W. and Russon, A. E. (1998). Learning by imitation: a hierarchical approach. Behavioral and Brain Sciences, 21, 667–709.CrossRefGoogle ScholarPubMed
Call, J. and Carpenter, M. (2002). Three sources of information in social learning. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press, 211–28.Google Scholar
Condon, W. S. and Ogston, W. D. (1967). A segmentation of behavior. Journal of Psychiatric Research, 5, 221–35.CrossRefGoogle Scholar
Dautenhahn, K. (1994). Trying to imitate – a step towards releasing robots from social isolation. In Gaussier, P. and Nicoud, J.-D. (eds.), Proceedings of From Perception to Action Conference, Lausanne, Switzerland. Los Alamitos, CA: IEEE Computer Society Press, 290–301.Google Scholar
Dautenhahn, K. (1995). Getting to know each other – artificial social intelligence for autonomous robots. Robotics and Autonomous Systems, 16, 333–56.CrossRefGoogle Scholar
Dautenhahn, K. and Nehaniv, C. L. (2002). An agent-based perspective on imitation. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press.Google Scholar
Goodenough, O. (2002). Information and replication in culture: three modes for the transmission of culture through observed action. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press, 573–585.Google Scholar
Hall, E. T. (1983). The Dance of Life: The Other Dimension of Time. New York, NY: Anchor Press/Doubleday.Google Scholar
Heyes, C. M. and Galef, B. G. (1996). Social Learning in Animals: The Roots of Culture. Academic Press.Google Scholar
Heyes, C. M. and Ray, E. D. (2000). What is the significance of imitation in animals?Advances in the Study of Behavior, 29, 215–45.CrossRefGoogle Scholar
Kendon, A. (1970). Movement coordination in social interaction: some examples described. Acta Psychologica, 32, 100–25.CrossRefGoogle ScholarPubMed
Mitchell, R. W. (1987). A comparative-developmental approach to understanding imitation. In Bateson, P. P. G. and Klopfer, P. H. (eds.), Perspectives in Ethology 7: Alternatives. New York, NY: Plenum Press, 183–215.CrossRefGoogle Scholar
Miyake, Y. (2003). Co-creation in man–machine interaction. In 12th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2003), 321–4.Google Scholar
Nehaniv, C. L. (1996). From relation to emulation: the covering lemma for transformation semigroups. Journal of Pure and Applied Algebra, 107(1), 75–87.CrossRefGoogle Scholar
Nehaniv, C. L. (1999). Meaning for observers and agents. In IEEE International Symposium on Intelligent Control/Intelligent Systems and Semiotics, ISIC/ISAS'99 – September 15–17, 1999 Cambridge, Massachusetts, USA, 435–440.Google Scholar
Nehaniv, C. L. and Dautenhahn, K. (2001). Like me? – measures of correspondence and imitation. Cybernetics and Systems, 32(1–2), 11–51.Google Scholar
Nehaniv, C. L. and Dautenhahn, K. (2002). The correspondence problem. In Dautenhahn, K. and Nehaniv, C. L. (ed.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press.Google Scholar
Ogawa, H. and Watanabe, T. (2001). Interrobot: speech-driven embodied interaction robot. Advanced Robotics, 15(3), 371–7.CrossRefGoogle Scholar
Robins, B., Dautenhahn, K., Nehaniv, C. L., Mirza, N. A., Francois, D., and Olsson, L. (2005). Sustaining interaction dynamics and engagement in dyadic child–robot interaction kinesics: lessons learnt from an exploratory study. In 14th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2005), 716–22.CrossRefGoogle Scholar
Tomasello, M. and Call, J. (1997). Primate Cognition. Oxford: Oxford University Press.Google Scholar
Watanabe, T. (2004). E-cosmic: embodied communication system for mind connection. In 13th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2004), 1–6.Google Scholar
Whiten, A. (2002a). Imitation of sequential and hierarchical structure in action: experimental studies with children and chimpanzees. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press, 191–209.Google Scholar
Whiten, A. (2002b). Selective imitation in ape and child: A window on the construal of others' actions. Presentation at Perspectives on Imitation: From Cognitive Neuroscience to Social Science (Royaumont Abbey – France, 24–26 May 2002, Organizer: Susan Hurley).Google Scholar
Zentall, T. and Galef, B. G., , J. (eds.) (1988). Social Learning: Psychological and Biological Perspectives. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Zentall, T. R. (2001). Imitation and other forms of social learning in animals: evidence, function, and mechanisms. Cybernetics and Systems, 32(1–2), 5396.CrossRefGoogle Scholar

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