Skip to main content

Can development be designed? What we may learn from the Cog Project

  • 3. Adaptive and Cognitive Systems
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 929))

Abstract

Neither design nor evolutionary approaches to building behaviorbased robots feature a role for development in the genesis of behavioral organization. However, the new Cog Project aims to build a humanoid robot that will display behavioral abilities observed in human infants; and proposes making use of ideas from evolution and developmental psychology in its design. This paper provisionally evaluates this work from a developmental perspective, to show how developmental study may offer not only a source of phenomena for modelling but also a method that contributes to our understanding of self-organization. Cog's design methodology confronts problems with selection and interpretation of component behaviors, and how these may be better understood through appropriate developmental study is illustrated. Cog's design principles are shown to exhibit interesting convergences with infant mechanisms, based on the significance of emergent functionality and the action- as opposed to representation-based nature of initial and outcome mechanisms, but analysis of infants suggests a more constructive view of ability is required.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bersini, H. (1992). Animat's I. In F.J. Varela & P. Bourgine (Eds.), Towards a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  2. Brooks, R. (1986) A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, RA 2, 14–23.

    Google Scholar 

  3. Brooks, R. (1990) Elephants don't play chess. In P. Maes (ed.) Designing Autonomous Agents. Bradford/M.I.T. Press.

    Google Scholar 

  4. Brooks, R.A. (1991a) Intelligence without reasoning. Proceedings of the Twelfth International Joint Conference on Artificial Intelligence.

    Google Scholar 

  5. Brooks, R. (1991b) Intelligence without representation. Artificial Intelligence, 47, 139–160.

    Google Scholar 

  6. Brooks, R.A. (1994) Coherent behavior from many adaptive processes. In D. Cliff, P. Husbands, J.-A. Meyer & S.W. Wilson (Eds.) Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  7. Brooks, R.A. and Stein, A. (1993) Building brains for bodies. MIT AI Laboratory Memo No. 1439.

    Google Scholar 

  8. Clark, A. and Toribo, J. (1994) Doing without representing? University of Sussex, Cognitive Science Research Paper, Serial No. CSRP 310.

    Google Scholar 

  9. Cliff, D., Harvey, I. and Husbands, P. (1992) Incremental evolution of neural network architectures for adaptive behavior. University of Sussex, Cognitive Science Research Paper No.250.

    Google Scholar 

  10. Cliff, D., Harvey, I. and Husbands, P. (1994) General visual robot controller networks via artificial vision. University of Sussex, Cognitive Science Research Paper No.318.

    Google Scholar 

  11. Dennis, W. (1960) Causes of retardation among institutional children: Iran. Journal of Genetic Psychology, 56 77–86.

    Google Scholar 

  12. Dretske, F.I. (1988) Explaining Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  13. Foner, L. and Maes, P. (1994) Paying attention to what's important: Using focus of attention to improve unsupervised learning. In D. Cliff, P. Husbands, J.-A. Meyer & S.W. Wilson (Eds.) Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  14. Gibson, J.J. (1979) The Ecological Approach to Visual Perception. Boston MA: Houghton-Mifflin.

    Google Scholar 

  15. Gibson, K.R. (1981) Comparative neuro-ontogeny. In G. Butterworth (ed.) Infancy and Epistemology. Brighton: Harvester.

    Google Scholar 

  16. Goodwin, B. (1993) Development as a robust natural process. In W. Stein & F.J. Varela (eds.) Thinking About Biology. Reading, MA: Addison-Wesley.

    Google Scholar 

  17. Harvey, I., Husbands, P. and Cliff, D. (1994) Issues in evolutionary robotics. University of Sussex, Cognitive Science Research Paper No. 219.

    Google Scholar 

  18. Harvey, I., Husbands, P. and Cliff, D. (1994) Seeing the light: Artificial evolution, real vision. In D. Cliff, P. Husbands, J.-A. Meyer & S.W. Wilson (Eds.) Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  19. Israel, D. (1988) Bogdan on Information. Mind and Language, 3 123–140.

    Google Scholar 

  20. Maturana, H. and Varela, F.J. (1988) The Tree of Knowledge. Boston & London: Shambhala.

    Google Scholar 

  21. Meyer, J.-A. & Guillot (1994) From SAB90 to SAB94: Four years of animat research. In D. Cliff, P. Husbands, J.-A. Meyer & S.W. Wilson (Eds.) Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  22. Mitchell, T.M. (1983) Learning and Problem Solving. Proceedings of the Eighth International Joint Conference on Artificial Intelligence.

    Google Scholar 

  23. Oyama, S. (1985) The Ontogeny of Information. Cambridge: Cambridge UniversityPress.

    Google Scholar 

  24. Parker, S.T. (1985) Higher intelligence as an adaptation for social and technological strategies in early Homo Sapiens. In G. Butterworth, J.C. Rutkowska & M. Scaife (eds.) Evolution and Developmental Psychology. New York: St. Martin's Press

    Google Scholar 

  25. Parker, S.T. and Gibson, K.R. (1979) A developmental model for the evolution of language and intelligence in early hominids. Behavioral and Brain Sciences, 2 367–407.

    Google Scholar 

  26. Piaget, J. (1971) Biology and Knowledge. Edinburgh: Edinburgh University Press.

    Google Scholar 

  27. Reeke, G.N., Finkel, L.H., Sporns, O. and Edelman, G.M. (1990) Synthetic neural modeling: A multilevel approach to the analysis of brain complexity. In G.M. Edelman, W.E. Gall & W.M. Cowan (eds.) Signal and Sense: Local and Global Order in Perceptual Maps. New York: Wiley-Liss.

    Google Scholar 

  28. Rutkowska, J.C. (1994a) Emergent functionality in human infants. In D. Cliff, P. Husbands, J.-A. Meyer & S.W. Wilson (Eds.) Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  29. Rutkowska, J.C. (1994b) Prehension intention from 12 to 22 weeks. Presented at the IXth International Conference on Infant Studies. Paris, 2–5 June.

    Google Scholar 

  30. Rutkowska, J.C. (1994c). Scaling up sensorimotor systems: Constraints from human infancy. Adaptive Behavior, 2 349–373.

    Google Scholar 

  31. Smithers, T. (1994) On why better robots make it harder. In D. Cliff, P. Husbands, J.-A. Meyer and S.W. Wilson (eds.) From Animals to Animats 3. Cambridge, MA: MIT Press/Bradford Books.

    Google Scholar 

  32. Valsiner, J. (1987) Culture and the Development of Children's Action. Chichester: Wiley.

    Google Scholar 

  33. Varela, F.J. (1988). Cognitive Science: A Cartography of Current Ideas. Author's unpublished translation of F.J. Varela (1989). Connaitre — Les Sciences Cognitives: Tendances et Perspectives. Paris: Editions du Seuil.

    Google Scholar 

  34. Varela, F.J. (1993). Organism: A meshwork of selfless selves. Second European Conference on Artificial Life. Brussels, 24–26 May.

    Google Scholar 

  35. Wood, D., Bruner, J.S. and Ross, G. (1976) The role of tutoring in problem-solving. Journal of Child Psychology and Psychiatry, 17 89–100.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Federico Morán Alvaro Moreno Juan Julián Merelo Pablo Chacón

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Rutkowska, J.C. (1995). Can development be designed? What we may learn from the Cog Project. In: Morán, F., Moreno, A., Merelo, J.J., Chacón, P. (eds) Advances in Artificial Life. ECAL 1995. Lecture Notes in Computer Science, vol 929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59496-5_313

Download citation

  • DOI: https://doi.org/10.1007/3-540-59496-5_313

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59496-3

  • Online ISBN: 978-3-540-49286-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics