Advertisement

Empirical and Metaphysical Anti-Representationalism

  • Anthony Chemero

Abstract

Anti-representationalism is in the air. In the last few years, many philosophers and cognitive scientists have considered or even embraced the claim that cognition is not representational, often without giving explicit consideration to what exactly this means. The point of this essay is to try to make some sense of claims that cognitive science can do without representations by proposing a taxonomy for them. In what follows, I will make a distinction between two different varieties of anti-representationalism. And, with this distinction in hand, I will consider some actual scientific work that has led to claims that cognitive science can do, at least in part, without representations.

Keywords

Olfactory Bulb Connectionist Network Color Vision Perceptual System Cognitive Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agre, P. and Chapman, D. (1987) Pengi: An Implementation of a Theory of Activity. Proceedings of AAAI-87. Menlo Park, CA: AAAI.Google Scholar
  2. Agre, P. and Chapman, D. (1990) What are Plans for? Robotics and Autonomous Systems 6: 17–34.CrossRefGoogle Scholar
  3. Akins, K. (1993) What is it like to be Boring and Myopic? In: Dahlbom, B. (ed.) Dennett and his Critics. Maiden, MA: Blackwell.Google Scholar
  4. Amit, D. (1989) Modeling Brain Function: The World of Attractor Networks. Cambridge: Cambridge University Press.Google Scholar
  5. Beer, R. (1995) Computational and Dynamical Languages for Autonomous Agents. In: Port, R. and van Gelder, T. (eds.) Mind as Motion. Cambridge: MIT Press.Google Scholar
  6. Chapman, D. (1991) Vision, Instruction and Action. Cambridge: MIT Press.Google Scholar
  7. Chemero, A. (1995) Connectionism and Representations. In: M. Evers (ed.) Proceedings of the 1995 Midwest Artificial Intelligence and Cognitive Science Society.Google Scholar
  8. Chemero, A. (1998) How to be an Anti-representationalist. Doctoral dissertation. Bloomington: Indiana University.Google Scholar
  9. Chemero, A. (1998a) A Stroll Among the Worlds of Animats and Persons: A Review of Andy Clark’s Being There. Psyche 4 (14).Google Scholar
  10. Cussins, A. (1990) The Connectionist Construction of Concepts. In: Boden, M (ed.) Philosophy of Artificial Intelligence. New York: Oxford University Press.Google Scholar
  11. Dennett, D. (1995) Darwin’s Dangerous Idea. New York: Simon and Schuster.Google Scholar
  12. Dreyfus, H. (1972/1993) What Computers Still Can’t Do. Cambridge: MIT Press.Google Scholar
  13. Dreyfus, H. (1991) Being-in-the-World. Cambridge: MIT Press.Google Scholar
  14. Freeman, W. and Skarda, C. (1990) Representations: Who Needs Them? In: McGaugh, et al (eds.) Brain Organization and Memory Cells, Systems and Circuits. New York: Oxford University Press.Google Scholar
  15. Gibson, J. (1979) The Ecological Approach to Visual Perception. New Jersey: Houghton Mifflin.Google Scholar
  16. Harvey, I. (1992) Untimed and Misrepresented: Connectionism and the Computer Metaphor. Tech. Rep. 245. Sussex: U. of Sussex.Google Scholar
  17. Harvey, I., Husbands, P., Cliff, D., Thompson, A., and Jakobi, N. (1997) Evolutionary Robotics: The Sussex Approach. University of Sussex Tech Report.Google Scholar
  18. Haugeland, J. (1985) Artificial Intelligence: The Very Idea. Cambridge: MIT Press.Google Scholar
  19. Haugeland, J. (1998) Having Thought. New York: Cambridge University Press.Google Scholar
  20. Heidegger, M. (1927) Sein und Zeit. Translated Macquarrie and Robinson, 1962. New York: Harper and Row.Google Scholar
  21. Husbands, P., Harvey, I., and Cliff, D. (1995) Circle in the Round: State Space Attractor for Evolved Sight Robots. Journal of Robotics and Autonomous Systems 15: 83–106.CrossRefGoogle Scholar
  22. Lloyd, D. (unpublished).Google Scholar
  23. Merleau-Ponty, M. (1963) The Structure of Behavior. Translated by Fisher. Boston: Beacon Press.Google Scholar
  24. Michaels, C. and Carello, C. (1981) Direct Perception. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  25. Millikan, R. (1984) Language, Thought and Other Biological Categories. Cambridge: MIT Press.Google Scholar
  26. Millikan, R. (1993) White Queen Psychology and Other Essays for Alice. Cambridge: MIT Press.Google Scholar
  27. Petitot, J. (1995) Morphodynamics and Attractor Syntax. In: Port, R. and van Gelder, T. (eds.) Mind as Motion. Cambridge: MIT Press.Google Scholar
  28. Pollack, J. (1990) Recursive Distributed Representations. Artificial Intelligence 46: 77–105.CrossRefGoogle Scholar
  29. Port, R. and van Gelder, T. (1995) Mind as Motion. Cambridge: MIT Press.Google Scholar
  30. Port, R., Anderson, S., and McAuley, D. (1996) Toward Simulated Audition in Open Environments. In: Covey E., Hawkins H. and Port, R. (eds.) Neural Representation of Temporal Patterns. New York: Plenum.Google Scholar
  31. Preston, B. (1995) Heideggerian AI. Philosophy and Phenomenological Research.Google Scholar
  32. Ramsey, W. (1997) Do Connectionist Representations Earn their Explanatory Keep? Mind and Language.Google Scholar
  33. Rorty, R. (1979) Philosophy and the Mirror of Nature. Princeton: Princeton U. Press.Google Scholar
  34. Rorty, R. (1991) Philosophical Papers. Cambridge: Cambridge U. Press.Google Scholar
  35. Ryle, G. (1949) The Concept of Mind. London: Hutchinson.Google Scholar
  36. Skarda, C. and Freeman, W. (1987) How the Brain Makes Chaos to Make Sense of the World. Behavioral and Brain Sciences 10: 161–195.CrossRefGoogle Scholar
  37. Smith, B. C., (1996) On the Origin of Objects. Cambridge: MIT Press.Google Scholar
  38. Stich, S. (1983) From Folk Psychology to Cognitive Science. Cambridge: MIT Press.Google Scholar
  39. Thompson, E., Palaciois, A., and Varela. F. (1992) Ways of Coloring. Behavioral and Brain Sciences 15.Google Scholar
  40. van Gelder, T. (1995) What might Cognition be if not Computation? Journal of Philosophy 91: 345–381.CrossRefGoogle Scholar
  41. van Gelder, T. (1998) The Dynamical Systems Hypothesis. Behavioral and Brain Sciences.Google Scholar
  42. van Gelder, T. and Port, R. (1994) Beyond Symbolic. In: Hanovar and Uhr (eds.) Symbol Processing and Connectionist Network Models in Artificial Intelligence and Cognitive Modelling.Google Scholar
  43. van Gelder, T. and Port, R. (1995) It’s about Time. In: Port, R. and van Gelder, T. (eds.) Mind as Motion. Cambridge: MIT Press.Google Scholar
  44. Varela, F., Thompson, E. and Rosch, E. (1991) The Embodied Mind. Cambridge: MIT Press.Google Scholar
  45. von Uexküll, J. (1934) A Stroll through the Worlds of Animals and Men. In: Lashley, K. (ed.) Instinctive Behavior. New York: International Press.Google Scholar
  46. Wheeler, M. (1994) From Activation to Activity: Representation, Computation and the Dynamics of Neural Network Control Systems. Artificial Intelligence and the Simulation of Behavior Quarterly 87: 36–42.Google Scholar
  47. Winograd, T. and Flores, F. (1986) Understanding Computers and Cognition. Norwood, NJ: Ablex.Google Scholar

Copyright information

© Kluwer Academic/Plenum Publishers 1999

Authors and Affiliations

  • Anthony Chemero
    • 1
  1. 1.Department of Philosophy and Cognitive Science ProgramIndiana UniversityBloomingtonUSA

Personalised recommendations