본문 바로가기
KERD
논문KCI 등재

How to Integrate Representation into Computational Modeling, and Why We Should

2

조회

0

다운로드

2

인용

0

참고문헌

키워드

초록

I argue that Chalmers’s proposed computational foundation conflicts with contemporary cognitive science. I present an alternative approach to modeling the mind computationally. On my alternative approach, computational models can individuate mental states in representational terms, without any appeal to organizationally invariant properties. I develop my approach through case studies drawn from cognitive psychology, CS, and AI.

Abstract

I argue that Chalmers’s proposed computational foundation conflicts with contemporary cognitive science. I present an alternative approach to modeling the mind computationally. On my alternative approach, computational models can individuate mental states in representational terms, without any appeal to organizationally invariant properties. I develop my approach through case studies drawn from cognitive psychology, CS, and AI.

참고문헌 (40)

  1. Bays, P., "Computational Principles of Sensorimotor Control that Minimize Uncertainty and Variability", Journal of Physiology, 578, pp.387~396 (2007)
  2. Block, N., "Mental Paint, In Reflections and Replies: Essays on the Philosophy of Tyler Burge" (2003), MIT Press
  3. Brainard, D., "Bayesian Approaches to Color Vision, In The Visual Neurosciences, 4th ed" (2009), MIT Press
  4. Burge, T., "Foundations of Mind" (2007), Oxford University Press
  5. Burge, T., "Five Theses on De Re States and Attitudes, In The Philosophy of David Kaplan" (2009), Oxford University Press
  6. Burge, T., "Origins of Objectivity" (2010), Oxford University Press
  7. Burge, T., "Origins of Perception", Disputatio, 4, pp.4~38 (2010)
  8. Chalmers, D., "Perception and the Fall from Eden, In Perceptual Experience" (2006), Oxford University Press
  9. Chalmers, D. ., "A Computational Foundation for the Study of Cognition", This volume, ~ (2012)
  10. Chater, N., "Probabilistic Models of Language Processing and Acquisition", Trends in Cognitive Science, 10, pp.335~344 (2006)
  11. Chater, N., "The Probabilistic Mind" (2008), Oxford University Press
  12. Cheng, K., "Bayesian Integration of Spatial Information", Psychological Bulletin, 133, pp.625~637 (2007)
  13. Egan, F., "In Defense of Narrow Mindedness", Mind and Language, 14, pp.177~194 (1999)
  14. Evans, G., "The Varieties of Reference" (1983), Oxford University Press
  15. Fodor, J., "Representations" (1981), MIT Press
  16. Fodor, J., "Replies, In Meaning in Mind" (1991), Blackwell
  17. Fodor, J., "The Elm and the Expert" (1994), MIT Press
  18. Gershman, S., "Multistability and Perceptual Inference", Neural Computation, 24, pp.1~24 (2012)
  19. Gunter, C., "Semantics of Programming Languages" (1992), MIT Press
  20. Haugeland, J., "Artificial Intelligence: The Very Idea" (1985), MIT Press
  21. Knill, D, "The Bayesian Brain: The Role of Uncertainty in Neural Coding and Computation", Trends in Neuroscience, 27, pp.712~719 (2004)
  22. Knill, D., "Perception as Bayesian Inference" (1996), Cambridge University Press
  23. Lewis, D., "Psychophysical and Theoretical Identifications", Australasian Journal of Philosophy, 50, pp.249~258 (1972)
  24. Longley, J., "Notions of Computability at Higher Types I, In Logic Colloquium 2000" (2000), A. K. Peters
  25. Mitchell, J., "Foundations for Programming Languages" (1996), MIT Press
  26. Park, S., "“A Probabilistic Language Based upon Sampling Functions", ACM Transactions on Programming Languages and Systems, 5, pp.1~45 (2008)
  27. Peacocke, C., "A Study of Concepts" (1992), MIT Press
  28. Peacocke, C., "Content, Computation, and Externalism", Mind and Language, 9, pp.303~335 (1994)
  29. Piantadosi, S., "Bootstrapping in a Language of Thought: A Formal Model of Numerical Concept Learning", Cognition
  30. Piccinini, G., "Computation without Representation", Philosophical Studies, 137, pp.205~241 (2008)
  31. Plotkin, G., "LCF Considered as a Programming Language", Theoretical Computer Science, 5, pp.223~255 (1977)
  32. Putnam, H., "Mind, Language, and Reality: Philosophical Papers, vol. 2" (1975), Cambridge University Press
  33. Quine, W. V., "Word and Object" (1960), MIT Press
  34. Rescorla, M., "Church’s Thesis and the Conceptual Analysis of Computability", Notre Dame Journal of Formal Logic, 48, pp.253~280 (2007)
  35. Rescorla, M., "Against Structuralist Theories of Computational Implementation", British Journal for the Philosophy of Science
  36. Rescorla, M., "Bayesian Perceptual Psychology, In The Oxford Handbook of the Philosophy of Perception", Oxford University Press
  37. Scott, D., "A Type-Theoretical Alternative to ISWIM, CUCH, and OWHY", Theoretical Computer Science, 121, pp.411~440 (1993)
  38. Shepherdson, J., "Computability of Recursive Functions", Journal of the Association of Computing Machinery, 10, pp.217~255 (1961)
  39. Stich, S., "From Folk Psychology to Cognitive Science" (1983), MIT Press
  40. Stone, J., "Footprints Sticking Out of the Sand, Part 2: Children’s Bayesian Priors for Shape and Lighting Direction", Perception, 40, pp.175~190 (2011)

관련 논문AI추천

이 간행물의 다른 논문 (3건)