Specification of the Unified Conceptual Space, for Purposes of Empirical Investigation

  • Joel ParthemoreEmail author
Part of the Synthese Library book series (SYLI, volume 359)


Recent years have seen a number of competing theories of concepts within philosophy of mind, supplanting the classical definitionist and imagist accounts: among them, Jerry Fodor’s Informational Atomism Theory, Jesse Prinz’s Proxytypes Theory, and Peter Gärdenfors’ Conceptual Spaces Theory (CST). On the whole there has been little empirical investigation into the competing theories’ merits; the (limited) empirical investigation of CST offers the one obvious exception. Some theories, such as Informational Atomism, seem almost beyond the possibility of such testing by design. Some philosophers would claim that theories of concepts, by their nature, cannot be tested empirically; and they raise valid concerns. Although I concede that theories of concepts are not open to direct empirical investigation, nonetheless indirect methods can provide strong circumstantial evidence for or against a theory such as CST; and I offer a research plan for doing so. Indeed, I argue that an extension of CST I call the Unified Conceptual Space Theory (UCST) is better placed than the competition when it comes to such testing, not least because it comes with a software application, in the form of a mind-mapping program, as a more-or-less direct translation of the theory into a working computer model. This paper provides the most detailed specification to date of the algorithm underlying the UCST, described in earlier publications as an attempt to move CST in a more algorithmically amenable and therefore, it is hoped, more empirically testable direction. UCST brings all the many widely divergent conceptual spaces discussed in CST together into a single unified “space of spaces” arranged along three axes, where points in the space have both local and distal connections to other points.


Empirical Investigation Conceptual Space Integral Dimension Grammatical Category Voronoi Tessellation 
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.



The author gratefully acknowledges the financial and academic support of the Centre for Cognitive Semiotics at Lund University, directed by Prof. Göran Sonesson and assisted by Prof. Jordan Zlatev; the assistance of Daniel Barratt in designing the experiments; and, finally, the helpful discussion and criticism received at seminars of the Centre for Cognitive Semiotics.


  1. Allen, C. (1999). Animal concepts revisited: The use of self-monitoring as an empirical approach. Erkenntnis, 51(1), 33–40.CrossRefGoogle Scholar
  2. Berkeley, G. (1999). Principles of human knowledge and three dialogues. Oxford/New York: Oxford University PressGoogle Scholar
  3. Brentano, F. (1995). Psychology from an empirical standpoint. London: Routledge.Google Scholar
  4. Chella, A., Coradeschi, S., Frixione, M., & Saffioti, A. (2004). Perceptual anchoring via conceptual spaces. In Proceedings of the AAAI-04 workshop on anchoring symbols to sensor data (pp. 40–45). AAAI Press, Menlo Park.Google Scholar
  5. Chella, A., Frixione, M., & Gaglio, S. (2008). A cognitive architecture for robot self-consciousness. Artificial Intelligence in Medicine, 44(2), 147–154.CrossRefGoogle Scholar
  6. Clark, A. (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford: Oxford University Press.Google Scholar
  7. Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19.CrossRefGoogle Scholar
  8. Curry, H. B. (1963). Foundations of mathematical logic. Mineola/New York: Courier Dover Publications.Google Scholar
  9. Davidson, D. (1986). A coherence theory of knowledge and truth. In E. LePore (Ed.), Truth and interpretation (pp. 307–319). Oxford: Blackwell.Google Scholar
  10. Dennett, D. C. (1969). Content and consciousness. London: Routledge & K. Paul.Google Scholar
  11. de Saussure, F. (2013 [1916]). Course in general linguistics (Trans. W. Baskin). New York: Columbia University Press.Google Scholar
  12. Evans, G. (1982). Varieties of reference. Oxford: Clarendon Press.Google Scholar
  13. Fodor, J. A. (1998). Concepts: Where cognitive science went wrong. Oxford: Clarendon Press.CrossRefGoogle Scholar
  14. Fodor, J. A. (2008). LOT 2: The language of thought revisited. New York: Oxford University Press.CrossRefGoogle Scholar
  15. Frege, G. (1892). Über Sinn und Bedeutung. Zeitschrift für Philosophie und Philosophische Kritik C:25–50, original publicationGoogle Scholar
  16. Gärdenfors, P. (2004). Conceptual spaces: The geometry of thought. Cambridge: Bradford Books.Google Scholar
  17. Gärdenfors, P. (2007). Representing actions and functional properties in conceptual spaces. In T. Ziemke, J. Zlatev, & R. Frank (Eds.), Body, language and mind, volume I: Embodiment (Vol. 1, pp. 167–195). Berlin: Mouton de Gruyter.Google Scholar
  18. Gärdenfors, P., & Warglien, M. (2012). Using conceptual spaces to model actions and events. Journal of Semantics, 29(4), 487–519. doi: 10.1093/jos/ffs007 CrossRefGoogle Scholar
  19. Goodman, N. (1976). Languages of art: An approach to a theory of symbols. Cambridge: Hackett Publishing.Google Scholar
  20. Harnad, S. (1990). The symbol grounding problem. Physica D: Nonlinear Phenomena, 42(3), 335–346.CrossRefGoogle Scholar
  21. Harvey, I. (1992). Untimed and misrepresented: Connectionism and the computer metaphor, cSRP 245.Google Scholar
  22. Hemeren, P. (2008). Mind in action: Action representation and the perception of biological motion. PhD thesis, University of Lund.Google Scholar
  23. Jaeger, G. (2010). Natural color categories are convex sets. In M. Aloni, H. Bastiaanse, T. de Jager, & K. Schulz (Eds.), Logic, language and meaning (Lecture notes in computer science, Vol. 6042/2010, pp. 11–20). Berlin/Heidelberg: Springer.Google Scholar
  24. James, W. (1975 [1909]). The meaning of truth. Cambridge: Harvard University Press.Google Scholar
  25. Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception and Psychophysics, 14, 201–211.CrossRefGoogle Scholar
  26. Kripke, S. A. (1980). Naming and necessity. Cambridge: Harvard University Press.Google Scholar
  27. LeDoux, J. E. (1996). The emotional brain: The mysterious underpinnings of emotional life. New York: Weidenfeld and Nicholson.Google Scholar
  28. Machery, E. (2009). Doing without concepts. Oxford/New York: Oxford University Press.CrossRefGoogle Scholar
  29. Margolis, E., & Laurence, S. (1999). Concepts and cognitive science. In E. Margolis & S. Laurence (Eds.), Concepts: core readings. Cambridge: MIT.Google Scholar
  30. Maturana, H. R., & Varela, F. J. (1992). The tree of knowledge: The biological roots of human understanding. London: Shambhala.Google Scholar
  31. Metzinger, T. (Ed.). (2000). Neural correlates of consciousness: Empirical and conceptual questions. Cambridge: MIT.Google Scholar
  32. Newell, A. (1980). Physical symbol systems. Cognitive Science, 4(2), 135–183.CrossRefGoogle Scholar
  33. Newen, A., & Bartels, A. (2007). Animal minds and the possession of concepts. Philosophical Psychology, 20(3), 283–308.CrossRefGoogle Scholar
  34. Parthemore, J. (2011a). Concepts enacted: Confronting the obstacles and paradoxes inherent in pursuing a scientific understanding of the building blocks of human thought. PhD thesis, University of Sussex, Falmer, Brighton, UK. Available from
  35. Parthemore, J. (2011b). Of boundaries and metaphysical starting points: Why the extended mind cannot be so lightly dismissed. Teorema, 30(2), 79–94.Google Scholar
  36. Parthemore, J. (2013). The unified conceptual space theory: An enactive theory of concepts. Adaptive Behavior, 21, 168–177. doi: 10.1177/1059712313482803.CrossRefGoogle Scholar
  37. Parthemore, J. (2014). Conceptual change and development on multiple time scales: From incremental evolution to origins. Sign System Studies Under review, 42, 193–218.CrossRefGoogle Scholar
  38. Parthemore, J., & Morse, A. F. (2010). Representations reclaimed: Accounting for the co-emergence of concepts and experience. Pragmatics & Cognition, 18(2), 273–312.CrossRefGoogle Scholar
  39. Parthemore, J., & Whitby, B. (2013). When is any agent a moral agent? Reflections on machine consciousness and moral agency. International Journal of Machine Consciousness, 5(2), 105–129.CrossRefGoogle Scholar
  40. Prinz, J. (2004). Furnishing the mind: Concepts and their perceptual basis. Cambridge: MIT.Google Scholar
  41. Rosch, E. (1975). Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7, 573–605.CrossRefGoogle Scholar
  42. Rosch, E. (1999). Principles of categorization. In E. Margolis & S. Laurence (Eds.), Concepts: Core readings (chap. 8, pp. 189–206). Cambridge: MIT.Google Scholar
  43. Ruiz-Primo, M. A., Shavelson, R. J. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33(6), 569–600.CrossRefGoogle Scholar
  44. Ryle, G. (1949). The concept of mind. London: Penguin.Google Scholar
  45. Sharples, M. (1999). How we write: An account of writing as creative design. London: Routledge.CrossRefGoogle Scholar
  46. Thompson, E. (2007). Mind in life: Biology, phenomenology and the sciences of mind. Cambridge: Harvard University Press.Google Scholar
  47. Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. Cambridge: MIT.Google Scholar
  48. Warglien, M., Gärdenfors, P., & Westera, M. (2012). Event structure, conceptual spaces and the semantics of verbs. Theoretical Linguistics, 38(3–4), 159–193. doi: 10.1515/tl-2012-0010.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Centre for Cognitive SemioticsLund UniversityLundSweden

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