Skip to main content

Abstract

Cognitive processes are often modelled in computational terms. Can this still be done if only minimal assumptions are made about any sort of representation of reality? Is there a purely knowledge-based theory of computation that explains the key phenomena which are deemed to be computational in both living and artificial systems as understood today? We argue that this can be done by means of techniques inspired by the modelling of dynamical systems. In this setting, computations are defined as curves in suitable metaspaces and knowledge is generated by virtue of the operation of the underlying mechanism, whatever it is. Desirable properties such as compositionality will be shown to fit naturally. The framework also enables one to formally characterize the computational behaviour of both knowledge generation and knowledge recognition. The approach may be used in identifying when processes or systems can be viewed as being computational in general. Several further questions pertaining to the philosophy of computing are considered.

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

Access this chapter

Institutional subscriptions

Notes

  1. 1.

    The Tarski–Kantorovich fixed point theorem states the following: Let \(\langle X,\le \rangle \) be a cpo and let \(H: X \rightarrow X\) be chain-continuous. If there is an \(x \in X\) such that \(x \le H(x)\), then \(x'=\sup _n H^n(x)\) is a fixpoint and in fact the least fixpoint of H among all y with \(y \ge x\). For a proof see e.g. [22]. Chain-continuity is also known as Scott-continuity.

References

  1. Farkaš, I.: Indispensability of computational modeling in cognitive science. J. Cognit. Sci. 13, 401–435 (2012)

    Google Scholar 

  2. Wiedermann, J., van Leeuwen, J.: Rethinking computations. In: 6th AISB Symp. on Computing and Philosophy: The Scandal of Computation—What is Computation? AISB Convention 2013 Proceedings, pp. 6–10. AISB, Exeter, UK (2013)

    Google Scholar 

  3. Wiedermann, J., van Leeuwen, J.: Computation as knowledge generation, with application to the observer-relativity problem. In: 7th AISB Symp. on Computing and Philosophy: Is Computation Observer-Relative? AISB Convention 2014 Proceedings, AISB, Goldsmiths, University of London (2014)

    Google Scholar 

  4. Beck, L.W.: The actor and the spectator—foundations of the theory of human action. Yale University Press (1975) (Reprinted: Key Texts, Thoemmes Press, 1998)

    Google Scholar 

  5. Blass, A., Gurevich, Y.: Algorithms: a quest for absolute definitions. Bulletin EATCS 81, 195–225 (2003)

    Google Scholar 

  6. Gurevich, Y.: Foundational analyses of computation. In: Cooper, S.B., Dawar, A., Löwe, B. (eds.), How the World Computes, Proc. CiE 2012. Lecture Notes in Computer Science, vol. 7318, pp. 264–275. Springer (2012)

    Google Scholar 

  7. Floridi, L.: The Philosophy of Information. Oxford University Press, Oxford (2011)

    Book  Google Scholar 

  8. Searle, J.R.: Minds, brains, and programs. Behavioral Brain Sci. 3, 417–457 (1980)

    Article  Google Scholar 

  9. Searle, J.R.: Is the brain a digital computer? Proceedings and Addresses of the American Philosophical Association 64(3), 21–37 (1990)

    Article  Google Scholar 

  10. Tong, D.: The unquantum quantum. Sci. Am. 307, 46–49 (2012)

    Article  Google Scholar 

  11. Frailey, D.J.: Computation is process. In: Ubiquity Symposium ’What is Computation?’, ACM Magazine Ubiquity, November issue, Article No 5 (2010)

    Google Scholar 

  12. Horsman, C., Stepney, S., Wagner, R.C., Kendon, V.: When does a physical system compute? Proc. Royal Soc. A 470(2169), 20140182 (2014)

    Article  Google Scholar 

  13. Horsman, C., Kendon, V., Stepney, S., Young, J.P.W.: Abstraction and representation in living organisms: when does a biological system compute? In: Representation and Reality: Humans, Animals and Machines. Springer, Heidelberg (2017)

    Chapter  Google Scholar 

  14. Arbib, M.A.: Automata theory and control theory—a rapprochement. Automatica 3, 161–189 (1966)

    Article  Google Scholar 

  15. Mazurkiewicz, A.: Concurrent program schemes and their interpretation. Technical Report No. PB-17, DAIMI, Datalogisk Afdeling, Aarhus University, Aarhus (1977)

    Google Scholar 

  16. Scott, D.S.: Continuous lattices. In: Lawvere, F. (ed.), Toposes, Algebraic Geometry and Logic. Lecture Notes in Mathematics, vol. 274, pp. 97–136. Springer (1972)

    Google Scholar 

  17. Longo, G.: Some topologies for computations, invited lecture. In: Géométrie au XX siècle, 1930–2000, Paris. http://www.di.ens.fr/users/longo/files/topol-comp.pdf (2001)

  18. Fodor, J.A.: The mind-body problem. Sci. Am. 244, 124–132 (1981)

    Article  Google Scholar 

  19. Piccinini, G.: Computation without representation. Philos. Stud. 137(2), 205–241 (2008)

    Article  MathSciNet  Google Scholar 

  20. Piccinini, G., Bahar, S.: Neural computation and the computational theory of cognition. Cognit. Sci. 37(3), 453–488 (2013)

    Article  Google Scholar 

  21. Hopcroft, J.E., Ullman, J.D.: Formal Languages and their Relation to Automata. Addison-Wesley, Reading, MA (1968)

    Google Scholar 

  22. Ok, E.A.: Elements of order theory. Ch 6: Order-theoretic fixed point theory. https://sites.google.com/a/nyu.edu/efeok/books

  23. Abramsky, S.: Two puzzles about computation. In: Cooper, S.B., van Leeuwen, J. (eds.) Alan Turing—His Work and Impact, pp. 53–57. Elsevier, Amsterdam (2013)

    Google Scholar 

  24. Pylyshyn, Z.W.: Computation and cognition: toward a foundation for cognitive science. MIT Press, Cambridge MA (1984)

    Google Scholar 

  25. Putnam, H.: Brains and behavior. Presented to the American Association for the Advancement of Science, section L (History and Philosophy of Science), 27 Dec 1961

    Google Scholar 

  26. Piccinini, G.: Computational modelling vs computational explanation: is everything a Turing machine, and does it matter to the philosophy of mind? Aust. J. Philoso. 85(1), 93–115 (2007)

    Google Scholar 

  27. Dodig-Crnkovic, G.: Modeling life as cognitive info-computation. In: Beckman, A., Csuhaj-Varjú, E., Meer, K. (eds.), Language, Life, Limits, Proc. CiE 2014. Lecture Notes in Computer Science, vol. 8493, pp. 153–162. Springer (2014)

    MATH  Google Scholar 

Download references

Acknowledgements

The work of the second author was partially supported by ICS AS CR fund RVO 67985807 and the Czech National Foundation Grant No. 15-04960S.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jan van Leeuwen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

van Leeuwen, J., Wiedermann, J. (2017). Knowledge, Representation and the Dynamics of Computation. In: Dodig-Crnkovic, G., Giovagnoli, R. (eds) Representation and Reality in Humans, Other Living Organisms and Intelligent Machines. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-43784-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-43784-2_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43782-8

  • Online ISBN: 978-3-319-43784-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics