Minds and Machines

, Volume 19, Issue 4, pp 465–475 | Cite as

Is Evolution Algorithmic?

Article

Abstract

In Darwin’s Dangerous Idea, Daniel Dennett claims that evolution is algorithmic. On Dennett’s analysis, evolutionary processes are trivially algorithmic because he assumes that all natural processes are algorithmic. I will argue that there are more robust ways to understand algorithmic processes that make the claim that evolution is algorithmic empirical and not conceptual. While laws of nature can be seen as compression algorithms of information about the world, it does not follow logically that they are implemented as algorithms by physical processes. For that to be true, the processes have to be part of computational systems. The basic difference between mere simulation and real computing is having proper causal structure. I will show what kind of requirements this poses for natural evolutionary processes if they are to be computational.

Keywords

Physical computation Algorithmic process Evolution Algorithmic information theory Dennett Simulation 

References

  1. Ahouse, J. C. (1998). The Tragedy of a priori selectionism: Dennett and Gould on adaptationism. Biology and Philosophy, 13, 359–391.CrossRefGoogle Scholar
  2. Brandon, R. (1998). The Levels of selection: A hierarchy of interactors. In D. Hull & M. Ruse (Eds.), The philosophy of biology (pp. 176–197). Oxford: Oxford University Press.Google Scholar
  3. Chaitin, G. J. (1975). Randomness and mathematical proof. Scientific American, 232(5), 47–52.CrossRefGoogle Scholar
  4. Crutchfield, J. P. & Mitchell, M. (1995). The evolution of emergent computation. Proceedings of the National Academy of Sciences, USA 92: (23), 10742–10746.Google Scholar
  5. Cummins, R. (1975). Functional analysis. The Journal of Philosophy, 72(20), 741–765.CrossRefGoogle Scholar
  6. Dennett, D. (1995). Darwin’s dangerous idea: Evolution and the meanings of life. Nowy Jork: Simon & Schuster.Google Scholar
  7. Eigen, M. (1992). Steps toward life: A perspective on evolution. Oxford: Oxford University Press.Google Scholar
  8. Fodor, J. (1996). Deconstructing dennett’s Darwin. Mind and Language, 11(3), 246–262.CrossRefMathSciNetGoogle Scholar
  9. Gould, S. J. (1997). “Evolution: The pleasures of pluralism,” The New York Review of Books, (pp. 47–52).Google Scholar
  10. Grey, C. P., & Keck, W. (1999). Bacterial targets and antibiotics: Genome-based drug discovery. Cellular and Molecular Life Sciences, 56, 779–787.CrossRefGoogle Scholar
  11. Keane, A. J. & Petruzzelli, N. (2000). Aircraft wing design using GA-based multi-level strategies, in Proceedings of the 8th AIAA/USAF/NASSA/ISSMO Symposium on Multidisciplinary analysis and optimization, pp. A00-40171 AIAA-2000-4937, Long Beach, A.I.A.A.Google Scholar
  12. Krohs, U. (2004). Eine theorie biologischer theorien. Berlin: Springer.Google Scholar
  13. Mahner, M., & Bunge, M. (2001). Function and functionalism: A synthetic perspective. Philosophy of Science, 68(1), 75–94.CrossRefGoogle Scholar
  14. Mayr, E. (1997). This is biology. The science of the living world. Cambridge, USA: Belknap Press.Google Scholar
  15. Michalewicz, Z. (1996). Genetic algorithms + data structures = evolution programs. New York: Springer.MATHGoogle Scholar
  16. Miłkowski, M. (2007). Is computationalism trivial?, In G. Dodig-Crnkovic & S. Stuart (Eds.), Computation, information, cognition—the nexus and the liminal. (pp. 236–246). Cambridge Scholars Publishing.Google Scholar
  17. Millikan, R. G. (1984). Language thought, and other biological categories. New foundations for realism,. Cambridge, MA: MIT Press.Google Scholar
  18. Piccinini, G. (2007). Computational modelling vs. computational explanation. The Australasian Journal of Philosophy, 85(1), 93–115.CrossRefMathSciNetGoogle Scholar
  19. Putnam, H. (1987). Representation and reality. Cambridge, MA: MIT Press.Google Scholar
  20. Scheutz, M. (2001). Computational versus causal complexity. Minds and Machines, 11, 543–566.MATHCrossRefGoogle Scholar
  21. Scheutz, M. (2002). Philosophical issues about computation. In encyclopedia of cognitive science. London, UK: MacMillan.Google Scholar
  22. Searle, J. (1992). Rediscovery of mind. Cambridge (Mass): MIT Press.Google Scholar
  23. Wright, L. (1973). Functions. The Philosophical Review, 82(2), 139–168.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Institute of Philosophy and SociologyPolish Academy of SciencesWarsawPoland

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