Biology and Philosophy

, Volume 20, Issue 5, pp 951–966 | Cite as

Maynard Smith, optimization, and evolution

Article

Abstract

Maynard Smith’s defenses of adaptationism and of the value of optimization theory in evolutionary biology are both criticized. His defense does not adequately respond to the criticism of adaptationism by Gould and Lewontin. It is also argued here that natural selection cannot be interpreted as an optimization process if the objective function to be optimized is either (i) interpretable as a fitness, or (ii) correlated with the mean population fitness. This result holds even if fitnesses are frequency-independent; the problem is further exacerbated in the frequency-dependent context modeled by evolutionary game theory. However, Eshel and Feldman’s new results on “long-term” evolution may provide some hope for the continuing relevance of the game-theoretic framework. These arguments also demonstrate the irrelevance of attempts by Intelligent Design creationists to use computational limits on optimization algorithms as evidence against evolutionary theory. It is pointed out that adaptation, natural selection, and optimization are not equivalent processes in the context of biological evolution.

Keywords

Adaptation Evolution Frequency-dependence Natural selection No free lunch theorems Optimization 

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References

  1. Bishop D.T. and Cannings C. (1978). A generalized war of attrition. J. Theor. Biol. 70: 85–124CrossRefPubMedGoogle Scholar
  2. Behera N. (1996). Variational principles in evolution. Bull. Math. Biol. 58: 175–202CrossRefPubMedGoogle Scholar
  3. Crow J.F. and Kimura M. (1970). An Introduction to Population Genetics Theory. Minneapolis, BurgessGoogle Scholar
  4. Dawkins R. (1996). Climbing Mount Improbable. London, Viking/PenguinGoogle Scholar
  5. de Jong K. (1993). Genetic algorithms are NOT function optimizers. In: Whitley L.D., (eds). Foundations of Genetic Algorithms. San Mateo, CA, Morgan Kaufmann, pp. 5–17Google Scholar
  6. Dembski W.A. (2002). No Free Lunch: Why Specified Complexity Cannot be Purchased without Intelligence. Lanham, MD, Rowman and LittlefieldGoogle Scholar
  7. Eshel I. and Feldman M.W. (2001). Optimality and evolutionary stability under short-term and long-term selection. In: Orzack S.H. and Sober E. (eds), Adaptationism and Optimality. Cambridge UK, Cambridge University Press, pp. 161–190Google Scholar
  8. Ewens W.J.(1969). With additive fitness, the mean fitness increases. Nature 221: 1076CrossRefGoogle Scholar
  9. Ewens W.J. (1989). An interpretation and proof of the fundamental theorem of natural selection. Theor. Popul. Biol. 36: 167–180CrossRefPubMedGoogle Scholar
  10. Ewens W.J. (1992). An optimizing principle of natural selection in evolutionary population genetics. Theor. Popul. Biol. 42: 333–346CrossRefPubMedGoogle Scholar
  11. Fisher R.A. (1930). The Genetical Theory of Natural Selection. Oxford, Clarendon PressGoogle Scholar
  12. Forster M.R. 1999. Notice: No Free Lunches for Anyone, Bayesians Included. <http://www.no-free-lunch.org/Fors99.pdf>. Accessed: 14 February 2005
  13. Godfrey-Smith P. (2001). Three kinds of adaptationism. In: Orzack S.H. and Sober E. (eds). Adaptationism and Optimality. Cambridge, UK, Cambridge University Press, pp. 335–357Google Scholar
  14. Gould S.J. and Lewontin R.C. (1979). The Spandrels of San Marco and the Panglossian paradigm. Proc. R. Soc. Lond. B 205: 581–598PubMedCrossRefGoogle Scholar
  15. Haldane J.B.S. (1928). Possible Worlds and Other Papers. New York, HarperGoogle Scholar
  16. Holland J. (1975). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Ann Arbor, University of Michigan PressGoogle Scholar
  17. Karlin S. (1975). General two locus selection models: some objectives, rules and interpretations. Theor. Popul. Biol. 7: 364–398CrossRefPubMedGoogle Scholar
  18. Lanczos C. (1959). The Variational Principles of Mechanics. Toronto, University of Toronto PressGoogle Scholar
  19. Lewontin R.C. (1961). Evolution and the theory of games. J. Theor. Biol. 1: 383–403CrossRefGoogle Scholar
  20. Lewontin R.C. (1974). The Genetic Basis of Evolutionary Change. New York, Columbia University PressGoogle Scholar
  21. Lewontin R.C.(1977). “Adaptation”. Encyclopedia Einaudi Turin 1: 198 –214Google Scholar
  22. Lewontin R.C. (1978). Adaptation. Sci. Am. 239: 212–230PubMedCrossRefGoogle Scholar
  23. Lewontin R.C. (1979). Fitness, survival, and optimality. In: Horn D.J., Mitchell R. and Stairs G.R. (eds) Analysis of Ecological Systems. Columbus, Ohio State University Press, pp. 3–21Google Scholar
  24. Lewontin R.C. (1991). Facts and the factitious in natural sciences. Crit. Inq. 18: 140–153CrossRefGoogle Scholar
  25. Maynard Smith J. (1978). Optimization theory in evolution. Annu. Rev. Ecol. Syst. 9: 31–56CrossRefGoogle Scholar
  26. Maynard Smith J. (1982). Evolution and the Theory of Games. Cambridge, UK, Cambridge University PressGoogle Scholar
  27. Maynard Smith J. and Szathmáry E. (1995). The Major Transitions in Evolution. Oxford, Oxford University PressGoogle Scholar
  28. Mayr E. (1983). How to carry out the adaptationist program. Am. Nat. 121: 324–334CrossRefGoogle Scholar
  29. Michod R.E. (1999). Darwinian Dynamics: Evolutionary Transitions in Fitness and Individuality. Princeton, Princeton University PressGoogle Scholar
  30. Moran P.A.P. (1964). On the nonexistence of adaptive topographies. Ann. Hum. Genet. 27: 383–393PubMedCrossRefGoogle Scholar
  31. Parker G.A. and Maynard Smith J.(1990). Optimality theory in evolutionary biology. Nature 348: 27–33CrossRefGoogle Scholar
  32. Perakh M. 2003. The No Free Lunch Theorems and Their Applications to Evolutionary Algorithms. <http://www.nctimes.net/∼ ∼mark/bibl_science/orr_demb_NFL.htm>. Accessed: 13 February 2005.
  33. Perakh M. (2004). Why there is a free lunch after all: William Dembski’s wrong answer to irrelevant questions. In: Young M. and Edis T. (eds) Why Intelligent Design Fails: A Scientific Critique of the New Creationism. New Brunswick, Rutgers University Press, pp. 153–171Google Scholar
  34. Quenette P.-Y. and Gerard J.-F. (1992). Does frequency-dependent selection optimize fitness?. J. Theor. Biol. 159: 381–385PubMedCrossRefGoogle Scholar
  35. Reeve H.K. and Sherman P.W. 1999. Adaptations: Meanings. In: Nature Encyclopedia of Life Sciences. John Wiley, Chichester. http://www.els.net/ [doi:10.1038/npg.els.0001707].
  36. Scheuer P.A.G. and Mandel S.P.H. (1959). An inequality in population genetics. Heredity 31: 519–524Google Scholar
  37. Svirezhev Y.M. (1972). Optimum principles in population genetics. In: Ratner V.A. (ed) Studies on Theoretical Genetics. Novosibirsk, USSR Academy of Science, pp. 86–102Google Scholar
  38. Shahshahani S. 1979. A new mathematical framework for the study of linkage and selection. Memoirs Am. Math. Soc. 17: 211Google Scholar
  39. Wolpert D.H. and Macready W.G. (1997). No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1: 67–82CrossRefGoogle Scholar
  40. Wright S. (1932). The roles of mutation, inbreeding, crossbreeding and selection in evolution. In: Jones D.F., (ed), Proceedings of the Sixth International Congress of Genetics. I. Monisha, WI, Brooklyn Botanic Garden, pp. 356–366Google Scholar
  41. Wright S. (1967). Surfaces’ of selective value. Proc. Natl. Acad. Sci. USA 58: 165–172PubMedCrossRefGoogle Scholar
  42. Zeeman E.C. (1981). Dynamics of the evolution of animal conflicts. J. Theor. Biol. 89: 249–270CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of Philosophy, and Section of Integrative BiologyUniversity of Texas at AustinAustinUSA

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