Skip to main content

Perturbation of Equilibria in the Mathematical Theory of Evolution

  • Reference work entry
Encyclopedia of Complexity and Systems Science
  • 117 Accesses

Definition of the Subject

The importance of evolution can hardly be overstated. As the Jesuit priest Pierre Teilhard de Chardin put it,

Evolution is a general postulate to which all theories, all hypotheses, all systems must hence forward bow and which they mustsatisfy in order to be thinkable and true. Evolution is a light which illuminates all facts, a trajectory which all lines of thought mustfollow – this is what evolution is.

Darwin's evolution theory is based on three fundamental principles: reproduction, mutation and selection, which describe how populations change overtime and how new forms evolve out of old ones. Starting with W. F. R. Weldon, whom at the beginning of the 20th century realized that “the problemof animal evolution is essentially a statistical problem”, and blooming in the 30's with Fisher, Haldane and Wright, numerous mathematicaldescriptions of the resulting evolutionary dynamics have been proposed, developed and studied. Deeply engraved in these frameworks...

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

Access this chapter

Institutional subscriptions

Abbreviations

Evolutionarily stable equilibria (ESS):

An ESS is a set of frequencies of different types of individuals in a population that can not be invaded by the evolution of a single mutant. It is the evolutionary counterpart of a Nash equilibrium.

Fitness landscape:

A metaphorical description of fitness as a function of individual's genotypes or phenotypes in terms of a multivariable function that does not depend on any external influence.

Genetic locus:

The position of a gene on a chromosome. The different variants of the gene that can be found at the same locus are called alleles.

Nash equilibrium:

In classical game theory, a Nash equilibrium is a set of strategies, one for each player of the game, such that none of them can improve her benefits by unilateral changes of strategy.

Scale free network:

A graph or network such that the degrees of the nodes are taken from a power-law distribution. As a consequence, there is not a typical degree in the graph, i.?e., there are no typical scales.

Small-world network:

A graph or network of N nodes such that the mean distance between nodes scales as \( { \log N } \). It corresponds to the well-known “six degrees of separation” phenomenon.

Bibliography

Primary Literature

  1. Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512

    Google Scholar 

  2. Drossel B (2001) Biological evolution and statistical physics. Adv Phys 50:209–295

    ADS  Google Scholar 

  3. Fisher RA (1958) The Genetical Theory of Natural Selection, 2nd edn. Dover, New York

    Google Scholar 

  4. Gintis H (2000) Game Theory Evolving. Princeton University, Princeton

    MATH  Google Scholar 

  5. Hauert C (2002) Effects of space in \( { 2\times 2 } \) games. Int J Bifurc Chaos 12:1531–1548

    MathSciNet  MATH  Google Scholar 

  6. Hauert C, Doebeli M (2004) Spatial structure often inhibits the evolution of cooperation in the snowdrift game. Nature 428:643–646

    ADS  Google Scholar 

  7. Hendry AP, Kinnison MT (1999) The pace of modern life: Measuring rates of contemporary microevolution. Evolution 53:1637–1653

    Google Scholar 

  8. Hofbauer J, Sigmund K (1998) Evolutionary Games and Population Dynamics. Cambridge University, Cambridge

    MATH  Google Scholar 

  9. Hofbauer J, Sigmund K (2003) Evolutionary game dynamics. Bull Am Math Soc 40:479–519

    MathSciNet  MATH  Google Scholar 

  10. Kimura M (1983) The Neutral Theory of Molecular Evolution. Cambridge University, Cambridge

    Google Scholar 

  11. Maynard-Smith J (1982) Evolution and the Theory of Games. Cambridge University, Cambridge

    Google Scholar 

  12. Maynard-Smith J, Price GR (1973) The logic of animal conflict. Nature 246:15–18

    Google Scholar 

  13. Moran PAP (1962) The Statistical Processes of Evolutionary Theory. Clarendon, Oxford

    MATH  Google Scholar 

  14. Nash JF (1950) Equilibrium points in n-person games. Proc Natl Acad Sci USA 36:48–49

    MathSciNet  ADS  MATH  Google Scholar 

  15. Nowak MA (2006) Evolutionary Dynamics: Exploring the Equations of Life. Harvard Univ Press, Harvard

    Google Scholar 

  16. Nowak MA, May R (1992) Evolutionary games and spatial chaos. Nature 359:826–829

    ADS  Google Scholar 

  17. Nowak MA, Sasaki A, Taylor C, Fudenberg D (2004) Emergence of cooperation and evolutionary stability in finite populations. Nature 428:646–650

    ADS  Google Scholar 

  18. Page K, Nowak MA (2002) A unified evolutionary dynamics. J Theor Biol 219:93–98

    MathSciNet  Google Scholar 

  19. Roca CP, Cuesta JA, Sánchez A (2006) Time scales in evolutionary dynamics. Phys Rev Lett 97: art. no. 158701

    Google Scholar 

  20. Roca CP, Cuesta JA, Sánchez A (2007) The importance of selection rate in the evolution of cooperation. Eur Phys J Special Topics 143:51–58

    Google Scholar 

  21. Santos FC, Pacheco JM, Lenaerts T (2006) Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proc Natl Acad Sci USA 103:3490–3494

    ADS  Google Scholar 

  22. Skyrms B (2003) The Stag Hunt and the Evolution of Social Structure. Cambridge University, Cambridge

    Google Scholar 

  23. Szabó G, Fáth G (2007) Evolutionary games on graphs. Phys Rep 446:97–216

    Google Scholar 

  24. Sánchez A, Cuesta JA (2005) Altruism may arise by individual selection. J Theor Biol 235:233–240

    Google Scholar 

  25. Watts DJ, Strogatz SH (1998) Collective dynamics of “Small World” Networks. Nature 393:440–442

    ADS  Google Scholar 

  26. Wright S (1932) The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proc 6th Int Cong Genet 1:356–366

    Google Scholar 

Books and Reviews

  1. Nowak M, Sigmund K (2004) Evolutionary dynamics of biological games. Science 303:793–799

    ADS  Google Scholar 

  2. Taylor PD, Jonker L (1978) Evolutionarily stable strategies and game dynamics. J Math Biosci 40:145–156

    MathSciNet  MATH  Google Scholar 

  3. von Neumann J, Morgenstern O (1944) Theory of Games and Economic Behavior. Princeton University Press, Princeton

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag

About this entry

Cite this entry

Sánchez, A. (2009). Perturbation of Equilibria in the Mathematical Theory of Evolution. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_394

Download citation

Publish with us

Policies and ethics