Hostname: page-component-84b7d79bbc-2l2gl Total loading time: 0 Render date: 2024-08-04T17:20:19.042Z Has data issue: false hasContentIssue false

Chaos and the Explanatory Significance of Equilibrium: Strange Attractors in Evoluhonary Game Dynamics

Published online by Cambridge University Press:  19 June 2023

Brian Skyrms*
Affiliation:
University of California—Irvine

Extract

The classical game theory ofvon Neumann and Morgenstern (1947) is built on the concept of equilibrium. I will begin this essay with two more or Jess controversial philosophical claims regarding that equilibrium concept:

  1. (1) The explanatory significance of the equilibrium concept depends on the underlying dynamics.

  2. (2) When the underlying dynamics is taken seriously, it becomes apparent that equilibrium is not the central explanatory concept.

Type
Part XI. The Dynamics of Rational Deliberation
Copyright
Copyright © 1993 by the Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

1

The existence of this strange attractor together with a preliminary study of the route to chaos involved was first reported in Skynns (1992a). This paper contains further experimental results. I would like to thank the University of California at lrvine for support in the form of computing time and Linda Palmer for implementing and running programs to determine the Liapunov spectrum. I would also like to thank Immanuel Bomze, Vincent Crawford, William Harper and Richard Jeffrey for comments on an earlier version of this paper.

References

Ameodo, A., Coullet, P. and Tresser, C. (1980), “Occurrence of Strange Attractors in Three Dimensional Volterra Equations”, Physics Letters 79: 259-263.Google Scholar
Ameodo, A., Coullet, P., Peyraud, J. and Tresser, C. (1982), “Strange Attractors in Volterra Equations for Species in Competition”, Journal of Mathematical Biology 14: 153-157.Google Scholar
Bomze, I. M. (1986), “Non-cooperative 2-person Games in Biology: a Classification”, International Journal of Game Theory 15: 31-59.CrossRefGoogle Scholar
Brown, G. W. (1951), “Iterative Solutions of Games by Fictitious Play”, in Activity Analysis of Production and Allocation (Cowles Commission Monograph) New York: Wiley, pp. 374-376.Google Scholar
Coumot, A. (1897), Researches into the Mathematical Principles of the Theory of Wealth (tr. from the French ed. of 1838) New York : Macmillan.Google Scholar
van Damme, E. (1987), Stability and Perfection of Nash Equilibria Berlin : Springer.CrossRefGoogle Scholar
Eckmann, J. P. and Ruelle, D. (1985), “Ergodic Theory of Chaos and Strange Attractors”, Reviews of Modern Physics 57: 617-656.CrossRefGoogle Scholar
Gardini, L., Lupini, R., and Messia, M. G. (1989), “Hopf Bifurcation and Transition to Chaos in Lotka-Volterra equation”, Mathematical Biolog y 27: 259-272.CrossRefGoogle Scholar
Gilpin, M. E. (1979), “Spiral Chaos in a Predator-Prey Model”, The American Naturalist 13: 306-308.CrossRefGoogle Scholar
Guckenheimer, J. and Holmes, P. (1986), Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields (Corrected second printing) Berlin: Springer.Google Scholar
Hirsch, M. W. and Smale, S. (1974), Differential Equations, Dynamical Systems and Linear Algebra New York: Academic Press.Google Scholar
Hofbauer, J. (1981), “On the Occurrence of Limit Cycles in the Volterra-Lotka Equation”, Nonlinear Analysis 5: 1003-1007.CrossRefGoogle Scholar
Hofbauer, J. and Sigmund, K. (1988), The Theory of Evolution and Dynamical Systems Cambridge: Cambridge University Press.Google Scholar
May, R. M. and Leonard, W. L. (1975), “Nonlinear Aspects of Competition between Three Species”, SIAM Journal of Applied Mathematics 29: 243-253.CrossRefGoogle Scholar
Maynard Smith, J. (1982), Evolution and the Theory of Games Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Maynard Smith, J. and Price, G. R. (1973), “The Logic of Animal Conflict”, Nature 146: 15-18.CrossRefGoogle Scholar
Nachbar, J. H.(1990), “‘Evolutionary’ Selection Dynamics in Games: Convergence and Limit Properties”, International Journal of Game Theory 19: 59-89.CrossRefGoogle Scholar
Press, J., Flannery, B., Teukolsky, S. ,and Vetterling, W. (1989), Numerical Recipes: The Art of Scientific Computing rev. ed. Cambridge: Cambridge University Press.Google Scholar
Rand, D. (1978), “Exotic Phenomena in Games and Duopoly Models”, Journal of Mathematical Economics 5: 173-184.CrossRefGoogle Scholar
Rössler, O. (1976), “Different Types of Chaos in Two Simple Differential Equations”, Zeitschrift fur Naturforschung 31a: 1664-1670.CrossRefGoogle Scholar
Selten, R. (1975), “Reexamination of the perfectness concept of equilibrium in extend sive games”, International Journal of Game Theory 4: 25-55.CrossRefGoogle Scholar
Shaffer, W. M. (1985), “Order and Chaos in Ecological Systems”, Ecology 66: 93-106.CrossRefGoogle Scholar
Shaffer, W. M. and Kot, M. (1986), “Differential Systems in Ecology and Epidemiology”, in Chaos: An Introduction ed. A. V. Holden. Manchester : University of Manchester Press, pp. 158-178.CrossRefGoogle Scholar
Skynns, B. (1988), “Deliberational Dynamics and the Foundations of Bayesian Game Theory”, in J.E.Tomberlin (ed.) Epistemology [Philosophical Perspectives v.2] Northridge: Ridgeview, pp. 345-367.Google Scholar
Skynns, B. (1989), “Correlated Equilibria and the Dynamics of Rational Deliberation”, Erkenntnis 31: 347-364.Google Scholar
Skynns, B. (1990), The Dynamics of Rational Deliberation Cambridge, Mass: Harvard University Press.Google Scholar
Skynns, B.(1991), “Inductive Deliberation, Admissible Acts and Perfect Equilibrium”, in M. Bacharach and S. Hurley (eds.) Foundations of Decision Theory Oxford: Blackwells, pp. 220-241.Google Scholar
Skynns, B. (1992a), “Chaos in Game Dynamics”, Journal of Logic, Language and Information 1: 111-130.CrossRefGoogle Scholar
Skynns, B. (1992b), “Adaptive and Inductive Inductive Deliberational Dynamics”, in P. Bourgine and B. Walliser (eds.) Economics and Cognitive Science Pergamon Press: Oxford, pp. 93-107.CrossRefGoogle Scholar
Smale, S. (1976), “On the Differential Equations of Species in Competition”, Journal of Mathematical Biology 3, 5-7.CrossRefGoogle Scholar
Takeuchi, Y. and Adachi, N. (1984), “Influence of Predation on Species Coexistence in Volterra Models”, Mathematical Biosciences 70: 65-90.CrossRefGoogle Scholar
Taylor, P. and Jonker, L. (1978), “Evolutionarily Stable Strategies and Game Dynamics”, Mathematical Biosciences 40, 145-156.CrossRefGoogle Scholar
Vance, R. R. (1978), “Predation and Resource Partitioning in a one-predator-two prey model community”, American Naturalist 112: 441-448.CrossRefGoogle Scholar
Vandermeer, J. (1991), “Contributions to the Global Analysis of 3-D Lotka-Volterra Equations: Dynamic Boundedness and Indirect Interactions in the Case of One Predator and Two Prey”, Journal of Theoretical Biology 148: 545-561.CrossRefGoogle Scholar
von Neumann, J. and Morgenstern, O. (1947), Theory of Games and Economic Behavior Princeton: Princeton University Press.Google Scholar
Wolf, A., Swift, L.B., Swinney, H.L. and Vastano, J. A.(1985), “Determining Lyaponov Exponents from a Time Series”, Physica 16-D: 285-317.CrossRefGoogle Scholar
Wolfram, S. (1991), Mathematica 2nd. ed. New York: Addison Wesley.Google Scholar
Zeeman, E. C. (1980), “Population Dynamics from Game Theory”, in Z. Niteck and C. Robinson (eds.) Global Theory of Dynamical Systems (Lecture Notes in Mathematics (819) Berlin: Springer Verlag, pp. 471-497.CrossRefGoogle Scholar