Skip to main content
SpringerLink
Log in

Playing Games with Genetic Algorithms

  • Chapter
Evolutionary Computation in Economics and Finance

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 100))

Abstract

In 1987 the first published research appeared which used the Genetic Algorithm as a means of seeking better strategies in playing the repeated Prisoner’s Dilemma. Since then the application of Genetic Algorithms to game-theoretical models has been used in many ways. To seek better strategies in historical oligopolistic interactions, to model economic learning, and to explore the support of cooperation in repeated interactions. This brief survey summarises related work and publications over the past thirteen years. It includes discussions of the use of game-playing automata, co-evolution of strategies, adaptive learning, a comparison of evolutionary game theory and the Genetic Algorithm, the incorporation of historical data into evolutionary simulations, and the problems of economic simulations using real-world data.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alemdar N. M., Özyildirim S. (1998) A Genetic Game of Trade, Growth and Externalities. Journal of Economic Dynamics and Control 22(6), 811–32

    Article  MathSciNet  MATH  Google Scholar 

  2. Arifovic J. (1990) Learning by Genetic Algorithms in Economic Environments. Santa Fe Institute Econ. Res. Prog. Working Paper 90–001.

    Google Scholar 

  3. Arifovic J. (1994) Genetic Algorithm Learning and the Cobweb Model. Journal of Economic Dynamics and Control 18(1), 3–28

    Article  MATH  Google Scholar 

  4. Arifovic J. (1995) Genetic Algorithms and Inflationary Economies. Journal of Monetary Economies 36(1), 219–243

    Article  Google Scholar 

  5. Arifovic J. (1998) Stability of Equilibria Under Genetic Algorithm Adaptation: An Analysis. Macroeconomic Dynamics 2(1), 1–21

    MATH  Google Scholar 

  6. Arifovic J., Eaton B. C. (1995) Coordination via Genetic Learning. Computational Economies 8(3), 181–203

    Article  MATH  Google Scholar 

  7. Arifovic J., Eaton B. C. (1998) The Evolution of Type Communication in a Sender/Receiver Game of Common Interest with Cheap Talk. Journal of Economic Dynamics and Control 22(8–9), 1187–1207

    Article  MATH  Google Scholar 

  8. Ashlock D., Smucker M. D., Stanley E. A., Tesfatsion L. (1996) Preferential Partner Selection in an Evolutionary Study of Prisoner’s Dilemma. Bio Systems 37(1–2), 99–125

    Article  Google Scholar 

  9. Axelrod R. (1984) The Evolution of Cooperation. N. Y., Basic Books.

    Google Scholar 

  10. Axelrod R. (1987) The Evolution of Strategies in the Iterated Prisoner’s Dilemma. In: Davis L. (Ed.) Genetic Algorithms and Simulated Annealing, London: Pittman, 32–41

    Google Scholar 

  11. Axelrod R. (1997) The Complexity of Cooperation. Princeton: P. U. P.

    Google Scholar 

  12. Baar T., Oldser, G. J. (1982) Dynamic Non-Cooperative Game Theory. New York: Academic Press

    Google Scholar 

  13. Beckenbach F. (1999) Learning by Genetic Algorithms in Economies? In: Brenner (1999) op. cit., 73–100

    Google Scholar 

  14. Binmore K., Dasgupta P. (1986) Game Theory: A Survey. In: Binmore K., and Dasgupta P. (Eds.) Economic Organizations as Games, Oxford: B. Blackwell, 1–45

    Google Scholar 

  15. Birchenhall C. R. (1996) Evolutionary Games and Genetic Algorithms. In: Gilli M. (Ed.) Computational Economic Systems: Models, Methods & Econometrics, The series Advances in Computational Economics 5, Dordrecht: Kluwer Academic Publishers, 3–23

    Google Scholar 

  16. Brenner T. (Ed.) (1999) Computational Techniques for Modelling Learning in Economics, in the series Advances in Computational Economics 11, Dordrecht: Kluwer Academic Publishers

    Google Scholar 

  17. Bullard J., Duffy J. (1998) Learning and the Stability of Cycles. Macroeconomic Dynamics 2(1), 22–48

    MATH  Google Scholar 

  18. Bullard J., Duffy J. (1999) Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs. Computational Economics 13(1), 41–60

    Article  MATH  Google Scholar 

  19. Cacho O., Simmons P. (1999) A Genetic Algorithm Approach to Farm Investment. Australian Journal of Agricultural and Resource Economics, 43(3), 305–322

    Article  Google Scholar 

  20. Chen S.-H., Duffy J., Yeh C. H. (1996) Equilibrium Selection via Adaptation: Using Genetic Programming to Model Learning in a Co-ordination Game, mimeo.

    Google Scholar 

  21. Chen S. -H., Ni C. -C. (1997) Coevolutionary Instability in Games: An Analysis Based on Genetic Algorithms. In: Proceedings of 1997 IEEE International Conference on Evolutionary Computation, Piscataway, N.J.: Institute of Electrical and Electronics Engineers, 703–708

    Google Scholar 

  22. Chen S. -H., Ni C. -C. (2000) Simulating the Ecology of Oligopolistic Competition with Genetic Algorithms, Knowledge and Information Systems, forthcoming.

    Google Scholar 

  23. Chess D. M. (1988) Simulating the Evolution of Behavior: The Iterated Prisoners’ Dilemma, Complex Systems 2, 663–670

    MathSciNet  Google Scholar 

  24. Cho I. -K. (1995) Perceptrons Play the Repeated Prisoner’s Dilemma, Journal of Economic Theory 67, 266–284

    Article  MathSciNet  MATH  Google Scholar 

  25. Cho I. -K. (1996a) On the Complexity of Repeated Principal Agent Games. Economic Theory 7(1), 1–17

    Article  MATH  Google Scholar 

  26. Cho I. -K. (1996b) Perceptrons Play Repeated Games with Imperfect Monitoring. Games and Economic Behavior 16(1), 22–53

    Article  MathSciNet  MATH  Google Scholar 

  27. Cho I. -K., Li H. (1999) How Complex are Networks Playing Repeated Games? Economic Theory 13(1), 93–123

    Article  MathSciNet  MATH  Google Scholar 

  28. Curzon Price T. (1997) Using Co-evolutionary Programming to Simulate Strategie Behaviour in Markets. Journal of Evolutionary Economics 7(3), 219–254

    Article  Google Scholar 

  29. Dawid H. (1996a) Genetic Algorithms as a Model of Adaptive Learning in Economic Systems. Central European Journal for Operations Research and Economics 4(1), 7–23

    MATH  Google Scholar 

  30. Dawid H. (1996b) Learning of Cycles and Sunspot Equilibria by Genetic Algorithms. Journal of Evolutionary Economics 6(4), 361–373

    Article  MathSciNet  Google Scholar 

  31. Dawid H. (1999) Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models. Lecture Notes in Economics and Mathematical Systems, Vol 441. Heidelberg: Springer-Verlag, 2nd ed.

    Book  MATH  Google Scholar 

  32. Dawid H., Kopel M. (1998) On Economic Applications of the Genetic Algorithm: A Model of the Cobweb Type. Journal of Evolutionary Economics 8(3), 297–315

    Article  Google Scholar 

  33. Dawid H., Mehlmann A. (1996) Genetic Learning in Strategie Form Games. Complexity 1(5), 51–59

    Article  MathSciNet  Google Scholar 

  34. Fader P. S., Hauser J. R. (1988) Implicit Coalitions in a Generalised Prisoner’s Dilemma, Journal of Conflict Resolution 32, 553–582

    Article  Google Scholar 

  35. Fogel D. B., Harrald P. G. (1994) Evolving Continuous Behaviors in the Iterated Prisoner’s Dilemma. In: Sebald A., Fogel L. (Eds.) The Third Annual Conference on Evolutionary Programming, Singapore: World Scientific, 119–130

    Google Scholar 

  36. Forrest S. (Ed.) (1991), Emergent Computation: Self-Organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks, Cambridge: M.I.T. Press.

    Google Scholar 

  37. Franke R. (1998) Coevolution and Stable Adjustments in the Cobweb Model. Journal of Evolutionary Economics 8(4), 383–406

    Article  MathSciNet  Google Scholar 

  38. Friedman D. (1991) Evolutionary Games in Economics. Econometrica 59(3), 637–666

    Article  MathSciNet  MATH  Google Scholar 

  39. Fudenberg D., Levine D. K. (1998) The Theory of Learning in Games. Cambridge: M.I.T. Press

    MATH  Google Scholar 

  40. Fudenberg D., Tirole J. (1991) Game Theory. Cambridge: M.I.T. Press

    Google Scholar 

  41. Fujiki C, Dickinson J. (1987) Using the Genetic Algorithm to Generate Lisp Source Code to Solve the Prisoner’s Dilemma. In: Grefenstette J. J. (Ed.) Genetic Algorithms and their Applications. Proceedings of the 2nd. International Conference on Genetic Algorithms. Hillsdale, N. J.: Lawrence Erlbaum

    Google Scholar 

  42. Goldberg D. E. (1988) Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, Mass.: Addison-Wesley

    Google Scholar 

  43. Herbrich R., Keilbach M., Graepel T., Bollmann-Sdorra P., Obermayer K. (1999) Neural networks in economics. In: Brenner (1999), op. cit., 169–196

    Google Scholar 

  44. Ho T. H. (1996) Finite Automata Play Repeated Prisoner’s Dilemma with Information Processing Costs. Journal of Economic Dynamics and Control 20(1–3), 173–207

    Article  MathSciNet  Google Scholar 

  45. Hofbauer J., Sigmund C. (1988) The Theory of Evolution and Dynamic Systems. Cambridge: C. U. P.

    Google Scholar 

  46. Hofbauer J., Sigmund C. (1998) Evolutionary Games and Population Dynamics, Cambridge: C. U. P.

    Book  MATH  Google Scholar 

  47. Holland J. H. (1975) Adaptation in Natural and Artificial Systems. Ann Arbor: Univ. of Michigan Press. (A second edition was published in 1992: Cambridge: M.I.T. Press.)

    Google Scholar 

  48. Holland J. H. (1992) Genetic Algorithms. Scientific American July, 66–72

    Google Scholar 

  49. Holland J. H., Holyoak K. J., Nisbett R. E., Thagard P. R. (1986) Induction: Processes of Inference, Learning, and Discovery, Cambridge: M.I.T. Press.

    Google Scholar 

  50. Holland J. H., Miller J. H. (1991) Artificial Adaptive Agents in Economic Theory. American Economic Review: Papers and Proceedings 81(2), 365–370

    Google Scholar 

  51. Huck S., Müller W., Strobel M. (1999) On the Emergence of Attitudes Towards Risk. In: Brenner (1999), op. cit., 123–144

    Google Scholar 

  52. Jung Y. J., Kagel J. H., Levin D. (1994) On the Existence of Predatory Pricing: An Experimental Study of Reputation and Entry Deterrence in the Chain-store Game. Rand Journal of Economics 25(1), 72–93

    Article  Google Scholar 

  53. Judd K. L. (1998) Numerical Methods in Economics, Cambridge: M.I.T. Press

    MATH  Google Scholar 

  54. Lindgren K. (1991) Evolutionary Phenomena in Simple Dynamics. In: Langton C, Taylor C, Farmer J., Rasmussen S., (Eds.), Artificial Life II, Vol. 10, Reading: Addison-Wesley, 295–324

    Google Scholar 

  55. Mailath G. J. (1998) Do People Play Nash Equilibrium? Lessons from Evolutionary Game Theory. Journal of Economic Literature 36(3), 1347–74

    Google Scholar 

  56. Marimon R., McGrattan E., Sargent T. J. (1990) Money as a Medium of Exchange in an Economy with Artificially Intelligent Agents. Journal of Economic Dynamics and Control 14, 329–373

    Article  MathSciNet  MATH  Google Scholar 

  57. Marks, R. E. (1989a) Niche Strategies: The Prisoner’s Dilemma Computer Tournaments Revisited. AGSM Working Paper 89–009. http://www.agsm.edu.au/~bobm/papers/niche.pdf

    Google Scholar 

  58. Marks R. E. (1989b). Breeding Optimal Strategies: Optimal Behavior for Oligopolists. In: Schaffer J. David (Ed.), Proceedings of the Third International Conference on Genetic Algorithms, San Mateo, CA.: Morgan Kaufmann, 198–207

    Google Scholar 

  59. Marks R. E. (1992a) Repeated Games and Finite Automata. In: Creedy J., Borland J., Eichberger J. (Eds.) Recent Developments in Game Theory. Aldershot: Edward Elgar, 43–64

    Google Scholar 

  60. Marks R. E. (1992b) Breeding Hybrid Strategies: Optimal Behaviour for Oligopolists. Journal of Evolutionary Economics, 2, 17–38

    Article  Google Scholar 

  61. Marks R. E. (1998) Evolved Perception and Behaviour in Oligopolies. Journal of Economic Dynamics and Control 22(8–9), 1209–1233

    Article  MATH  Google Scholar 

  62. Marks R. E., Midgley D. F., Cooper L. G. (1995) Adaptive Behavior in an Oligopoly. In: Biethahn J., Nissen V. (Eds.) Evolutionary Algorithms in Management Applications, Berlin: Springer-Verlag, 225–239

    Chapter  Google Scholar 

  63. Marks R. E., Midgley D. F., Cooper L. G. (1998) Refining the Breeding of Hybrid Strategies. Australian Graduate School of Management Working Paper 98–017, Sydney. <http: //www. agsm. edu. au/~bobm/papers/wp98017. html>

    Google Scholar 

  64. Marks R. E., Midgley D. F., Cooper L. G. (2000) Breeding Better Strategies in Oligopolistic Price Wars. Submitted to the IEEE Transactions on Evolutionary Computation, special issue on Agent-Based Modelling of Evolutionary Economic Systems, INSEAD Working Paper 2000/65/MKT, <http://www.agsm.edu.au/~bobm/papers/ieee-marks.html>

    Google Scholar 

  65. Marks R. E., Schnabl H. (1999) Genetic Algorithms and Neural Networks: A Comparison Based on the Repeated Prisoner’s Dilemma. In: Brenner (1999), op. cit., 197–219

    Google Scholar 

  66. Maynard Smith J. (1982) Evolution and the Theory of Games. Cambridge: C. U. P.

    Book  MATH  Google Scholar 

  67. Megiddo N., Wigderson, A. (1986) On Play by Means of Computing Machines. In: Halpern J. Y. (Ed.) Reasoning About Knowledge, Los Altos: Kaufmann, 259–274

    Google Scholar 

  68. Midgley D. F., Marks R. E., Cooper L. G. (1997) Breeding Competitive Strategies. Management Science 43(3), 257–275

    Article  MATH  Google Scholar 

  69. Miller J. H. (1996) The Coevolution of Automata in the Repeated Prisoner’s Dilemma. Journal of Economic Behavior and Organization 29, 87–112

    Article  Google Scholar 

  70. Mitchell M. (1996) An Introduction to Genetic Algorithms. Cambridge: M.I.T. Press

    Google Scholar 

  71. Nachbar J. H. (1988) The Evolution of Cooperation Revisited. mimeo, Santa Monica: RAND Corp., June.

    Google Scholar 

  72. Nachbar J. H. (1992) Evolution in the Finitely Repeated Prisoner’s Dilemma, Journal of Economic Behavior and Organization 19(3), 307–326

    Article  Google Scholar 

  73. Nelson R. R., Winter S. G. (1982) An Evolutionary Theory of Economic Change. Cambridge: Belknap Press of Harvard University Press

    Google Scholar 

  74. Ozyildirim S. (1997) Computing Open-loop Noncooperative Solution in Discrete Dynamic Games. Journal of Evolutionary Economics 7(1), 23–40

    Article  Google Scholar 

  75. Riechmann T. (1999) Learning and Behavioural Stability: An Economic Interpretation of Genetic Algorithms. Journal of Evolutionary Economics 9(2), 225–242

    Article  Google Scholar 

  76. Riechmann T. (2001) Genetic Algorithm Learning and Evolutionary Games, in this volume.

    Google Scholar 

  77. Rubinstein A. (1986) Finite Automata Play the Repeated Prisoner’s Dilemma. Journal of Economic Theory, 39, 83–96

    Article  MathSciNet  MATH  Google Scholar 

  78. Rubinstein A. (1998) Modeling Bounded Rationality. Cambridge: M.I.T. Press

    Google Scholar 

  79. Sargent T. J. (1993) Bounded Rationality in Macroeconomics. Oxford: O. U. P.

    Google Scholar 

  80. Selten R. (1978) The Chain Store Paradox. Theory and Decision 9, 127–59

    Article  MathSciNet  MATH  Google Scholar 

  81. Selten R. (1991) Evolution, Learning, and Economic Behavior. Games and Economic Behavior 3, 3–24

    Article  MATH  Google Scholar 

  82. Slade M. E. (1992) Vancouver’s Gasoline-price Wars: An Empirical Exercise in Uncovering Supergame Strategies. Review of Economic Studies 59, 257–274

    Article  MATH  Google Scholar 

  83. Slade M. E. (1995) Empirical Games: The Oligopoly Case. Canadian Journal of Economics 28(2), 368–402

    Article  Google Scholar 

  84. Slade M. E., Eaton B. C. (1990) Evolutionary Equilibrium in Market Supergames. University of British Columbia Department of Economics Discussion Paper: 90–30.

    Google Scholar 

  85. Stanley E. A., Ashlock D., Tesfatsion L. (1994) Iterated Prisoner’s Dilemma with Choice and Refusal of Partners. In: Langton C. (Ed.) Artificial Life III, Vol. 17, Santa Fe Institute Studies in the Sciences of Complexity, Redwood City: Addison-Wesley, 131–175

    Google Scholar 

  86. Szpiro G. (1997) The Emergence of Risk Aversion. Complexity 2, 31–39

    Article  MathSciNet  Google Scholar 

  87. Tesfatsion L. (1997) A Trade Network Game with Endogenous Partner Selection. In: Amman H. M., Rüstern B., Whinston A. B. (Eds.) Computational Approaches to Economic Problems, Dordrecht: Kluwer Academic Publishers, 249–269

    Chapter  Google Scholar 

  88. Vallee T., Baar T. (1999) Off-line Computation of Stackeiberg Solutions with the Genetic Algorithm. Computational Economics 13(3), 201–209

    Article  MATH  Google Scholar 

  89. Weibull J. W. (1995) Evolutionary Game Theory, Cambridge: M.I.T. Press

    MATH  Google Scholar 

  90. Wu J., Axelrod R. (1995) How to Cope with Noise in the Iterated Prisoner’s Dilemma, Journal of Conflict Resolution 39(1), 183–189

    Article  Google Scholar 

  91. Yao X., Darwen P. J. (1994) An Experimental Study of n-person Iterated Prisoner’s Dilemma Games. Informatica 18, 435–450

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Australian Graduate School of Management, Universities of Sydney and New South Wales, Sydney, 2052, Australia

    Robert E. Marks

Authors
  1. Robert E. Marks
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. AI-ECON Research Center, Department of Economics, National Chengchi University, 11623, Taipei, Taiwan, R. O. China

    Shu-Heng Chen

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Marks, R.E. (2002). Playing Games with Genetic Algorithms. In: Chen, SH. (eds) Evolutionary Computation in Economics and Finance. Studies in Fuzziness and Soft Computing, vol 100. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1784-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-7908-1784-3_2

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2512-1

  • Online ISBN: 978-3-7908-1784-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation