Genetic Learning in Stategic Form Games

Dawid H, Mehlmann A (1996)
Complexity 1(5): 51-59.

Zeitschriftenaufsatz | Veröffentlicht| Englisch
 
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Autor/in
Dawid, HerbertUniBi; Mehlmann, Alexander
Abstract / Bemerkung
We analyze the learning behavior of a Simple Genetic Algorithm in symmetric 3 × 3 Strategic-Form-Games. In cases of contests within one population and also between two populations the behavior of the SGA is compared with the behavior of the replicator dynamics and is analyzed with respect to equilibrium concepts in evolutionary game theory. Furthermore conservative non-adaptive strings are added to the population which lead to convergence to an equilibrium even in “GA-deceptive” games where the equilibrium can not be reached by GAs using only selection and crossover.
Stichworte
agent-based modelling; etace_agent_based_modelling
Erscheinungsjahr
1996
Zeitschriftentitel
Complexity
Band
1
Ausgabe
5
Seite(n)
51-59
ISSN
1076-2787
Page URI
https://pub.uni-bielefeld.de/record/2637718

Zitieren

Dawid H, Mehlmann A. Genetic Learning in Stategic Form Games. Complexity. 1996;1(5):51-59.
Dawid, H., & Mehlmann, A. (1996). Genetic Learning in Stategic Form Games. Complexity, 1(5), 51-59. doi:10.1002/cplx.6130010513
Dawid, H., and Mehlmann, A. (1996). Genetic Learning in Stategic Form Games. Complexity 1, 51-59.
Dawid, H., & Mehlmann, A., 1996. Genetic Learning in Stategic Form Games. Complexity, 1(5), p 51-59.
H. Dawid and A. Mehlmann, “Genetic Learning in Stategic Form Games”, Complexity, vol. 1, 1996, pp. 51-59.
Dawid, H., Mehlmann, A.: Genetic Learning in Stategic Form Games. Complexity. 1, 51-59 (1996).
Dawid, Herbert, and Mehlmann, Alexander. “Genetic Learning in Stategic Form Games”. Complexity 1.5 (1996): 51-59.

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