Arbeitspapier
Genetic Algorithms and Economic Evolution
This paper tries to connect the theory of genetic algorithm (GA) learning to evolutionary game theory. It is shown that economic learning via genetic algorithms can be described as a specific form of evolutionary game. It will be pointed out that GA learning results in a series of near Nash equilibria which during the learning process build up to finally reach a neighborhood of an evolutionarily stable state. In order to clarify this point, a concept of evolutionary stability of genetic populations will be developed. Thus, in a second part of the paper it becomes possible to explain both, the reasons for the specific dynamics of standard GA learning models and the different kind of dynamics of GA learning models, which use extensions to the standard GA.
- Sprache
-
Englisch
- Erschienen in
-
Series: Diskussionsbeitrag ; No. 219
- Klassifikation
-
Wirtschaft
Computational Techniques; Simulation Modeling
Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- Thema
-
learning
computational economics
genetic algorithms
evolutionary dynamics
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Riechmann, Thomas
- Ereignis
-
Veröffentlichung
- (wer)
-
Universität Hannover, Wirtschaftswissenschaftliche Fakultät
- (wo)
-
Hannover
- (wann)
-
1998
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Riechmann, Thomas
- Universität Hannover, Wirtschaftswissenschaftliche Fakultät
Entstanden
- 1998
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