Genetic algorithm learning and evolutionary games

@inproceedings{Riechmann2001GeneticAL,
  title={Genetic algorithm learning and evolutionary games},
  author={Thomas Riechmann},
  year={2001}
}
This paper links 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 speci"c form of an 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 "nally approach a neighborhood of an evolutionarily stable state. In order to characterize this kind of dynamics, a concept of evolutionary superiority and… CONTINUE READING
Highly Cited
This paper has 67 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 44 extracted citations

67 Citations

0510'00'03'07'11'15
Citations per Year
Semantic Scholar estimates that this publication has 67 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 28 references

Behavioral heterogeneity and genetic algorithm learning in the cobweb model. Discussion Paper 9, IKSF

  • R. Franke
  • 1997
Highly Influential
3 Excerpts

A survey of evolution strategies

  • T. ck, F. Homeister, Schwefel, H.-P
  • Proceedings of the 4th International Conference…
  • 1991
Highly Influential
3 Excerpts

The Theory of Evolution and Dynamical Systems

  • J. Hofbauer, K. Sigmund
  • 1988
Highly Influential
5 Excerpts

Adaptive Learning by Genetic Algorithms, 2nd Edition

  • H. Dawid
  • 1999
2 Excerpts

Similar Papers

Loading similar papers…