Abstract
In chapter 5 we presented some simulations of genetic learning in evolutionary games. As it is, evolutionary games are however always a stylized model of an economic system, since no explicit structure of the model is given, but only the payoffs of the different actions in different circumstances. In chapter 3 we argued that economic systems are SDF systems because all the single individuals together determine the state of the economy, which again determines the payoffs of the different actions of the individuals. If we consider evolutionary games we always assume that the payoff of any action is the average of the payoffs which would be attained against all the different individuals (or more accurately against a uniform population acting like this individual) in the population. In other words, if we consider genetic learning in evolutionary games the fitness function is always a linear function of the state of the population. Obviously there are however many economic models where no such linear relationship exists and these differ in the basic structure from evolutionary games.
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© 1996 Springer-Verlag Berlin Heidelberg
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Dawid, H. (1996). Simulations with Genetic Algorithms in Economic Systems. In: Adaptive Learning by Genetic Algorithms. Lecture Notes in Economics and Mathematical Systems, vol 441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-00211-7_6
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DOI: https://doi.org/10.1007/978-3-662-00211-7_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61513-2
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