Economic Modeling Using Evolutionary Algorithms: The Effect of a Binary Encoding of Strategies

Ludo Waltman, Nees Jan van Eck, Rommert Dekker and Uzay Kaymak ()

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

Abstract: We are concerned with evolutionary algorithms that are employed for economic modeling purposes. We focus in particular on evolutionary algorithms that use a binary encoding of strategies. These algorithms, commonly referred to as genetic algorithms, are popular in agent-based computational economics research. In many studies, however, there is no clear reason for the use of a binary encoding of strategies. We therefore examine to what extent the use of such an encoding may influence the results produced by an evolutionary algorithm. It turns out that the use of a binary encoding can have quite significant effects. Since these effects do not have a meaningful economic interpretation, they should be regarded as artifacts. Our findings indicate that in general the use of a binary encoding is undesirable. They also highlight the importance of employing evolutionary algorithms with a sensible economic interpretation.

Keywords: agent-based computational economics; binary encoding; evolutionary algorithm; genetic algorithm; premature convergence (search for similar items in EconPapers)
JEL-codes: B41 M M11 R15 R4 (search for similar items in EconPapers)
Date: 2009-05-20
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Citations: View citations in EconPapers (3)

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Journal Article: Economic modeling using evolutionary algorithms: the effect of a binary encoding of strategies (2011)
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