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.

Additional Metadata
Keywords agent-based computational economics, binary encoding, evolutionary algorithm, genetic algorithm, premature convergence
JEL Economic Methodology (jel B41), Business Administration and Business Economics; Marketing; Accounting (jel M), Production Management (jel M11), Econometric and Input Output Models; Other Models (jel R15), Transportation Systems (jel R4)
Publisher Erasmus Research Institute of Management
Persistent URL hdl.handle.net/1765/16014
Series ERIM Report Series Research in Management
Journal ERIM report series research in management Erasmus Research Institute of Management
Citation
Waltman, L, van Eck, N.J.P, Dekker, R, & Kaymak, U. (2009). Economic Modeling Using Evolutionary Algorithms: The Effect of a Binary Encoding of Strategies (No. ERS-2009-028-LIS). ERIM report series research in management Erasmus Research Institute of Management. Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/16014