Refining the Breeding of Hybrid Strategies




Robert E. Marks
Australian Graduate School of Management
University of New South Wales
Sydney NSW 2052
Australia
bobm@agsm.edu.au

David F. Midgley
Australian Graduate School of Management
University of New South Wales
Sydney NSW 2052
Australia
and
INSEAD
davidm@agsm.edu.au

Lee G. Cooper
Anderson Graduate School of Management
University of California Los Angeles
Los Angeles CA 90095
USA
lcooper@agsm.ucla.edu





ABSTRACT

We extend our earlier work using artificial agents to model multi-period games between competing brands in an oligopoly. We do so by developing a multiple-population genetic algorithm in order to allow customized agents for each brand. We also consider more competitors and more possible pricing actions per competitor than before, and we evaluate the robustness of our results by Monte Carlo methods. All these developments have been facilitated by writing better code and by increases in computing power since our original work. We find that:

In addition, we report on two surprising effects. The Holyfield-Tyson effect: whereby sophistic ated agents do not perform that well against primitive agents; and the Frankenstein effect: whereby agents developed in competition with other agents exhibit different behaviors when competing with the historical actions of managers.

Overall, we believe the strength of our approach results from the use of an empirically grounded fitness function with which to test our assumptions and approaches.

Text of the paper in Acrobat PDF 3.0 format


bobm@agsm.edu.au
Last altered on February 16, 1999.