Understanding the nature of predatory pricing in the large-scalemarket economy with genetic algorithms
Shu-Heng Chen
Chih-Chi Ni
AI-ECON Res. Grou, Nat. Chengchi Univ., Taipei ;
This paper appears in: Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Publication Date: 15-18 Sep 1996
On page(s): 354-359
Meeting Date: 09/15/1996 - 09/18/1996
Location: Dearborn, MI, USA
ISBN: 0-7803-2978-3
References Cited: 13
INSPEC Accession Number: 5431302
Digital Object Identifier: 10.1109/ISIC.1996.556227
Current Version Published: 2002-08-06
Abstract
This paper applies co-evolutionary genetic algorithms to an
economic modelling problem. The chain-store game is a game-theoretic
model for predatory pricing (price wars); the modelling goal is to study
when predatory pricing can arise. It is found that, even under the same
payoff structure, the results of the co-evolution of weak monopolists
and entrants are sensitive to the representation of the decision-making
process. Two representations are studied: 1) the action-based
representation, and 2) the strategy-based representation. The former is
to represent a naive mind and the latter is to capture a sophisticated
mind. For the action-based representation, the convergence results are
easily obtained and predatory pricing is only temporary in all
simulations. However, for the strategy-based representation, predatory
pricing is not a rare phenomenon and its appearance is cyclical but not
regular
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