Genetic algorithms in economics: Difference between revisions

Revision as of 13:37, 12 July 2010

Revision as of 18:49, 13 July 2010

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{{Main|genetic algorithm}}

The '''[[geneticGenetic algorithm]]s''' hashave increasingly been applied to economics over the last two decades. It has been used to characterize a variety of models including the [[cobweb model]], the [[overlapping generations model]], [[game theory]], [[Genetic algorithm scheduling|schedule optimization]] and [[asset pricing]]. Specifically, it has been used as a model to represent learning, rather than as a means for fitting a model.

== Genetic Algorithmalgorithm in the Cobwebcobweb Modelmodel ==

The [[cobweb model]] is a simple supply and demand model for a good over ''t'' periods. Firms (agents) make a production quantity decision in a given period, however their output is not produced until the following period. Thus, the firms are going to have to use some sort of method to forecast what the future price will be. The GA is used as a sort of learning behaviour for the firms. Initially their quantity production decisions are random, however each period they learn a little more. The result is the agents converge within the area of the [[rational expectations]] (RATEX) equilibrium for the stable and unstable case. If the election operator is used, the GA converges exactly to the RATEX equilibrium.

There are two types of learning methods these agents can be deployed with: social learning and individual learning. In social learning, each firm is endowed with a single string which is used as its quantity production decision. It then compares this string against other firms' strings. In the individual learning case, agents are endowed with a pool of strings. These strings are then compared against other strings within the agent's population pool. This can be thought of as mutual competing ideas within a firm whereas in the social case, it can be thought of as a firm learning from more successful firms. Note that in the social case and in the individual learning case with identical cost functions, that this is a homogeneous solution, that is all agents' production decisions are identical. However, if the cost functions are not identical, this will result in a heterogeneous solution, where firms produce different quantities (note that they are still locally homogeneous, that is within the firm's own pool all the strings are identical).

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== References ==

* J Arifovic, 'Genetic Algorithm Learning and the Cobweb Model ', Journal of Economic Dynamics and Control, vol. 18, Issue 1, (January 1994), 3-–28.

==External links==