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Evolutionary Optimization of Parameter Sets for Adaptive Software-Agent Traders in Continuous Double Auction Markets

Overview This paper presents the first results from using a genetic algorithm to optimize all the real- valued parameters governing adaptation in the trading agents. It is shown that a simple genetic algorithm (GA), in combination with an appropriate evaluation function, can deliver good parameter settings from random initial-value conditions. The evolutionary trajectories of the population through the 8- dimensional parameter space are illustrated, and the use of the GA to identify parameters that are redundant or even harmful is discussed.

Further White Paper Details
Publisher	HP Labs	File Format	PDF, requires Acrobat Rdr 5
Date Published	April 2001	Downloads	94
Format	White Papers
Topics	Electronic Malls, Online Trading, Genetic Engineering

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