On using ZCS in a Simulated Continuous Double-Auction Market

This paper presents results from on-going investigations into the performance of the Michiganstyle classifier system in a complex multi-agent environment. Using a simplified model of a continuous double-auction market place the use of ZCS as an adaptive economic trading agent is examined. It is shown that a number of small changes to the basic system greatly improves its performance, resulting in improvements in the overall efficiency of the market. It is also shown that the role of the rule-discovery component of the classifier system is particularly critical in such a closely-coupled multi-agent environment.

• Type: Conference
• Year: 1999
• Where: GECCO
• Authors: Larry Bull
• Keywords: Complex Multi-agent Environment, Continuous Double-auction Market, GECCO 1999, Multi-agent Environment, Optimization