Does cognitive capacity matter when learning using genetic programming in double auction markets?

Authors:
Shu-Heng Chen;Chung-Ching Tai;Shu G. Wang
Affiliations:
AI-ECON Research Center, Department of Economics, National Chengchi University, Taiwan;Department of Economics, Tunghai University, Taiwan;AI-ECON Research Center, Department of Economics, National Chengchi University, Taiwan
Venue:
MABS'09 Proceedings of the 10th international conference on Multi-agent-based simulation
Year:
2009

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Abstract

The relationship between human subjects' cognitive capacity and their economic performances has been noticed in recent years due to the evidence found in a series of cognitive economic experiments. However, there are few agent-based models aiming to characterize such relationship. This paper attempts to bridge this gap and serve as an agent-based model with a focus on agents' cognitive capacity. To capture the heterogeneity of human cognitive capacity, this paper employs genetic programming as the algorithm of the learning agents, and then uses population size as a proxy parameter of individual cognitive capacity. By modeling agents in this way, we demonstrate a nearly positive relationship between cognitive abilities and economic performance.