Does cognitive capacity matter when learning using genetic programming in double auction markets?
Does cognitive capacity matter when learning using genetic programming in double auction markets?
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.
37-48
Chen, Shu-Heng
13f75ac4-9eeb-4601-b72a-edb0784d112b
Tai, Chung-Ching
b3370b23-7410-4254-99bc-6711046e1095
Wang, Shu G.
148fc79e-ea39-491b-873c-947852088019
2010
Chen, Shu-Heng
13f75ac4-9eeb-4601-b72a-edb0784d112b
Tai, Chung-Ching
b3370b23-7410-4254-99bc-6711046e1095
Wang, Shu G.
148fc79e-ea39-491b-873c-947852088019
Chen, Shu-Heng, Tai, Chung-Ching and Wang, Shu G.
(2010)
Does cognitive capacity matter when learning using genetic programming in double auction markets?
Tosto, Di and Parunak, H. Dyke
(eds.)
In Multi-Agent-Based Simulation X: International Workshop, MABS 2009, Budapest, Hungary, May10-15, 2009. Revised Selected Papers.
vol. 5683,
Springer.
.
(doi:10.1007/978-3-642-13553-8_4).
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Conference or Workshop Item
(Paper)
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.
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Published date: 2010
Additional Information:
© 2010 Springer-Verlag Berlin Heidelberg
Venue - Dates:
The 10th International Workshop on Multi-Agent-Based Simulation (MABS 2009), , Budapest, Hungary, 2009-05-10 - 2009-05-15
Identifiers
Local EPrints ID: 468215
URI: http://eprints.soton.ac.uk/id/eprint/468215
PURE UUID: 0967d0cc-a94b-48a6-850e-a216ea6de8fb
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Date deposited: 05 Aug 2022 16:52
Last modified: 17 Mar 2024 03:59
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Contributors
Author:
Shu-Heng Chen
Author:
Shu G. Wang
Editor:
Di Tosto
Editor:
H. Dyke Parunak
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