The University of Southampton
University of Southampton Institutional Repository

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?
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
Springer
Chen, Shu-Heng
13f75ac4-9eeb-4601-b72a-edb0784d112b
Tai, Chung-Ching
b3370b23-7410-4254-99bc-6711046e1095
Wang, Shu G.
148fc79e-ea39-491b-873c-947852088019
Tosto, Di
Parunak, H. Dyke
Chen, Shu-Heng
13f75ac4-9eeb-4601-b72a-edb0784d112b
Tai, Chung-Ching
b3370b23-7410-4254-99bc-6711046e1095
Wang, Shu G.
148fc79e-ea39-491b-873c-947852088019
Tosto, Di
Parunak, H. Dyke

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. pp. 37-48 . (doi:10.1007/978-3-642-13553-8_4).

Record type: 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.

This record has no associated files available for download.

More information

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
ORCID for Chung-Ching Tai: ORCID iD orcid.org/0000-0002-2557-177X

Catalogue record

Date deposited: 05 Aug 2022 16:52
Last modified: 13 Aug 2022 02:03

Export record

Altmetrics

Contributors

Author: Shu-Heng Chen
Author: Chung-Ching Tai ORCID iD
Author: Shu G. Wang
Editor: Di Tosto
Editor: H. Dyke Parunak

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×