Toward an Agent-Based Computational Modeling of Bargaining Strategies in Double Auction Markets with Genetic Programming
Created by W.Langdon from
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- @InProceedings{Chen:2000:TAB,
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author = "Shu-Heng Chen",
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title = "Toward an Agent-Based Computational Modeling of
Bargaining Strategies in Double Auction Markets with
Genetic Programming",
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booktitle = "Intelligent Data Engineering and Automated Learning -
IDEAL 2000: Data Mining, Financial Engineering, and
Intelligent Agents",
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editor = "Kwong Sak Leung and Lai-Wan Chan and Helen Meng",
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year = "2000",
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series = "Lecture Notes in Computer Science",
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volume = "1983",
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pages = "517--531",
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address = "Shatin, N.T., Hong Kong, China",
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month = "13-15 " # dec,
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-41450-9",
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CODEN = "LNCSD9",
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ISSN = "0302-9743",
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bibdate = "Tue Sep 10 19:08:58 MDT 2002",
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URL = "http://www.aiecon.org/staff/shc/pdf/toward_an_agent.pdf",
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URL = "http://citeseer.ist.psu.edu/463839.html",
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DOI = "doi:10.1007/3-540-44491-2_76",
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acknowledgement = ack-nhfb,
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size = "15 pages",
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abstract = "Using genetic programming, this paper proposes an
agent- based computational modelling of double auction
(DA) markets in the sense that a DA market is modeled
as an evolving market of autonomous interacting traders
(automated software agents). The specific DA market on
which our modeling is based is the Santa Fe DA market
([12], [13]), which in structure, is a discrete-time
version of the Arizona continuous- time experimental DA
market ([14], [15]).",
- }
Genetic Programming entries for
Shu-Heng Chen
Citations