Is Genetic Programming ``Human-Competitive''? The Case of Experimental Double Auction Markets

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{conf/ideal/ChenS11,

• author = "Shu-Heng Chen and Kuo-Chuan Shik",
• title = "Is Genetic Programming ``Human-Competitive''? The Case of Experimental Double Auction Markets",
• booktitle = "Proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning, {IDEAL} 2011",
• year = "2011",
• editor = "Hujun Yin and Wenjia Wang and Victor J. Rayward-Smith",
• volume = "6936",
• series = "Lecture Notes in Computer Science",
• pages = "116--126",
• address = "Norwich, UK",
• month = sep # " 7-9",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, experimental markets, double auctions, working memory capacity",
• isbn13 = "978-3-642-23877-2",
• DOI = "doi:10.1007/978-3-642-23878-9_15",
• size = "11 pages",
• abstract = "In this paper, the performance of human subjects is compared with genetic programming in trading. Within a kind of double auction market, we compare the learning performance between human subjects and autonomous agents whose trading behaviour is driven by genetic programming (GP). To this end, a learning index based upon the optimal solution to a double auction market problem, characterised as integer programming, is developed, and criteria tailor-made for humans are proposed to evaluate the performance of both human subjects and software agents. It is found that GP robots generally fail to discover the best strategy, which is a two-stage procrastination strategy, but some human subjects are able to do so. An analysis from the point of view of cognitive psychology further shows that the minority who were able to find this best strategy tend to have higher working memory capacities than the majority who failed to do so. Therefore, even though GP can outperform most human subjects, it is not human-competitive from a higher standard.",
• affiliation = "AIECON research center, Department of Economics, National Chengchi University, Taipei, Taiwan",
• bibdate = "2011-08-25",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/ideal/ideal2011.html#ChenS11",

}

Genetic Programming entries for Shu-Heng Chen Kuo-Chuan Shik

Citations