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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/64753


    Title: Is Genetic Programming ``Human-Competitive''''? The Case of Experimental Double Auction Markets
    Authors: 陳樹衡
    Chen, Shu-Heng;Shih, Kuo-Chuan
    Contributors: 經濟系
    Keywords: Experimental Markets;Double Auctions;Genetic Programming;Human-Competitiveness;Working Memory Capacity
    Date: 2011
    Issue Date: 2014-03-20 16:57:43 (UTC+8)
    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 behavior is driven by genetic programming (GP). To this end, a learning index based upon the optimal solution to a double auction market problem, characterized 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.
    Relation: Intelligent Data Engineering and Automated Learning - IDEAL 2011 Lecture Notes in Computer Science Volume 6936, 2011, pp 116-126
    Data Type: book/chapter
    DOI 連結: http://dx.doi.org/10.1007/978-3-642-23878-9_15
    DOI: 10.1007/978-3-642-23878-9_15
    Appears in Collections:[經濟學系] 專書/專書篇章

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