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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/48586


    Title: On the Selection of Adaptive Algorithms in ABM：A Computational Equivalence Approach
    Authors: 陳樹衡
    Chen,Shu-Heng;TAI,CHUNG-CHING
    Contributors: 政大經濟系
    Keywords: agent-based methodology;agent engineering;computational intelligence;computational equivalence;CE lab
    Date: 2006-07
    Issue Date: 2010-11-24 22:03:34 (UTC+8)
    Abstract: Agent-based Methodology (ABM) is becoming indispensable for the interdisciplinary
    study of social and economic complex adaptive systems. The essence of ABM lies in the notion
    of autonomous agents whose behavior may evolve endogenously and can generate and mimic the
    corresponding complex system dynamics that the ABM is studying. Over the past decade, many
    Computational Intelligence (CI) methods have been applied to the design of autonomous agents, in
    particular, their adaptive schemes. This design issue is non-trivial since the chosen adaptive schemes
    usually have a profound impact on the generated system dynamics. Robert Lucas, one of the most
    influential modern economic theorists, has suggested using laboratories with human agents, also
    known as Experimental Economics, to help solve the selection issue. While this is a promising
    approach, laboratories used in the current experimental economics are not computationally equipped
    to meet the demands of the selection task. This paper attempts to materialize Lucas’ suggestion
    by establishing a laboratory where human subjects are equipped with the computational power that
    satisfies the computational equivalence condition.
    Relation: Computational Economics,28(1),51-69
    Data Type: article
    DOI link: http://dx.doi.org/10.1007/s10614-006-9039-1
    DOI: 10.1007/s10614-006-9039-1
    Appears in Collections:[Department of Economics] Periodical Articles

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