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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/55309


    Title: 決策學習模型的通用架構---尺度不變性與參數估計
    Other Titles: A General Framework for Decision-Learning Models---Dimensional Invariance and Parameter Estimation
    Authors: 鄭中平
    Contributors: 國立政治大學心理學系
    行政院國家科學委員會
    Keywords: 決策學習模型
    Date: 2009
    Issue Date: 2012-11-08 14:05:26 (UTC+8)
    Abstract: 愛荷華賭博作業廣泛用在顯示不同群體在決策歷程中的差異，透過以量化的認知模型分析愛荷華賭博作業，由於模型中的參數分別對應愛荷華賭博作業心理歷程的成分，可進一步瞭解不同群體在決策歷程上的可能差異。除了常用的期望價值學習模型外，尚有近十個量化認知模型，企圖模擬愛荷華賭博作業的認知歷程。本研究有三個目的，首先在建立一個通用的架構，儘可能納入這些決策學習模型。其次，透過通用架構進行這些模型的比對，瞭解模型的尺度不變性。最後，本研究擬針對此通用架構發展較具一般性的估計方式，以進行這些模型的參數估計。
    Iowa gambling task is a cognitive task designed for exploring the possible decision making deficit. By modeling this task, parameters of the expectancy-valence model may be correspondent to the components of psychological processes underlying the Iowa gambling task. Besides the often-cited expectancy-valence model, there are up to 10 quantitative decision-learning models which also aim to simulate Iowa gambling task. The study consists of three objectives. First, the study will propose a general framework to incorporate most decision-learning models. Second, by comparing these models under the framework, we will explore the dimensional invariance issue. Finally, the study tries to develop a comprehensive statistical routine for most decision-learning models under the framework.
    Relation: 基礎研究
    學術補助
    研究期間:9808~ 9907
    研究經費:443仟元
    Data Type: report
    Appears in Collections:[心理學系] 國科會研究計畫

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