Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.
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DOI:
10.1037/a0018526
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发表时间:
2010-04
影响因子:
5.4
通讯作者:
Nosofsky, Robert M.
Nosofsky, Robert M.
中科院分区:
心理学1区
文献类型:
--
作者:
Fific, Mario;Little, Daniel R.;Nosofsky, Robert M.

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我们形式化并提供了一组用于预测感知分类响应时间(RTs)和选择概率的逻辑规则模型的测试。这些模型是通过综合心理架构、随机漫步和决策约束方法开发的。根据这些模型,人们根据一组组成维度对刺激的位置做出独立的决定。然后,通过逻辑规则将这些独立的决策组合起来,以确定总体分类响应。独立决策的时间过程通过沿单个维度操作的随机行走过程来建模。备选的心智架构被用作组合独立决策以实现逻辑规则的机制。我们得出了基本的定性对比,以区分规则模型和分类RT的主要替代模型的预测。我们还使用这些模型来预测与快速感知分类任务中单个刺激相关的详细RT分布数据。
We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT distribution data associated with individual stimuli in tasks of speeded perceptual classification.
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