PERCEPTION & COGNITION IN CATEGORIZATION/IDENTIFICATION

描述(申请人摘要)： 拟议研究的长期目标是更好地理解 知觉和认知过程的性质，当一个 个人对对象进行识别或分类。有两条研究路线： 概述。第一部分考察了人类分类的最佳性 当基本利率和收益同时被操纵时的表现。 概述了检验(A)刺激的效果的实验 属性，(B)类别可区分性，以及(C)成本和 与基本费率的各种分类答复相关的好处 和回报敏感度。所有的实验都将使用知觉 分类任务(如Ashby&Cott，1988；Maddox，1995) 指定了两个正态分布的类别和大量的 类别样本是从每个类别分布中抽样的。它的用途 正态分布类别允许最优决策规则 是派生出来的。方法是将一系列量化模型应用于 逐次尝试学习数据和渐近度量 性能。每个模型都将包含关于 回应的最佳性，或潜在的次最佳性。标准 分类程序以及假设性医疗诊断 将利用程序。这些研究将为许多现实世界提供信息 分类问题，如医疗诊断，其中基本比率和 回报往往是不同的，而且同时也不同。第二行 研究检查了知觉和决策注意的过程 识别和分类。实验被概述，以检验 注意线索和决策规则操作的影响，如 以及(B)刺激性质和响应截止日期操纵 知觉和果断的注意过程。为了更好地理解 这些注意系统的性质，将尝试解释 同时确保数据的准确性和响应时间(RT) 理论框架(例如，Maddox和Ashby，1996)。确保稳定 估计精度和RT数据，每个任务都会利用一个小的 独特刺激的数量(15-30个)，每个有200-300个演示 每种情况下的刺激。该方法是应用一系列 量化模型，每个模型都包含关于 知觉注意和决策注意的性质及其相互作用 系统，并将这些模型与从理论导出的模型进行比较 不区分知觉形式和决定形式的 注意(例如，许多基于范例的模型；Nosofsky，1986)。这些 研究很重要，因为它们将提供有关 对几乎所有类型的人类来说都是基本的注意力过程 行为。

DESCRIPTION (Applicant's abstract): The long-term objective of the proposed research is to better understand the nature of the perceptual and cognitive processes involved when a person identifies or categorizes objects. Two lines of research are outlined. The first examines the optimality of human categorization performance when base-rates and payoffs are manipulated simultaneously. Experiments are outlined that examine the effect of (a) stimulus properties, (b) category discriminability, and (c) the costs and benefits associated with various categorization responses on base-rate and payoff sensitivity. All experiment will use the perceptual categorization task (e.g., Ashby & Cott, 1988; Maddox, 1995) in which two normally distributed categories are specified and a large number of category exemplars are sampled from each category distribution. The use of normally distributed categories allows the optimal decision rule to be derived. The approach is to apply a series of quantitative models to the trial-by-trial learning data and to measures of asymptotic performance. Each model will embody specific hypotheses about the optimality, or potential sub-optimality, of responding. Standard categorization procedures as well as hypothetical medical diagnosis procedures will be utilized. These studies will inform many real-world categorization problems, such as medical diagnosis, where base-rates and payoffs often differ and vary simultaneously. The second line of research examines perceptual and decisional attention processes in identification and categorization. Experiments are outlined that examine the effects of (a) attention cue and decision rule manipulations, as well as (b) stimulus property and response deadline manipulations on perceptual and decisional attention processes. To better understand the nature of these attention systems, attempts will be made to account simultaneously for accuracy and response time (RT) data within a single theoretical framework (e.g., Maddox & Ashby, 1996). To ensure stable estimates of the accuracy and RT data, each task will utilize a small number of unique stimuli (15-30) with 200-300 presentations of each stimulus in each condition. The approach is to apply a series of quantitative models that each embody specific hypotheses about the nature of, and interaction between, perceptual and decisional attention systems, and to compare these models with models derived from theories that do not distinguish between perceptual and decisional forms of attention (e.g., many exemplar-based models; Nosofsky, 1986). These studies are important because they will provide useful information about attention processes that are fundamental to nearly all types of human behavior.