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EITM: Minimization of complexity in human concept learning

EITM: Minimization of complexity in human concept learning
EITM:人类概念学习复杂性最小化
批准号:
0339062
负责人:
Jacob Feldman
金额:
$17.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-05-01 至 2008-04-30

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中文摘要
翻译
这个项目调查了人类学习者如何从例子中形成概括,重点是概念复杂性如何影响学习。在归纳概念时,当学习者只看了几把椅子后,就形成了对“椅子”概念的抽象,人类学习者倾向于简单;即,他们倾向于归纳与例子一致的最简单的概括。然而,“简单”一词的确切含义是出了名的难以用严谨的理论来把握。这个项目借鉴了在量化概念简单性和复杂性方面的最新进展,这些方法在数学上是合理的,在心理上也是准确的。该项目力求将这一进展推广到比以往更广泛的人类概念类型,包括“模糊”概率概念和在连续特征上定义的概念。该项目既包括数学建模,也包括对人体受试者进行广泛的实验,以学习各种概念。通过扩展我们对人类学习中复杂性最小化的理解,该项目旨在建立一个更完整的人类学习机制的描述。这个项目有许多潜在的科学好处,包括更好地理解人类学习,以及更有效的自动学习机制的可能性。更广泛地说,这个项目有可能帮助量化是什么让一些概念天生就比其他概念更容易学习,这可能会直接应用于教育实践和治疗学习障碍的理解。
英文摘要
This project investigates how human learners form generalizations from examples, focusing on how conceptual complexity influences learning. When inducing concepts, as when a learner forms an abstraction of the concept "chair" after viewing only a few individual chairs, human learners have a bias towards simplicity; i.e., they tend to induce the simplest generalizations consistent with the examples. The exact meaning of the term "simple," however, is notoriously difficult to capture in a rigorous theory. This project draws on recent progress in quantifying conceptual simplicity and complexity in ways that are both mathematically sound and psychologically accurate. The project seeks to generalize this progress to apply to a wider range of human conceptual types than has previously been possible, including "fuzzy" probabilistic concepts and concepts defined over continuous features. The project involves both mathematical modeling and extensive experiments on human subjects learning a wide variety of concepts. By extending our understanding of complexity-minimization in human learning, the project aims to build a more complete account of the mechanisms underlying human learning.This project has many potential scientific benefits, including a greater understanding of human learning and the possibility of more effective automated learning mechanisms. More broadly, this project has the potential to help quantify what makes some concepts inherently easier for humans to learn than others, which could have direct applications to education practices and to treatment understanding of learning disorders.
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EAGER: SAI: Cognitive Models of Human Social Wayfinding for the Redesign of Public Spaces
  • 批准号:
    2122119
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.99万
  • 财政年份:
    2021
  • 负责人:
    Jacob Feldman
  • 依托单位:
CAREER: The Logic of Grouping and Perceptual Organization
  • 批准号:
    9875175
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $32.45万
  • 财政年份:
    1999
  • 负责人:
    Jacob Feldman
  • 依托单位:
Mathematical Sciences: Ergodic Theory and Related Topics
  • 批准号:
    9500803
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.4万
  • 财政年份:
    1995
  • 负责人:
    Jacob Feldman
  • 依托单位:
Mathematical Sciences: Topics in Ergodic Theory and Dynamical Systems
  • 批准号:
    9113642
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.15万
  • 财政年份:
    1992
  • 负责人:
    Jacob Feldman
  • 依托单位:
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