Concept formation : knowledge and experience in unsupervised learning
著者
書誌事項
Concept formation : knowledge and experience in unsupervised learning
（The Morgan Kaufmann series in machine learning）
Morgan Kaufmann Publishers, c1991
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Concept Formation: Knowledge and Experience in Unsupervised Learning presents the interdisciplinary interaction between machine learning and cognitive psychology on unsupervised incremental methods. This book focuses on measures of similarity, strategies for robust incremental learning, and the psychological consistency of various approaches. Organized into three parts encompassing 15 chapters, this book begins with an overview of inductive concept learning in machine learning and psychology, with emphasis on issues that distinguish concept formation from more prevalent supervised methods and from numeric and conceptual clustering. This text then describes the cognitive consistency of two concept formation systems that are motivated by a rational analysis of human behavior relative to a variety of psychological phenomena. Other chapters consider the merits of various schemes for representing and acquiring knowledge during concept formation. This book discusses as well the earliest work in concept formation. The final chapter deals with acquisition of quantity conservation in developmental psychology. This book is a valuable resource for psychologists and cognitive scientists.
目次
I Inductive Approaches to Concept Formation
1 Computational Models of Concept Learning
2 An Incremental Bayesian Algorithm for Categorization
3 Representational Specificity and Concept Learning
4 Discrimination Net Models of Concept Formation
5 Concept Formation in Structured Domains
II Knowledge and Experience in Concept Formation
6 Theory-Guided Concept Formation
7 Explanation-Based Learning as Concept Formation
8 Some Influences of Instance Comparisons on Concept Formation
9 Harpoons and Long Sticks: The Interaction of Theory and Similarity in Rule Induction
10 Concept Formation over Problem-Solving Experience
III The Utility of Concept Formation in Intelligent Behavior
11 Concept Formation in Context
12 The Formation and Use of Abstract Concepts in Design
13 Learning to Recognize Movements
14 Representation Generation in an Exploratory Learning System
15 A Computational Account of Children's Learning About Number Conservation
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