検索条件入力書誌詳細 > Qualitative representations : how people reason and learn about the continuous world
書誌情報:Qualitative representations : how people reason and learn about the continuous world
Kenneth D. Forbus
Cambridge : The MIT Press , [2018]
1 online resource (xvi, 424 p.)
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https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8618068
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書誌詳細
刊年2018
G/SMDリモートファイル
形態1 online resource (xvi, 424 p.)
注記Includes bibliographical references and index
Introduction and preliminaries -- Introduction -- Representation -- Reasoning -- Analogy -- Dynamics -- Quantity -- Relationships between quantities -- Qualitative process theory -- Examples using QP theory -- Causality -- Qualitative simulation and reasoning about change -- Modeling -- Analogy in dynamics -- Dynamics in language -- Space -- Qualitative spatial reasoning: a theoretical framework -- Qualitative spatial calculi -- Understanding sketches and diagrams -- Learning and reasoning -- Learning and conceptual change -- Commonsense reasoning -- Expert reasoning -- Summary and new directions -- Summary -- New directions -- Bibliography -- Notes -- Index
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An argument that qualitative representations -- symbolic representations that carve continuous phenomena into meaningful units -- are central to human cognition. In this book, Kenneth Forbus proposes that qualitative representations hold the key to one of the deepest mysteries of cognitive science: how we reason and learn about the continuous phenomena surrounding us. Forbus argues that qualitative representations -- symbolic representations that carve continuous phenomena into meaningful units -- are central to human cognition. Qualitative representations provide a basis for commonsense reasoning, because they enable practical reasoning with very little data; this makes qualitative representations a useful component of natural language semantics. Qualitative representations also provide a foundation for expert reasoning in science and engineering by making explicit the broad categories of things that might happen and enabling causal models that help guide the application of more quantitative knowledge as needed. Qualitative representations are important for creating more human-like artificial intelligence systems with capabilities for spatial reasoning, vision, question answering, and understanding natural language. Forbus discusses, among other topics, basic ideas of knowledge representation and reasoning; qualitative process theory; qualitative simulation and reasoning about change; compositional modeling; qualitative spatial reasoning; and learning and conceptual change. His argument is notable both for presenting an approach to qualitative reasoning in which analogical reasoning and learning play crucial roles and for marshaling a wide variety of evidence, including the performance of AI systems. Cognitive scientists will find Forbus's account of qualitative representations illuminating; AI scientists will value Forbus's new approach to qualitative representations and the overview he offers
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Mode of access: World Wide Web
Print version record
URL:https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8618068(Abstract with links to resource)
出版国アメリカ合衆国
標題言語英語
本文言語英語
著者情報Forbus, Kenneth D.
ISBN9780262349802(: electronic bk)
無効/取消ISBN9780262038942(: electronic bk)
件名LCSH:Cognition
LCSH:Reasoning
LCSH:Spaceperception
NCID8618068
IDENThttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8618068

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