How People Reason and Learn about the Continuous World
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.
Hardcover$60.00 X | £50.00 ISBN: 9780262038942 440 pp. | 6 in x 9 in 109 b&w illus.
“Qualitative reasoning, getting computers to reason qualitatively about the real world, is one of the most challenging open problems in AI. This important book convincingly argues that qualitative reasoning provides an important link between perception and cognition. It is an immensely valuable resource for AI researchers and cognitive scientists alike."
Scientia Professor of Artificial Intelligence at University of New South Wales, Australia
"An accessible and comprehensive treatise on all aspects of qualitative representations, reasoning, and learning, and their relation to the quantitative world. A must-read for anyone who wants to understand the power and usefulness of symbolic, relational representations for both AI and cognitive science. Notable for its timeliness as these fields struggle to develop theories and implementations that bridge the burst of results from statistical machine learning with the power and rich expressiveness of qualitative representations.”
John E. Laird
John L. Tishman Professor of Engineering, University of Michigan
“This book presents a broad and deep exposition of the field of qualitative reasoning. It's a must-read for anyone interested in understanding the link between perception, cognition, and reasoning. The book beautifully brings together the fields of artificial intelligence, cognitive science, and psychology, in a way that only Ken Forbus can achieve.”
Professor of Constraint Programming, Department of Computer Science, and Director, Insight Centre for Data Analytics, University College Cork, Ireland
“It is three and a half decades since the landmark special issue of the journal Artificial Intelligence on qualitative reasoning, so it is certainly time to review what progress has been made since those auspicious beginnings. In this book, Ken Forbus reviews the origins of the field of qualitative reasoning and charts the progress since then, concentrating on his own work, but also including key related research of others. A constant thread is the relevance of qualitative reasoning to cognitive science, and how it has been influenced by cognitive science, for example in the chapters on analogical reasoning. I particularly welcome the attention given to qualitative spatial reasoning. For anyone interested in the field of qualitative reasoning, its relationship to cognitive science, sketch understanding, analogy, common sense, and expert reasoning, this book provides an excellent introduction, and many pointers to other work in the literature to explore.”
Anthony G. Cohn
Professor of Automated Reasoning, School of Computing, University of Leeds, UK