Clark Glymour

Clark Glymour is Alumni University Professor in the Department of Philosophy at Carnegie Mellon University and Senior Research Scientist at Florida Institute for Human and Machine Cognition. He is the author of The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology (MIT Press), Galileo in Pittsburgh, and other books.

  • Thinking Things Through, Second Edition

    Thinking Things Through, Second Edition

    An Introduction to Philosophical Issues and Achievements

    Clark Glymour

    The second edition of a unique introductory text, offering an account of the logical tradition in philosophy and its influence on contemporary scientific disciplines.

    Thinking Things Through offers a broad, historical, and rigorous introduction to the logical tradition in philosophy and its contemporary significance. It is unique among introductory philosophy texts in that it considers both the historical development and modern fruition of a few central questions. It traces the influence of philosophical ideas and arguments on modern logic, statistics, decision theory, computer science, cognitive science, and public policy. The text offers an account of the history of speculation and argument, and the development of theories of deductive and probabilistic reasoning. It considers whether and how new knowledge of the world is possible at all, investigates rational decision making and causality, explores the nature of mind, and considers ethical theories. Suggestions for reading, both historical and contemporary, accompany most chapters.

    This second edition includes four new chapters, on decision theory and causal relations, moral and political theories, “moral tools” such as game theory and voting theory, and ethical theories and their relation to real-world issues. Examples have been updated throughout, and some new material has been added. It is suitable for use in advanced undergraduate and beginning graduate classes in philosophy, and as an ancillary text for students in computer science and the natural sciences.

    • Paperback $45.00 £38.00
  • Thinking about Android Epistemology

    Thinking about Android Epistemology

    Kenneth M. Ford, Clark Glymour, and Patrick Hayes

    How to think about minds that aren't like ours: using artificial intelligence and computation theory to study the powers and limits of systems that learn.

    For millennia, "from Aristotle to almost yesterday," the great problems of philosophy have all been about people: questions of epistemology and philosophy of mind have concerned human capacities and limitations. Still, say the editors of Thinking about Android Epistemology, there should be theories about other sorts of minds, other ways that physical systems can be organized to produce knowledge and competence. The emergence of artificial intelligence in mid-twentieth century provided a way to study the powers and limits of systems that learn, to theorize and to make theories sufficiently concrete so that their properties and consequences can be demonstrated. In this updated version of the 1995 MIT Press book Android Epistemology, computer scientists and philosophers—among them Herbert Simon, Daniel Dennett, and Paul Churchland—offer a gentle, unsystematic introduction to alternative systems of cognition. They look at android epistemology from both theoretical and practical points of view, offering not only speculative proposals but applications—ideas for using computational systems to expand human capacities. The accessible and entertaining essays include a comparison of 2001's HAL and today's computers, a conversation among aliens who have a low opinion of human cognition, an argument for the creativity of robots, and a short story illustrating the power of algorithms for learning causal relations.

    Contributors Neil Agnew, Margaret Boden, Paul Churchland, Daniel Dennett, Ken M. Ford, Clark Glymour, Pat Hayes, Henry Kyburg, Doug Lenat, Marvin Minsky, Joseph Nadeau, Anatol Rappoport, Herbert Simon, Lynn Andrea Stein, Susan Sterrett

    • Paperback $7.75 £5.99
  • The Mind's Arrows

    The Mind's Arrows

    Bayes Nets and Graphical Causal Models in Psychology

    Clark Glymour

    The use of Bayes nets and graphical causal models in the investigation of human learning of causal relations, and in modeling and inference in cognitive psychology.

    In recent years, small groups of statisticians, computer scientists, and philosophers have developed an account of how partial causal knowledge can be used to compute the effect of actions and how causal relations can be learned, at least by computers. The representations used in the emerging theory are causal Bayes nets or graphical causal models.

    In his new book, Clark Glymour provides an informal introduction to the basic assumptions, algorithms, and techniques of causal Bayes nets and graphical causal models in the context of psychological examples. He demonstrates their potential as a powerful tool for guiding experimental inquiry and for interpreting results in developmental psychology, cognitive neuropsychology, psychometrics, social psychology, and studies of adult judgment. Using Bayes net techniques, Glymour suggests novel experiments to distinguish among theories of human causal learning and reanalyzes various experimental results that have been interpreted or misinterpreted—without the benefit of Bayes nets and graphical causal models. The capstone illustration is an analysis of the methods used in Herrnstein and Murray's book The Bell Curve; Glymour argues that new, more reliable methods of data analysis, based on Bayes nets representations, would lead to very different conclusions from those advocated by Herrnstein and Murray.

    • Hardcover $40.00 £32.00
  • Causation, Prediction, and Search, Second Edition

    Causation, Prediction, and Search, Second Edition

    Peter Spirtes, Clark Glymour, and Richard Scheines

    The authors address the assumptions and methods that allow us to turn observations into causal knowledge, and use even incomplete causal knowledge in planning and prediction to influence and control our environment.

    What assumptions and methods allow us to turn observations into causal knowledge, and how can even incomplete causal knowledge be used in planning and prediction to influence and control our environment? In this book Peter Spirtes, Clark Glymour, and Richard Scheines address these questions using the formalism of Bayes networks, with results that have been applied in diverse areas of research in the social, behavioral, and physical sciences.

    The authors show that although experimental and observational study designs may not always permit the same inferences, they are subject to uniform principles. They axiomatize the connection between causal structure and probabilistic independence, explore several varieties of causal indistinguishability, formulate a theory of manipulation, and develop asymptotically reliable procedures for searching over equivalence classes of causal models, including models of categorical data and structural equation models with and without latent variables.

    The authors show that the relationship between causality and probability can also help to clarify such diverse topics in statistics as the comparative power of experimentation versus observation, Simpson's paradox, errors in regression models, retrospective versus prospective sampling, and variable selection.

    The second edition contains a new introduction and an extensive survey of advances and applications that have appeared since the first edition was published in 1993.

    • Hardcover $65.00 £55.00
    • Paperback $70.00 £58.00
  • Computation, Causation, and Discovery

    Computation, Causation, and Discovery

    Gregory F. Cooper and Clark Glymour

    In science, business, and policymaking—anywhere data are used in prediction—two sorts of problems requiring very different methods of analysis often arise. The first, problems of recognition and classification, concerns learning how to use some features of a system to accurately predict other features of that system. The second, problems of causal discovery, concerns learning how to predict those changes to some features of a system that will result if an intervention changes other features. This book is about the second—much more difficult—type of problem.

    Typical problems of causal discovery are: How will a change in commission rates affect the total sales of a company? How will a reduction in cigarette smoking among older smokers affect their life expectancy? How will a change in the formula a college uses to award scholarships affect its dropout rate? These sorts of changes are interventions that directly alter some features of the system and perhaps—and this is the question—indirectly alter others.

    The contributors discuss recent research and applications using Bayes nets or directed graphic representations, including representations of feedback or "recursive" systems. The book contains a thorough discussion of foundational issues, algorithms, proof techniques, and applications to economics, physics, biology, educational research, and other areas.

    • Paperback $55.00 £45.00
  • Android Epistemology

    Android Epistemology

    Kenneth M. Ford, Clark Glymour, and Patrick Hayes

    Android epistemology is the exploration of the space of possible machines and their capacities for knowledge, beliefs, attitudes, desires, and for action in accord with their mental states.

    Android epistemology is the exploration of the space of possible machines and their capacities for knowledge, beliefs, attitudes, desires, and for action in accord with their mental states.

    • Hardcover $45.00 £38.00
    • Paperback $50.00 £40.00
  • Thinking Things Through

    Thinking Things Through

    An Introduction to Philosophical Issues and Achievements

    Clark Glymour

    Thinking Things Through provides a broad, historical, and rigorous introduction to the logical tradition in philosophy and to its contemporary significance. The presentation is centered around three of the most fruitful issues in Western thought: What are proofs, and why do they provide knowledge? How can experience be used to gain knowledge or to alter beliefs in a rational way? What is the nature of mind and of mental events and mental states? In a clear and lively style, Glymour describes these key philosophical problems and traces attempts to solve them, from ancient Greece to the present.

    Thinking Things Through reveals the philosophical sources of modern work in logic, the theory of computation, Bayesian statistics, cognitive psychology, and artificial intelligence, and it connects these subjects with contemporary problems in epistemology and metaphysics. The text is full of examples and problems, and an instructor's manual is available.

    • Hardcover $45.00
    • Paperback $40.00 £32.00

Contributor

  • Foundational Issues in Human Brain Mapping

    Foundational Issues in Human Brain Mapping

    Stephen José Hanson and Martin Bunzl

    Neuroimagers and philosophers of mind explore critical issues and controversies that have arisen from the use of brain mapping in cognitive neuroscience and cognitive science.

    The field of neuroimaging has reached a watershed. Brain imaging research has been the source of many advances in cognitive neuroscience and cognitive science over the last decade, but recent critiques and emerging trends are raising foundational issues of methodology, measurement, and theory. Indeed, concerns over interpretation of brain maps have created serious controversies in social neuroscience, and, more important, point to a larger set of issues that lie at the heart of the entire brain mapping enterprise. In this volume, leading scholars—neuroimagers and philosophers of mind—reexamine these central issues and explore current controversies that have arisen in cognitive science, cognitive neuroscience, computer science, and signal processing. The contributors address both statistical and dynamical analysis and modeling of neuroimaging data and interpretation, discussing localization, modularity, and neuroimagers' tacit assumptions about how these two phenomena are related; controversies over correlation of fMRI data and social attributions (recently characterized for good or ill as "voodoo correlations"); and the standard inferential design approach in neuroimaging. Finally, the contributors take a more philosophical perspective, considering the nature of measurement in brain imaging, and offer a framework for novel neuroimaging data structures (effective and functional connectivity—"graphs").

    Contributors William Bechtel, Bharat Biswal, Matthew Brett, Martin Bunzl, Max Coltheart, Karl J. Friston, Joy J. Geng, Clark Glymour, Kalanit Grill-Spector, Stephen José Hanson, Trevor Harley, Gilbert Harman, James V. Haxby, Rik N. Henson, Nancy Kanwisher, Colin Klein, Richard Loosemore, Sébastien Meriaux, Chris Mole, Jeanette A. Mumford, Russell A. Poldrack, Jean-Baptiste Poline, Richard C. Richardson, Alexis Roche, Adina L. Roskies, Pia Rotshtein, Rebecca Saxe, Philipp Sterzer, Bertrand Thirion, Edward Vul

    • Hardcover $16.75 £13.99
    • Paperback $19.75 £15.99