Clark Glymour

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Clark Glymour is the Alumni University Professor in the Department of Philosophy at Carnegie Mellon University. He is also a senior research scientist at the Florida Institute for Human and Machine Cognition.[1] He is the founder of the Philosophy Department at Carnegie Mellon University, a Guggenheim Fellow, a Fellow of the Center for Advanced Study in Behavioral Sciences a Phi Beta Kappa lecturer, and is a Fellow of the statistics section of the AAAS. Glymour and his collaborators created the causal interpretation of Bayes nets.[2] His areas of interest include epistemology[3][4] (particularly Android epistemology), machine learning, automated reasoning, psychology of judgment, and mathematical psychology.[5] One of Glymour's main contributions to the philosophy of science is in the area of Bayesian probability, particularly in his analysis of the Bayesian "problem of old evidence".[6][7] Glymour, in collaboration with Peter Spirtes and Richard Scheines, also developed an automated causal inference algorithm implemented as software named TETRAD.[8] Using multivariate statistical data as input, TETRAD rapidly searches from among all possible causal relationship models and returns the most plausible causal models based on conditional dependence relationships between those variables. The algorithm is based on principles from statistics, graph theory, philosophy of science, and artificial intelligence.[9]

Glymour earned undergraduate degrees in chemistry and philosophy. He did graduate work in chemical physics and obtained a Ph.D in History and Philosophy of Science from Indiana University in 1969.

Publications[edit]

Books[edit]

  • Theory and Evidence (Princeton, 1980)
  • Examining Holistic Medicine (with D. Stalker), Prometheus, 1985
  • Foundations of Space-Time Theories (with J. Earman), University of Minnesota Press, 1986
  • Discovering Causal Structure (with R. Scheines, P. Spirtes and K.Kelly) Academic Press, 1987
  • Causation, Prediction and Search (with P.Spirtes and R. Scheines), Springer, 1993, 2nd Edition MIT Press, 2001
  • Thinking Things Through, MIT Press, 1994
  • Android Epistemology (with K. Ford and P. Hayes) MIT/AAAI Press, 1996
  • The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology, MIT Press, 2001
  • Galileo in Pittsburgh Harvard University Press, 2010.

Journal articles[edit]

  • When is a Brain Like the Planet?, Philosophy of Science, 2008.
  • (with David Danks) Reasons as Causes in Bayesian Epistemology, Journal of Philosophy, 2008.
  • Markov Properties and Quantum Experiments, in W. Demopoulos and I. Pitowsky, eds. Physical Theory and Its Interpretation: Essays in Honor of Jeffrey Bub, Springer 2006.
  • (with Chu, T. and David Danks) Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms, 2004.
  • Review of Phil Dowe and Paul Nordhoff: Cause and Chance: Causation in an Indeterministic World, Mind, 2005.
  • (with Eberhardt, Frederick, and Richard Scheines). N-1 Experiments Suffice to Determine the Causal Relations Among N Variables, 2004.
  • (with F. Eberhardt and R. Scheines), Log2(N) Experiments are Sufficient, and in the Worst Case Necessary, for Identifying Causal Structure, UAI Proceedings, 2005
  • (with Handley, Daniel, Nicoleta Serban, David Peters, Robert O'Doherty, Melvin Field, Larry Wasserman, Peter Spirtes, and Richard Scheines), Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays, Genomics, Vol. 83, Issue 6 (June, 2004), 1169-1175.
  • (with Handley, Daniel, Nicoleta Serban, and David G. Peters). Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors, Statistical Applications in Genetics and Molecular Biology, Vol. 3, Issue 1 (October 6, 2004), Article 25.
  • Comment on D. Lerner, The Illusion of Conscious Will, Behavioral and Brain Sciences, in press.
  • Review of Joseph E. Early, Sr. (Ed.): Chemical Explanation: Characteristics, Development, Autonomy, Philosophy of Science, Vol. 71, No. 3 (July, 2004), 415-418.
  • (with Spirtes, and Peter Glymour). Causal Inference, Encyclopedia of Social Science, in press
  • We believe in freedom of the will so that we can learn, Behavioral and Brain Sciences, Vol. 27, No. 5 (2004), 661-662.
  • The Automation of Discovery, Daedelus, Vol. Winter (2004), 69-77.
  • (with Serban, Nicoleta, Larry Wasserman, David Peters, Peter Spirtes, Robert O'Doherty, Dan Handley, and Richard Scheines). Analysis of microarray data for treated fat cells, (2003).
  • (with Danks, David, and Peter Spirtes). The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search, (2003).
  • (with Silva, Ricardo, Richard Scheines, and Peter Spirtes). Learning Measurement Models for Unobserved Variables, UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7–10, 2003, Acapulco, Mexico (2003), 543-550.
  • (with Danks, David and Peter Spirtes). The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search, Proceedings of IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics, (2003), 22-31.
  • (with Frank Wimberly, Thomas Heiman, and Joseph Ramsey). Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels, International Joint Conference on Artificial Intelligence Workshop, 2003
  • A Semantics and Methodology for Ceteris Paribus Hypotheses, Erkenntnis, Vol. 57 (2002), 395-405.
  • Review of James Woodward, Making Things Happen: A Theory of Causal Explanation, British Journal for Philosophy of Science, Vol. 55 (2004), 779-790.
  • (with Fienberg, Stephen, and Richard Scheines). Expert statistical testimony and epidemiological evidence: the toxic effects of lead exposure on children, Journal of Econometrics, Vol 113 (2003), 33-48.
  • Learning, prediction and causal Bayes Nets, Trends in Cognitive Science, Vol. 7, No. 1 (2003), 43-47.
  • (with Alison Gopnik, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks). A theory of causal learning in children: Causal maps and Bayes nets, Psychological Review, Vol. 111, No. 1 (2004).
  • and many others dating back to 1970.

External links[edit]

References[edit]

  1. ^ http://www.hss.cmu.edu/philosophy/faculty-glymour.php
  2. ^ P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993
  3. ^ http://loriweb.org/?p=2154>
  4. ^ Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, ISBN 87-92130-07-0
  5. ^ http://www.ihmc.us/groups/cglymour/
  6. ^ http://plato.stanford.edu/entries/epistemology-bayesian/
  7. ^ Glymour, C.; Theory and evidence (1981), pp. 63-93.
  8. ^ http://www.phil.cmu.edu/projects/tetrad/publications.html
  9. ^ Glymour, Clark; Scheines, Richard; Spirtes, Peter; Kelly, Kevin. "TETRAD: Discovering Causal Structure" Multivariate Behavioral Research 23.2 (1988). 10 July 2010 http://www.informaworld.com/10.1207/s15327906mbr2302_13