Pittsburgh, Pennsylvania, United States of America
  •  17
    Physics by convention
    Philosophy of Science 39 (3): 322-340. 1972.
  •  11
    These are chapters from a book forthcoming from MIT Press. Comments to the author at cg09@andrew.cmu.edu would be most welcome. Still time for changes.
  •  162
    Convergence to the truth and nothing but the truth
    Philosophy of Science 56 (2): 185-220. 1989.
    One construal of convergent realism is that for each clear question, scientific inquiry eventually answers it. In this paper we adapt the techniques of formal learning theory to determine in a precise manner the circumstances under which this ideal is achievable. In particular, we define two criteria of convergence to the truth on the basis of evidence. The first, which we call EA convergence, demands that the theorist converge to the complete truth "all at once". The second, which we call AE co…Read more
  •  6
    Peter Spirtes, Richard Scheines and Clark Glymour. Simulated Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD, EQS and LISREL Programs
  •  59
    On some patterns of reduction
    Philosophy of Science 37 (3): 340-353. 1970.
    The notion of reduction in the natural sciences has been assimilated to the notion of inter-theoretical explanation. Many philosophers of science (following Nagel) have held that the apparently ontological issues involved in reduction should be replaced by analyses of the syntactic and semantic connections involved in explaining one theory on the basis of another. The replacement does not seem to have been especially successful, for we still lack a plausible account of inter-theoretical explanat…Read more
  •  19
    We applied TETRAD II, a causal discovery program developed in Carnegie Mellon University’s Department of Philosophy, to a database containing information on 204 U.S. colleges, collected by the US News and World Report magazine for the purpose of college ranking. Our analysis focuses on possible causes of low freshmen retention in U.S. colleges. TETRAD II finds a set of causal structures that are compatible with the data.
  • Theory and Evidence
    British Journal for the Philosophy of Science 32 (3): 314-318. 1981.
  •  296
    Determinism, ignorance, and quantum mechanics
    Journal of Philosophy 68 (21): 744-751. 1971.
    is every bit as intelligible and philosophically respectable as many other doctrines currently in favor, e.g., the doctrine that mental events are identical with brain events; the attempt to give a linguistic construal of this latter doctrine meets many of the same sorts of difficulties encountered above (see Hempel, op. cit.). Secondly, I think that evidence for universal determinism may not, as a matter of fact, be so hard to come by as one might imagine. It is a striking fact about our world …Read more
  •  43
    Words, Thoughts and Theories argues that infants and children discover the physical and psychological features of the world by a process akin to scientific inquiry, more or less as conceived by philosophers of science in the 1960s (the theory theory). This essay discusses some of the philosophical background to an alternative, more popular, “modular” or “maturational” account of development, dismisses an array of philosophical objections to the theory theory, suggests that the theory theory offe…Read more
  •  64
    If quanta had logic
    with Michael Friedman
    Journal of Philosophical Logic 1 (1). 1972.
  •  13
    Statistical Inference and Data Mining
    with David Madigan, Daniel Pregibon, and Padhraic Smyth
  •  49
    The theory of your dreams
    In R. Cohen & L. Laudan (eds.), Physics, Philosophy, and Psychoanalysis, D. Reidel. pp. 57--71. 1983.
  •  34
    After reviewing theoretical reasons for doubting that machine learning methods can accurately infer gene regulatory networks from microarray data, we test 10 algorithms on simulated data from the sea urchin network, and on microarray data for yeast compared with recent experimental determinations of the regulatory network in the same yeast species. Our results agree with the theoretical arguments: most algorithms are at chance for determining the existence of a regulatory connection between gene…Read more
  •  190
    Instrumental Probability
    The Monist 84 (2): 284-300. 2001.
    The claims of science and the claims of probability combine in two ways. In one, probability is part of the content of science, as in statistical mechanics and quantum theory and an enormous range of "models" developed in applied statistics. In the other, probability is the tool used to explain and to justify methods of inference from records of observations, as in every science from psychiatry to physics. These intimacies between science and probability are logical sports, for while we think sc…Read more
  •  28
    Various algorithms have been proposed for learning (partial) genetic regulatory networks through systematic measurements of differential expression in wild type versus strains in which expression of specific genes has been suppressed or enhanced, as well as for determining the most informative next experiment in a sequence. While the behavior of these algorithms has been investigated for toy examples, the full computational complexity of the problem has not received sufficient attention. We show…Read more
  •  44
    The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of the causal Bayes net formalism. Four experiments suggest that preschoolers can use the conditional intervention principle both to learn complex causal structure from patterns of evidence and to predict patterns of evidence from knowledge of causal structure. Other theories of causal learning do not account for these results.
  •  107
    & Carnegie Mellon University Abstract The rationality of human causal judgments has been the focus of a great deal of recent research. We argue against two major trends in this research, and for a quite different way of thinking about causal mechanisms and probabilistic data. Our position rejects a false dichotomy between "mechanistic" and "probabilistic" analyses of causal inference -- a dichotomy that both overlooks the nature of the evidence that supports the induction of mechanisms and misse…Read more
  • The paradox of predictivism (book review)
    Notre Dame Philosophical Reviews (6). forthcoming.
  •  23
    Hans Reichenbach
    Stanford Encyclopedia of Philosophy. 2008.
  •  46
    Regression and Causation
    with Richard Scheines, Peter Spirtes, and Christopher Meek
    Clark Glymour, Richard Scheines, Peter Spirtes, and Christopher Meek. Regression and Causation
  •  39
    The ability to identify the mineral composition of rocks and soils is an important tool for the exploration of geological sites. Even though expert knowledge is commonly used for this task, it is desirable to create automated systems with similar or better performance. For instance, NASA intends to design robots that are sufficiently autonomous to perform this task on planetary missions. Spectrometer readings provide one important source of data for identifying sites with minerals of interest. R…Read more
  •  32
    Our primary interest is in determining how many gene perturbation experiments are required to determine the Various algorithms have been proposed for learning..
  •  31
    Theory discovery from data with mixed quantifiers
    Journal of Philosophical Logic 19 (1). 1990.
    Convergent realists desire scientific methods that converge reliably to informative, true theories over a wide range of theoretical possibilities. Much attention has been paid to the problem of induction from quantifier-free data. In this paper, we employ the techniques of formal learning theory and model theory to explore the reliable inference of theories from data containing alternating quantifiers. We obtain a hierarchy of inductive problems depending on the quantifier prefix complexity of t…Read more
  •  25
    sities. TETRAD II discovers a class of possible causal structures of a system from a data set containing measurements of the system variables. The signi cance of learning the causal structure of a system is that it allows for predicting the e ect of interventions into the system, crucial in policy making. Our data sets contained information on 204 U.S. national universities, collected by the US News and World Report magazine for the purpose of college ranking in 1992 and 1993. One apparently rob…Read more
  •  3