80-821 Seminar on Methodology

Units: 9-12 Department: Philosophy Cross-listed: 80-521 Related URLs: http://www.hss.cmu.edu/philosophy This seminar is on my favorite topic, reconceiving issues in the philosophy of science and induction in computational, rather than probabilistic terms so that truth-finding performance rather than justification is the primary concern. The theoretical background of the course is known as computational learning theory, but it might better be called computational epistemology. Instead of promoting a single standard of rationality or a single scientific method for all empirical questions, we will think of such questions as having intrinsic complexities that determine the best sense in which the true answer can be found. The subject is open-ended, with opportunities for keen students to make an original mark. Possible topics include: the topological and computational structure of the problem of induction, deep analogies between uncomputability and the problem of induction, learning theory and historicist conclusions about the nature of science, computers that can learn uncomputable facts about the environment, the learning power of belief revision algorithms, infinite regresses of methods, modal logics of convergent knowledge, a derivation of Ockhams razor from the aim of minimizing retractions or errors prior to finding the truth, and how all of this relates to standard approaches in the philosophy of science and statistics, such as model selection, Bayesian updating and classical statistical tests. Graduate students from other departments and undergraduates with training equivalent to 80-311 or 80-319 are welcome. Others are welcome to check with the instructor. The basic text will be the instructors book The Logic of Reliable Inquiry, which will be augmented by articles and excerpts from other works. The grade will be based on some exercises, seminar reports on class readings, and a short final paper.

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Spring 2005 times

No sections available for semester Spring 2005.