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08: Scientific Rationality: Bayesianism vs. Reliabilism

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Hauptschule
Seminar / Seminar
english language

How can novel, appropriate concepts be introduced in science? How can rational scientific change come about? How are scientific revolutions produced? How can advocates of very different scientific positions rationally discuss and resolve their differences? This seminar will explore two answers to these questions. Bayesian epistemology maintains that rational inquiry in science consists of adjusting probabilities of hypotheses in the light of evidence by rules that first emerged in the 18th century. Formal learning theory postulates that rational inquiry consists in using methods that are reliably converged to the truth. Each framework implies astonishing consequences for methods of inquiry.

Carnegie Mellon University, Pittsburgh
London School of Economics and Political Science

Dr. Clark GLYMOUR

Carnegie Mellon University, Pittsburgh

 Endowed positions at:
 Princeton University
 University of California San Diego
 Carnegie Mellon University
 Visiting Professor of Computer Science at Instituto Technilogico de Costa Rica

Dr. Stephan HARTMANN

London School of Economics and Political Science

Research Assistant, Center for Philosophy and the Foundations of Science, University of Gießen Research Assistant, Department of Physics, University of Gießen Visiting Scholar, Department of Physics, University of Washington Lecturer in Philosophy, University of Konstanz Lecturer in Philosophy, University of Gießen Research Scientist, Department of Physics, University of Munich Fellow, Center for Philosophy of Science, University of Pittsburgh Assistant Professor in Philosophy, University of Konstanz Director, Research Group Philosophy, Probability and Modeling, University of Konstanz Lecturer in Philosophy, Department of Philosophy, Logic and Scientific Method, LSE Reader in Philosophy, Department of Philosophy, Logic and Scientific Method, LSE Director, Centre for Philosophy of Natural and Social Science, LSE
1989-1991
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