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He argued that the entropy of statistical mechanics and the information entropy of information theory are basically the same thing.Consequently, statistical mechanics should be seen just as a particular application of a general tool of logical inference and information theory.where he emphasized a natural correspondence between statistical mechanics and information theory.In particular, Jaynes offered a new and very general rationale why the Gibbsian method of statistical mechanics works.And the three papers in the third section give a particularly interesting take on Carnap's view of induction, arguing that Carnap's considered view was actually much more subjectivist than we usually realize.I will discuss each of these sections in turn, giving what I take to be the upshot of the corresponding projects.
According to this principle, the distribution with maximal information entropy is the proper one. Carnapian Inductive Logic and Bayesian Statistics13. Bayesian Projectibility Brian Skyrms is Distinguished Professor of Logic and Philosophy of Science and Economics at the University of California, Irvine.Copyright (c) 2015, Per Christian Hansen All rights reserved.This book is a collection of previously published essays by Brian Skyrms.There have been almost no changes in any of the essays -- references to other papers in this volume, and references to papers by other authors that were forthcoming at the time, don't have updated publication information. This volume is certainly not comprehensive -- many topics that Skyrms has written on (causation, logic, and especially evolutionary game theory) are not represented at all.
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