Fuzzy sets as a basis for a theory of possibility

Evolutionary psychology is one of many biologically informed approaches to the study of human behavior. Along with cognitive psychologists, evolutionary psychologists propose that much, if not all, of our behavior can be explained by appeal to internal psychological mechanisms. What distinguishes evolutionary psychologists from many cognitive psychologists is the proposal that the relevant internal mechanisms are adaptations—products of natural selection—that helped our ancestors get around the world, survive and reproduce. To understand the central claims of evolutionary psychology we require an understanding of some key concepts in evolutionary biology, cognitive psychology, philosophy of science and philosophy of mind. Philosophers are interested in evolutionary psychology for a number of reasons. For philosophers of science —mostly philosophers of biology—evolutionary psychology provides a critical target. There is a broad consensus among philosophers of science that evolutionary psychology is a deeply flawed enterprise. For philosophers of mind and cognitive science evolutionary psychology has been a source of empirical hypotheses about cognitive architecture and specific components of that architecture. Philosophers of mind are also critical of evolutionary psychology but their criticisms are not as all-encompassing as those presented by philosophers of biology. Evolutionary psychology is also invoked by philosophers interested in moral psychology both as a source of empirical hypotheses and as a critical target.

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Stanford Encyclopedia of Philosophy

Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. The primary value of models is heuristic.

https://science.sciencemag.org/content/sci/263/5147/641.full.pdf

Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences

Criticism and the Growth of Knowledge. Edited by I. Lakatos and A. Musgrave. Pp. viii, 282. £3·50, paperback £1. 1970. (Cambridge University Press.)

https://core.ac.uk/download/pdf/374223.pdf

A manifesto for the equifinality thesis

This is an updated, revised and enlarged edition of Howson and Urbach's account of scientific method from the Bayesian standpoint. The book offers both an introduction to probability theory and a philosophical commentary on scientific inference. This new edition includes chapter exercises and extended material on topics such as regression analysis, distributions densities, randomisation and conditionalisation.

Scientific Reasoning: The Bayesian Approach.

Scientific Reasoning: The Bayesian Approach

9. Scientific Reasoning: the Bayesian Approach. By C. Howson and P. Urbach. ISBN 0 8126 9084 2 (hardbound), 0 8126 9085 0 (paperbound). Open Court, la Salle, 1989. 312 pp. $34.95 (hardbound), $16.95 (paperbound).

My title is intended to recall Terence Fine's excellent survey, Theories of Probability [1973]. I shall consider some developments that have occurred in the intervening years, and try to place some of the theories he discussed in what is now a slightly longer perspective. Completeness is not something one can reasonably hope to achieve in a journal article, and any selection is bound to reflect a view of what is salient. In a subject as prone to dispute as this, there will inevitably be many who will disagree with any author's views, and I take the opportunity to apologize in advance to all such people for what they will see as the narrowness and distortion of mine.

Theories of Probability

Introduction 1. Hume's Argument 2. Reliabilism 3. Realism and the No-Miracles Argument 4. Probabilism 5. Deductivisim 6. The Naturalistic Fallacy 7. 'A New Species of Logic' 8. The Logic of Scientific Discoveries 9. Chance and Probability Finale Coda: 'Of Miracles' References Index

Colin Howson

Papers

Scientific Reasoning: The Bayesian Approach.

Scientific Reasoning: The Bayesian Approach

Scientific Reasoning: The Bayesian Approach.

Theories of Probability

Hume's problem: induction and the justification of belief