First published in 1978, this reissue presents a seminal philosophical work by professor Putnam, in which he puts forward a conception of knowledge which makes ethics, practical knowledge and non-mathematic parts of the social sciences just as much parts of 'knowledge' as the sciences themselves. He also rejects the idea that knowledge can be demarcated from non-knowledge by the fact that the former alone adheres to 'the scientific method'. The first part of the book consists of Professor Putnam's John Locke (...) lectures, delivered at the University of Oxford in 1976, offering a detailed examination of a 'physicalist' theory of reference against a background of the works of Tarski, Carnap, Popper, Hempel and Kant. The analysis then extends to notions of truth, the character of linguistic enquiry and social scientific enquiry in general, interconnecting with the great metaphysical problem of realism, the nature of language and reference, and the character of ourselves. (shrink)

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of _Inference to the Best Explanation_ has also been updated throughout and includes a new bibliography. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1984.

The aim of the text is to evaluate Peirce's evolutionary cosmology and to try to make sense of the mixture of idealistic and naturalistic elements that may be found in it, especially by focusing on Peirce's conception of logical norms and rationality, and on the links that may be drawn between such views and some evolutionary themes in the contemporary debates on norms, belief and knowledge.

This book is available either individually, or as part of the specially-priced Arguments of the Philosphers Collection.

Metaphysicians speak of laws of nature in terms of necessity and universality; scientists, in terms of symmetry and invariance. In this book van Fraassen argues that no metaphysical account of laws can succeed. He analyzes and rejects the arguments that there are laws of nature, or that we must believe there are, and argues that we should disregard the idea of law as an adequate clue to science. After exploring what this means for general epistemology, the author develops the empiricist (...) view of science as a construction of models to represent the phenomena. (shrink)

Much as we would like to conceive empirical thought as rationally grounded in experience, pitfalls await anyone who tries to articulate this position, and ...

Une distinction entre la perception et la sensation a semblé nécessaire à la plupart des théoriciens et des philosophes, notamment parce que des sensations très différentes peuvent donner lieu à des perceptions identiques et des sensations qu'il y a tout lieu de croire identiques à des perceptions très différentes. Si tout le monde est en gros d'accord depuis longtemps pour admettre qu'il faut beaucoup plus que des sensations pour avoir une perception d'objet, il est plus difficile de dire en quoi (...) consiste cet élément supplémentaire qui doit s'ajouter à la sensation, et de quelle façon il réussit à se combiner avec elle pour donner la perception. On dit souvent que percevoir n'est pas sentir, mais avant tout juger. Mais l'identification de la perception à une simple forme particulière de jugement se révèle, à bien des égards, aussi insatisfaisante que pourrait l'être sa réduction à la simple sensation. A travers des auteurs comme Helmholtz, Husserl, Frege, essentiellement sur la nature du lien particulier qui unit la pensée à la sensation dans la perception et, plus précisément, sur la question de savoir si le jugement doit être considéré comme un accompagnement et une résultante de la perception qui le motive ou, au contraire, comme un constituant essentiel de celle-ci. (shrink)

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics (...) as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)

Reid's response to hume has traditionally been taken as begging all of hume's questions. One can, However, Find in reid an argument against hume's phenomenalistic skepticism. Reid's appeal to common sense is an attempt to call attention to the fact that we experience objects as external to us, Not as bundles of impressions. Still, Our access to these objects does arise out of sensations, Which are mental contents. Extending berkeley's idea of the "language of nature" reid suggests that language and (...) signification present apt theoretical models for explaining perception. Using this model, One can provide an answer to the argument from illusion. (shrink)

Abduction was first introduced in the epistemological context of scientific discovery. It was more recently analyzed in artificial intelligence, especially with respect to diagnosis analysis or ordinary reasoning. These two fields share a common view of abduction as a general process of hypotheses formation. More precisely, abduction is conceived as a kind of reverse explanation where a hypothesis H can be abduced from events E if H is a good explanation of E. The paper surveys four known schemes for abduction (...) that can be used in both fields. Its first contribution is a taxonomy of these schemes according to a common semantic framework based on belief revision. Its second contribution is to produce, for each non-trivial scheme, a representation theorem linking its semantic framework to a set of postulates. Its third contribution is to present semantic and axiomatic arguments in favor of one of these schemes, ordered abduction, which has never been vindicated in the literature. (shrink)

This monograph attempts to clarify one significant but much neglected aspect of Peirce's contribution to the philosophy of science. It was written in 1963 as my M. A. thesis at the Uni versity of Illinois. Since the topic is still neglected it is hoped that its pUblication will be of use to Peirce scholars. I should like to acknowledge my indebtedness to Dr. Max Fisch who broached this topic to me and who advised me con tinuously through its development, assisting (...) generously with his own insights and unpublished Peirce manuscripts. TABLE OF CONTENTS INTRODUCTION 1. A Current Issue in the Philosophy of Science 1 2. Peirce and His Theory of Abduction 5 3. The General Character of Abduction 7 PART I: THE EARLY THEORY 1. Peirce's Earliest Conception of Inference 11 2. Three Kinds of Inference and Three Figures of Syllogism 13 3. Ampliative Inference and Cognition 17 4. Induction and Hypothesis 20 5. The Method of Methods 23 PART II: THE LATER THEORY 1. The Transitional Period 28 2. Three Stages of Inquiry 31 3. Abduction and Guessing Instinct 35 4. Logic as a Normative Science 38 5. Hypothesis Construction and Selection 41 6. Abduction and Pragmatism 44 7. Economy of Research 47 8. Justification of Abduction 51 CONCLUSION 55 61 BIBLIOGRAPHY INTRODUCTION 1. (shrink)