" Vivid . . . immense clarity . . . the product of a brilliant and extremely forceful intellect." — Journal of the Royal Naval Scientific Service "Still a sheer joy to read." — Mathematical Gazette "Should be read by any student, teacher or researcher in mathematics." — Mathematics Teacher The originator of algebraic topology and of the theory of analytic functions of several complex variables, Henri Poincare (1854–1912) excelled at explaining the complexities of scientific and mathematical ideas to lay (...) readers. Science and Method, written in 1908, has been appreciated by a wide audience of nonprofessionals and translated into many languages. It defines the basic methodology and psychology of scientific discovery, particularly in regard to mathematics and mathematical physics. Drawing on examples from many fields, it explains how scientists analyze and choose their working facts, and it explores the nature of experimentation, theory, and the mind. 1914 edition. Translated by Francis Maitland. (shrink)

" Vivid . . . immense clarity . . . the product of a brilliant and extremely forceful intellect." — Journal of the Royal Naval Scientific Service "Still a sheer joy to read." — Mathematical Gazette "Should be read by any student, teacher or researcher in mathematics." — Mathematics Teacher The originator of algebraic topology and of the theory of analytic functions of several complex variables, Henri Poincare (1854–1912) excelled at explaining the complexities of scientific and mathematical ideas to lay (...) readers. Science and Method, written in 1908, has been appreciated by a wide audience of nonprofessionals and translated into many languages. It defines the basic methodology and psychology of scientific discovery, particularly in regard to mathematics and mathematical physics. Drawing on examples from many fields, it explains how scientists analyze and choose their working facts, and it explores the nature of experimentation, theory, and the mind. 1914 edition. Translated by Francis Maitland. (shrink)

We respect Herbert A. Simon as an established leader of empirical and logical analysis in the human sciences while we happily think of him as also the loner; of course he works with many colleagues but none can match him. He has been writing fruitfully and steadily for four decades in many fields, among them psychology, logic, decision theory, economics, computer science, management, production engineering, information and control theory, operations research, confirmation theory, and we must have omitted several. With all (...) of them, he is at once the technical scientist and the philosophical critic and analyst. When writing of decisions and actions, he is at the interface of philosophy of science, decision theory, philosophy of the specific social sciences, and inventory theory. When writing on causality, he is at the interface of methodology, metaphysics, logic and philosophy of physics, systems theory, and so on. Not that the interdisciplinary is his orthodoxy; we are delighted that he has chosen to include in this book both his early and little-appreciated treatment of straightforward philosophy of physics - the axioms of Newtonian mechanics, and also his fine papers on pure confirmation theory. (shrink)

Thomas S. Kuhn's classic book is now available with a new index.

In the fiftieth anniversary of this book’s first release, Winch’s argument remains as crucial as ever. Originally published in 1958, _The Idea of a Social Science and Its Relation to Philosophy_ was a landmark exploration of the social sciences, written at a time when that field was still young and had not yet joined the Humanities and the Natural Sciences as the third great domain of the Academy. A passionate defender of the importance of philosophy to a full understanding of (...) 'society' against those who would deem it an irrelevant 'ivory towers' pursuit, Winch draws from the works of such thinkers as Ludwig Wittgenstein, J.S. Mill and Max Weber to make his case. In so doing he addresses the possibility and practice of a comprehensive 'science of society'. (shrink)

In a new introduction, the authors describe how science and its social context were understood when this book was first published, and how the study of the history of science has changed since then.

In this paper I defend Kuhn’s view of scientific discovery, which involves two central tenets, namely that a scientific discovery always requires a discovery-that and a discovery-what, and that there are two kinds of scientific discovery, resulting from the temporal order of the discovery-that and the discovery-what. I identify two problems with Kuhn’s account and offer solutions to them from a realist stance. Alternatives to Kuhn’s account are also discussed.

In this paper I consider two accounts of scientific discovery, Robert Hudson's and Peter Achinstein's. I assess their relative success and I show that while both approaches are similar in promising ways, and address experimental discoveries well, they could address the concerns of the discovery sceptic more explicitly than they do. I also explore the implications of their inability to address purely theoretical discoveries, such as those often made in mathematical physics. I do so by showing that extending Hudson's or (...) Achinstein's account to such cases can sometimes provide a misleading analysis about who ought to be credited as a discoverer. In the final sections of the paper I work out some revisions to the Hudson/Achinstein account by drawing from a so-called structural realist view of theory change. Finally, I show how such a modified account of discovery can answer sceptical critics such as Musgrave or Woolgar without producing misleading analyses about who ought to receive credit as a discoverer in cases from the mathematical sciences. I illustrate the usefulness of this approach by providing an analysis of the case of the discovery of the Casimir effect. (shrink)

BACON.3 is a production system that discovers empirical laws. Although it does not attempt to model the human discovery process in detail, it incorporates some general heuristics that can lead to discovery in a number of domains. The main heuristics detect constancies and trends in data, and lead to the formulation of hypotheses and the definition of theoretical terms. Rather than making a hard distinction between data and hypotheses, the program represents information at varying levels of description. The lowest levels (...) correspond to direct observations, while the highest correspond to hypotheses that explain everything so for observed. To take advantage of this representation, BACON.3 has the ability to carry out and relate multiple experiments, collapse hypotheses with identical conditions, ignore differences to let similar concepts be treated as equal, and to discover and ignore irrelevant variables. BACON.3 has shown its generality by rediscovering versions of the ideal gas law, Kepler's third law of planetary motion, Coulomb's law, Ohm's law, and Galileo's laws for the pendulum and constant acceleration. (shrink)

The purpose of this paper is to motivate and defend a recognizable version of N. L. Wilson's "Principle of Charity" Doing so will involve: (1) distinguishing it fromthe significantly different versions of the Principle familiar through the work of Quine and Davidson; (2) showing that it is compatible with, among other things, both semantic externalism and "simulation" accounts of interpretation; and (3) explaining how it follows from plausible constraints relating to the connection between interpretation and self-interpretation. Finally, it will be (...) argued that Charity represents a type of "minimal individualism" that is closely tied to first person authority, and that endorsing Charity in our interpretations of others reflects a commitment to capturing, from the third-person starting point, their first-personal point of view. (shrink)

The Structure of Scientific Revolutions) and Alan Musgrave argue that it is impossible to precisely date discovery events and precisely identify discoverers. They defend this claim mainly on the grounds that so-called discoverers have in many cases misconceived the objects of discovery. In this paper, I argue that Kuhn and Musgrave arrive at their view because they lack a substantive account of how well discoverers must be able to conceptualize discovered objects. I remedy this deficiency by providing just such an (...) account, and with this account I delineate how one can secure precision regarding the identity of discoverers and the times of discoveries. Near the end of my paper I bring my target of criticism up-to-date; it turns out that Steve Woolgar adopts an approach to discovery kindred to those of Kuhn and Musgrave and I close the paper by discussing what is at stake in rebutting him. (shrink)

In the paper I explore the relations between a relatively new and quickly expanding branch of artificial intelligence –- the automated discovery systems –- and some new views advanced in the old debate over scientific realism. I focus my attention on one such system, GELL-MANN, designed in 1990 at Wichita State University. The program's task was to analyze elementary particle data available in 1964 and formulate an hypothesis (or hypotheses) about a `hidden', more simple structure of matter, or to put (...) it in contemporary terms –- the discovery of quarks. The central thesis of my paper is that systems like GELL-MANN not only discover (or rediscover) the hidden structure of matter, but also provide independent strong evidence in favor of scientific realism about entities involved in that structure. I make an attempt to show how an argument for scientific realism about sub-microscopic entities can be constructed that would parallel Ian Hacking's `argument from coincidence' presented with respect to microscopic objects in his famous book Representing and Intervening. (shrink)

In this follow-up to the highly successful _Ethnography Unbound,_ Michael Burawoy and nine colleagues break the bounds of conventional sociology, to explore the mutual shaping of local struggles and global forces. In contrast to the lofty debates between radical theorists, these nine studies excavate the dynamics and histories of globalization by extending out from the concrete, everyday world. The authors were participant observers in diverse struggles over extending citizenship, medicalizing breast cancer, dumping toxic waste, privatizing nursing homes, the degradation of (...) work, the withdrawal of welfare rights, and the elaboration of body politics. From their insider vantage points, they show how groups negotiate, circumvent, challenge, and even re-create the complex global web that entangles them. Traversing continents and extending over three years, this collaborative research developed its own distinctive method of "grounded globalization" to grasp the evaporation of traditional workplaces, the dissolution of enclaved communities, and the fluidity of identities. Forged between the local and global, these compelling essays make a powerful case for ethnography's insight into global dynamics. (shrink)

How is it possible to think new thoughts? What is creativity and can science explain it? And just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover the nature (...) of human creativity in the arts. The second edition of The Creative Mind has been updated to include recent developments in artificial intelligence, with a new preface, introduction and conclusion by the author. It is an essential work for anyone interested in the creativity of the human mind. (shrink)

Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gdel, Popper, Penrose, and Lucas, to address the hotly-contested question of whether computers might (...) become intellectually superior to human beings. (shrink)

This volume thus clears the ground for the productive and fruitful integration of these new developments into philosophy of science.

What is required for something to be evidence for a hypothesis? In this fascinating, elegantly written work, distinguished philosopher of science Peter Achinstein explores this question, rejecting typical philosophical and statistical theories of evidence. He claims these theories are much too weak to give scientists what they want--a good reason to believe--and, in some cases, they furnish concepts that mistakenly make all evidential claims a priori. Achinstein introduces four concepts of evidence, defines three of them by reference to "potential" evidence, (...) and characterizes the latter using a novel epistemic interpretation of probability. The resulting theory is then applied to philosophical and historical issues. Solutions are provided to the "grue," "ravens," "lottery," and "old-evidence" paradoxes, and to a series of questions. These include whether explanations or predictions furnish more evidential weight, whether individual hypotheses or entire theoretical systems can receive evidential support, what counts as a scientific discovery, and what sort of evidence is required for it. The historical questions include whether Jean Perrin had non-circular evidence for the existence of molecules, what type of evidence J. J. Thomson offered for the existence of the electron, and whether, as is usually supposed, he really discovered the electron. Achinstein proposes answers in terms of the concepts of evidence introduced. As the premier book in the fabulous new series Oxford Studies in Philosophy of Science, this volume is essential for philosophers of science and historians of science, as well as for statisticians, scientists with philosophical interests, and anyone curious about scientific reasoning. (shrink)

An essential work for anyone interested in the creativity of the human mind, "The Creative Mind" has been updated to include recent developments in artificial ...

The development of computational models to provide explanations of psychological data can be achieved using semi-automated search techniques, such as genetic programming. One challenge with these techniques is to control the type of model that is evolved to be cognitively plausible – a typical problem is that of “bloating”, where continued evolution generates models of increasing size without improving overall fitness. In this paper we describe a system for representing psychological data, a class of process-based models, and algorithms for evolving (...) models. We apply this system to the delayed match-to-sample task. We show how the challenge of bloating may be addressed by extending the fitness function to include measures of cognitive performance. (shrink)

Interpretation, in the sense relevant to hermeneutics, is an attempt to make clear, to make sense of an object of study. This object must, therefore, be a text or a text-analogue, which in some way is confused, incomplete, cloudy, seemingly contradictory--in one way or another, unclear. The interpretation aims to bring to light an underlying coherence or sense.

Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...) into mathematical proofs which drop out before the solution. Or better, they are like the hypotheses that drive science, which do not themselves need to be true. In other words, it does not matter whether or not intuitions are accurate as descriptions of the natural kinds that undergird philosophical concepts; the aims of conceptual analysis can still be met. (shrink)