This paper investigates the revolutionary conceptual changes that took place when the phlogiston theory of Stahl was replaced by the oxygen theory of Lavoisier. Using techniques drawn from artificial intelligence, it represents the crucial stages in Lavoisier's conceptual development from 1772 to 1789. It then sketches a computational theory of conceptual change to account for Lavoisier's discovery of the oxygen theory and for the replacement of the phlogiston theory.

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

Against the traditional view, Alvin Goldman argues that logic, probability theory, and linguistic analysis cannot by themselves delineate principles of rationality or justified belief. The mind's operations must be taken into account.

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)

Many people find themselves dissatisfied with recent linguistic philosophy, and yet know that language has always mattered deeply to philosophy and must in some sense continue to do so. Ian Hacking considers here some dozen case studies in the history of philosophy to show the different ways in which language has been important, and the consequences for the development of the subject. There are chapters on, among others, Hobbes, Berkeley, Russell, Ayer, Wittgenstein, Chomsky, Feyerabend and Davidson. Dr Hacking ends by (...) speculating about the directions in which philosophy and the study of language seem likely to go. The book will provide students with a stimulating, broad survey of problems in the theory of meaning and the development of philosophy, particularly in this century. The topics treated in the philosophy of language are among the central, current concerns of philosophers, and the historical framework makes it possible to introduce concretely and intelligibly all the main theoretical issues. (shrink)

It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.

The question of how concepts are formed was central for positivist and operationalist philosophers concerned to root scientific thought directly in experience. Although the positivist program has been abandoned, the current interest in the philosophy of scientific discovery shows the need for a theory of conceptual development. This paper offers a theory of how new concepts can arise, not by abstraction from experience or by definition, but by conceptual combination. Such combination produces a new concept as a non-linear, non-definitional amalgam (...) of existing concepts. After proposing rules intended to account for a variety of mundane cases of conceptual combination, the paper presents several illustrations of how scientific concepts have arisen through combination. (shrink)