In recent years, there have been some attempts to defend the legitimacy of a non-inductive generative logic of discovery whose strategy is to analyze a variety of constraints on the actual generation of explanatory hypotheses. These proposed new theories, however, are only weakly generative (relying on sophisticated processes of elimination) rather than strongly generative (embodying processes of correction).This paper develops a strongly generative theory which holds that we can come to know something new only as a variant of what we (...) already know — and that the novelty of this variant is not thereby eliminated nor beyond our powers of characterization, a double requirement that is vital for resolving the Meno paradox. In this light, the discovery of a new hypothesis is taken as the correction of an antecedent hypothesis in response to the discrepancies between the predictions generated by that antecedent hypothesis and the desired result (e.g. the actual data to be explained). This process comprises two parallel operations: the first, which demonstrates the positive role of the facts in generating new explanations, involves a mapping between multiple hypotheses and sets of predictions generated from those hypotheses, for the purpose of taking the actual data as a determinable variant of neighboring sets of predictions. This mapping permits the facts to indicate how corrective adjustments in the working hypothesis should be made; the second operation, which demonstrates the positive role of explanations in generating new facts, involves a mapping between differently construed versions of the actual data and the conceptualizations derived from those perceptual versions, for the purpose of taking the working hypothesis as a determinable variant of these neighboring conceptualizations. This mapping permits a given hypothesis to generate predictions increasingly closer to the actual facts. (shrink)

In this work the distinguished physical chemist and philosopher, Michael Polanyi, demonstrates that the scientist's personal participation in his knowledge, in ...

First published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

In this 1958 book, Professor Hanson turns to an equally important but comparatively neglected subject, the philosophical aspects of research and discovery.

Simonton examines the idea of the genius through his own theory called chance-configuration theory.

Inviting a reappraisal of the status of scientific knowledge, Andrew Pickering suggests that scientists are not mere passive observers and reporters of nature.

The main argument of this paper is that philosophical difficulties regarding scientific discovery arise mainly because philosophers base their arguments on a flawed picture of scientific research. Careful examination of N. R. Hanson's treatment of Kepler's discovery not only puts the rationality of this discovery beyond question, it also reveals what its rationality consists in. We can retrieve the point stressed by Hanson concerning the rational character of discoveries such as Kepler's even as we reject the type of "logical" analysis (...) he proposes. (shrink)

Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought (...) processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

Contributors; Preface; Introduction; Part I. Instruments in Experiments: 1. Scientific instruments: models of brass and aids to discovery; 2. Glass works: Newton’s prisms and the uses of experiment; 3. A viol of water or a wedge of glass; Part II. Experiment and Argument: 4. Galileo’s experimental discourse; 5. Fresnel, Poisson and the white spot: the role of successful predictions in the acceptance of scientific theories; 6. The rhetoric of experiment; Part III. Representing and Realising: 7. ’Magnetic curves’ and the magnetic (...) field: experimentation and representation in the history of a theory; 8. Artificial clouds, real particles; 9. Living in the material world; 10. Justification and experimentation; Part IV. The Constituency of Experiment: 11. Extraordinary experiment: electricity and the creation of life in Victorian England; 12. Why did Britain join CERN?; Part V. Hallmarks of Experiment: 13. From Kwajalein to Armageddon? Testing and the social construction of missile accuracy; 14. The epistemology of experiment; Select bibliography; Name index; Subject index. (shrink)

The main message of this volume is that the creative process of discovery is not a purely rational enterprise in the traditional sense which equates rationality with logical reasoning, yet it is a manifestation of a universal phenomenon ...

Papers presented cover: new approaches to evolutionary epistemology, new applications, critical evaluations, and the nature of the mind. Paper edition (unseen), $25.50. Annotation copyrighted by Book News, Inc., Portland, OR.

Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is written for a wide audience, (...) not just those professionals involved in computer design or artificial intelligence. It represents an important contribution to the ongoing discussion about what it means to be a machine, and what it means to be human. Book jacket. (shrink)

One of the major philosophical problems in physical sciences is what criteria should determine how scientific theories are selected and justified in practice and whether, in describing observable physical phenomena, such theories are effectively constrained to be unique. This book studies the example of a particular theory, the S-matrix theory. The S-matrix program was initiated by Heisenberg to deal with difficulties encountered in quantum field theories in describing particular phenomena. Since then, each theory has at different times been favored as (...) the explanation of observed phenomena. Certainly the S-matrix theory was adequate, feasible and fertile. However, the quantum field theory interpretation is now widely accepted and the study of alternative theories is all but abandoned. By examining the philosophy which influenced the turns in this story, the author explains how an adequate and viable theory fell out of favor and concludes with a critique of different methodologies in the history of science. (shrink)

Recent work in artificial intelligence, or AI, has produced programs capable of serious intellectual work in science. Results from AI are used to show that there exist mechanized procedures for discovering hypotheses and that these methods often lead to plausible hypotheses. The question to be answered is: By what methods can a computer program find plausible explanations of empirical data? To answer this, the common metaphor of search for describing several AI programs is examined followed by a look at examples (...) of programs actually constructed. Five types of search considered are: random, exhaustive, selective, heuristic, and opportunistic search. From there, the paper generalizes to some conclusions about mechanizing hypothesis formation. (shrink)

This paper is a critique of Darwinian models of the growth of scientific knowledge. Donald Campbell, Karl Popper, Stephen Toulmin, and others have discussed analogies between the development of biological species and the development of scientific knowledge: in both kinds of development, we find variation, selection, and transmission. It is argued that these similarities are superficial, and that closer examination of biological evolution and of the history of science shows that a non-Darwinian approach to historical epistemology is needed. An adequate (...) model of the growth of knowledge will have to go beyond evolutionary epistemology in discussing the role of intentional, abductive theory construction in scientific discovery, the selection of theories according to general criteria, the achievement of progress by sustained application of criteria, and the transmission of selected theories in highly organized scientific communities. (shrink)