The Analysis of Matter is perhaps best known for marking Russell's rejection of phenomenalism and his development of a variety of Lockean representationalism–-Russell's causal theory of perception. This occupies Part 2 of the work. Part 1, which is certainly less well known, contains many observations on twentieth-century physics. Unfortunately, Russell's discussion of relativity and the foundations of physical geometry is carried out in apparent ignorance of Reichenbach's and Carnap's investigations in the same period. The issue of conventionalism in its then (...) contemporary form is simply not discussed. The only writers of the period who appear to have had any influence on Russell's conception of the philosophical issues raised by relativity were Whitehead and Eddington. Even the work of A. A. Robb fails to receive any extended discussion;1 although Robb's causal theory is certainly relevant to many of Russell's concerns, especially those voiced in Part 3, regarding the construction of points and the topology of space-time. In the case of quantum mechanics, the idiosyncrasy of Russell's selection of topics is more understandable, since the Heisenberg and Schrödinger theories were only just discovered. Nevertheless, it seems bizarre to a contemporary reader that Russell should have given such emphasis2 to G. N. Lewis's suggestion that an atom emits light only when there is another atom to receive it–-a suggestion reminiscent of Leibniz, and one to which Russell frequently returns. In short, the philosophical problems of modern physics with which Russell deals seem remote from the perspective of post-positivist philosophy of physics. (shrink)

Selection type theories solve adaptation problems. Natural selection, clonal selection for antibody production, and selective theories of higher brain function are examples. An abstract characterization of typical selection processes is generated by analyzing and extending previous work on the nature of natural selection. Once constructed, this abstraction provides a useful tool for analyzing the nature of other selection theories and may be of use in new instances of theory construction. This suggests the potential fruitfulness of research to find other theory (...) types and construct their abstractions. (shrink)

A theory of analogy must describe how the meaning of an analogy is derived from the meanings of its parts. In the structure‐mapping theory, the interpretation rules are characterized as implicit rules for mapping knowledge about a base domain into a target domain. Two important features of the theory are (a) the rules depend only on syntactic properties of the knowledge representation, and not on the specific content of the domains; and (b) the theoretical framework allows analogies to be distinguished (...) cleanly from literal similarity statements, applications of abstractions, and other kinds of comparisons.Two mapping principles are described: (a) Relations between objects, rather than attributes of objects, are mapped from base to target; and (b) The particular relations mapped are determined by systematicity, as defined by the existence of higher‐order relations. (shrink)

With this treatise, an insightful exploration of the probabilistic connection between philosophy and the history of science, the famous economist breathed new life into studies of both disciplines. Originally published in 1921, this important mathematical work represented a significant contribution to the theory regarding the logical probability of propositions. Keynes effectively dismantled the classical theory of probability, launching what has since been termed the “logical-relationist” theory. In so doing, he explored the logical relationships between classifying a proposition as “highly probable” (...) and as a “justifiable induction.” Unabridged republication of the classic 1921 edition. (shrink)

2014 Reprint of 1954 American Edition. Full facsimile of the original edition, not reproduced with Optical Recognition Software. This two volume classic comprises two titles: "Patterns of Plausible Inference" and "Induction and Analogy in Mathematics." This is a guide to the practical art of plausible reasoning, particularly in mathematics, but also in every field of human activity. Using mathematics as the example par excellence, Polya shows how even the most rigorous deductive discipline is heavily dependent on techniques of guessing, inductive (...) reasoning, and reasoning by analogy. In solving a problem, the answer must be guessed at before a proof can be given, and guesses are usually made from a knowledge of facts, experience, and hunches. The truly creative mathematician must be a good guesser first and a good prover afterward; many important theorems have been guessed but no proved until much later. In the same way, solutions to problems can be guessed, and a god guesser is much more likely to find a correct solution. This work might have been called "How to Become a Good Guesser."-From the Dust Jacket. (shrink)

Here the author of How to Solve It explains how to become a "good guesser." Marked by G. Polya's simple, energetic prose and use of clever examples from a wide range of human activities, this two-volume work explores techniques of guessing, inductive reasoning, and reasoning by analogy, and the role they play in the most rigorous of deductive disciplines.

Introduction: Science and Common Sense Long before the beginnings of modern civilization, men ac- quired vast funds of information about their environment. ...

Ernst Mach is the only person whom Einstein included on both the list of physicists he considered his true precursors, and the list of the philosophers who had most affected him. Einstein scholars have been less generous in their estimation of Mach's contributions to Einstein's work, and even amongst the more generous of them, Mach's great achievements in physics are seldom mentioned in this context. This is odd, considering Mach was nominated for the Nobel Prize in Physics three times. In (...) this paper, I examine some of Mach's work in physics that bears conceptually on Einstein's 1905 paper on Special Relativity ("On The Electrodynamics of Moving Bodies"). Mach was the first to give the correct explanation of the Doppler Effect, and he presented it in a way that Einstein echoes in his 1905 paper: laying out two apparently contradictory principles and showing how both can be retained. It is also notable that Mach's explanation was explicit about not relying on the existence of a medium of transmission for the propagation of light waves. In his work on supersonic shock waves, Mach invokes the constancy of the velocity of sound (i.e., its independence of the motion of the sound source) , just as he had invoked the constancy of the velocity of light in his work on the Doppler Effect for Light. I examine the analogies between light and sound that were drawn upon by Einstein and Mach, as well as one analogy that Einstein could have, but did not make: Cherenkov radiation, or "singing electrons", i.e., cases in which the sound of light in the medium of transmission is exceeded, which results in an optical analogue of supersonic shock waves. (shrink)

Three different ways in which systems of axioms can contribute to the discovery of new notions are presented and they are illustrated by the various ways in which lattices have been introduced in mathematics by Schröder et al. These historical episodes reveal that the axiomatic method is not only a way of systematizing our knowledge, but that it can also be used as a fruitful tool for discovering and introducing new mathematical notions. Looked at it from this perspective, the creative (...) aspect of axiomatics for mathematical practice is brought to the fore. (shrink)

Analogy as a scientific method has been criticized during the last decades; only for heuristic purposes it has been accepted. On the other side especially proportional analogies have a long tradition in European thought since Plato and Aristotle, for, as Aristotle puts it, analogies allow a connection between different and unbridgeable ontological areas. As examples for such connections the analogia entis of Thomas of Aquino and the Kantian Analogies of Experience are discussed. They give us hints for a new view (...) of analogies, which during the Middle Ages were not only of heuristic value, but were accepted as a proof: Analogies do not only produce hypotheses, moreover, they build up new views of the world, they are the background of paradigms, for they create structures by introducing similarities and proportions. (shrink)

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"--metaphors that can shape our perceptions and actions without our ever noticing them. In (...) this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language. (shrink)

This article deals with six aspects of analogical thinking in mathematics: 1. Platonism and continuity principle or the “geometric voices of analogy” (as Kepler put it), 2. analogies and the surpassing of limits, 3. analogies and rule stretching, 4. analogies and concept stretching, 5. language and the art of inventing, 6. translation, or constructions instead of discovery. It takes especially into account the works of Kepler, Wallis, Leibniz, Euler, and Laplace who all underlined the importance of analogy in finding out (...) new mathematical truth. But the meaning of analogy varies with the different authors. Isomorphic structures are interpreted as an outcome of analogical thinking. (shrink)

A multiple analogy is a structured comparison in which several sources are likened to a target. In "Multiple analogies in science and philosophy," Shelley provides a thorough account of the cognitive representations and processes that participate in multiple analogy formation. Through analysis of real examples taken from the fields of evolutionary biology, archaeology, and Plato's "Republic," Shelley argues that multiple analogies are not simply concatenated single analogies but are instead the general form of analogical inference, of which single analogies are (...) a special case. The result is a truly general cognitive model of analogical inference.Shelley also shows how a cognitive account of multiple analogies addresses important philosophical issues such as the confidence that one may have in an analogical explanation, and the role of analogy in science and philosophy.This book lucidly demonstrates that important questions regarding analogical inference cannot be answered adequately by consideration of single analogies alone. (shrink)

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary (...) emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F. (shrink)

There are several key ingredients common to the various forms of model-based reasoning considered in this book. The term ‘model’ comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations and are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. The book’s contributors are researchers active in the area of creative reasoning in science and technology.

This book is about the methods used for unifying different scientific theories under one all-embracing theory. The process has characterized much of the history of science and is prominent in contemporary physics; the search for a 'theory of everything' involves the same attempt at unification. Margaret Morrison argues that, contrary to popular philosophical views, unification and explanation often have little to do with each other. The mechanisms that facilitate unification are not those that enable us to explain how or why (...) phenomena behave as they do. A feature of this book is an account of many case studies of theory unification in nineteenth- and twentieth-century physics and of how evolution by natural selection and Mendelian genetics were unified into what we now term evolutionary genetics. (shrink)

This paper is a contribution to the question of how aspects of science have been perceived through history. In particular, I will discuss how the contribution of axiomatics to the development of science and mathematics was viewed in 20th century philosophy of science and philosophy of mathematics. It will turn out that in connection with scientific methodology, in particular regarding its use in the context of discovery, axiomatics has received only very little attention. This is a rather surprising result, since (...) axiomatizations have been employed extensively in mathematics, science, and also by the philosophers themselves. (shrink)

We examine the use of analogy in human thinking from the perspective of a multiconstraint theory, which postulates three basic types of constraints: similarity, structure and purpose. The operation of these constraints is apparent in both laboratory experiments on analogy and in naturalistic settings, including politics, psychotherapy, and scientific research. We sketch how the multiconstraint theory can be implemented in detailed computational simulations of the analogical human mind.