Several variant “Newtonian” theories of inertia and gravitation are described, and their scientific usefulness discussed. An examination of these theories is used to throw light on traditional epistemological and metaphysical questions about space and time. Finally these results are examined in the light of the changes induced by the transition from “Newtonian” to general relativistic spacetime.

In this paper I argue that human pattern recognition can be simulated by automata. In particular, I show that gestalt recognition and recognition of family resemblances are within the capabilities of sufficiently complex Turing machines. The argument rests on elementary facts of automata and computability theory which are used to explicate our preanalytic, informal concepts concerning gestalt patterns and recognition. The central idea is that of a machine which “knows” its own structure. Although the paper thus aims to support mechanism, especially as a framework hypothesis for perception, it contains suggestions for philosophy of science and philosophy of language as well. Some of these suggestions are sketched in the final section.

The use of negative probabilities is discussed for certain problems in which a stochastic process approach is indicated. An extension of probability theory to include signed (negative and positive) probabilities is outlined and both philosophical and axiomatic examinations of negative probabilities are presented. Finally, a class of applications illustrates the use and implications of signed probability theory.

The theory of the economics of research played a central role in the analysis of scientific method of Charles Sanders Peirce. The present paper describes Peirce's project as he saw it and then puts its machinery to work in an analysis of current issues in the philosophy of science. The aim is to show that, even apart from their historical interest, Peirce's ideas on this subject have a substantial systematic interest.

Hilbert's program attempts to show that our mathematical knowledge can be certain because we are able to know for certain the truths of elementary arithmetic. I argue that, in the absence of a theory of mathematical truth, Hilbert does not have a complete theory of our arithmetical knowledge. Further, while his deployment of a Kantian notion of intuition seems to promise an answer to scepticism, there is no way to complete Hilbert's epistemology which would answer to his avowed aims.

The intuitive notion of a statistical explanation has been explicated in different ways; recently it has even been claimed that there are no statistical explanations at all. In an attempt to clarify the disputed issue, the approaches adopted by Hempel, by Jeffrey, Salmon and Greeno, and by Stegmüller are analyzed critically, as far as they are concerned with the explanation of particular events. A solution of the controversy is proposed on the basis of a concept of explanation which refers essentially to a causal analysis of the explanandum. The possibility of statistical explanations, then, becomes contingent upon the existence of indeterministic causation. In conclusion, therefore, a conception of causality is sketched which shows that indeterminism and causal connection are compatible, at least from an epistemological point of view, so that statistical explanation can be seen to represent a specific and possibly irreducible scientific activity.