Isaac Newton's Scientific Method examines Newton's argument for universal gravity and his application of it to resolve the problem of deciding between geocentric and heliocentric world systems by measuring masses of the sun and planets. William L. Harper suggests that Newton's inferences from phenomena realize an ideal of empirical success that is richer than prediction. Any theory that can achieve this rich sort of empirical success must not only be able to predict the phenomena it purports to explain, but also (...) have those phenomena accurately measure the parameters which explain them. Harper explores the ways in which Newton's method aims to turn theoretical questions into ones which can be answered empirically by measurement from phenomena, and to establish that propositions inferred from phenomena are provisionally accepted as guides to further research. This methodology, guided by its rich ideal of empirical success, supports a conception of scientific progress that does not require construing it as progress toward Laplace's ideal limit of a final theory of everything, and is not threatened by the classic argument against convergent realism. Newton's method endorses the radical theoretical transformation from his theory to Einstein's. Harper argues that it is strikingly realized in the development and application of testing frameworks for relativistic theories of gravity, and very much at work in cosmology today. (shrink)

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements (...) of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation. (shrink)

This paper uses Popper's treatment of probability and an epistemic constraint on probability assignments to conditionals to extend the Bayesian representation of rational belief so that revision of previously accepted evidence is allowed for. Results of this extension include an epistemic semantics for Lewis' theory of counterfactual conditionals and a representation for one kind of conceptual change.

The eight papers in this book are drawn from two conferences that honored Lewis White Beck, an influential Kant scholar.

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements (...) of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton’s argument from orbital phenomena to the inverse‐square law of gravitation. (shrink)

Skyrms' investigations of dynamic deliberation are traced through his book of 1990 and his subsequent investigation of dynamic deliberation based on inductive rules to his recent results about chaos generated by evolutionary game dynamics. It is argued that the dynamics studied in the book, and the inductive dynamics as well, need to be supplemented to yield the correct recommendation in an example game. Some features about information feedback are pointed out. Finally, it is suggested that more work is needed to (...) assess whether Skyrms' results about chaos have any interesting implications for plausible game theoretic representations of interactions among human agents. (shrink)

Classic examples of ostensive geometrical constructions are used to clarify Kant’s account of how they provide knowledge of claims about rigid bodies we can observe and manipulate. It is argued that on Kant’s account claims warranted by ostensive constructions must be limited to scales and tolerances corresponding to our perceptual competencies. This limitation opens the way to view Riemann’s work as contributing valuable conceptual resources for extending geometrical knowledge beyond the bounds of observation. It is argued that neither Reichenbach’s descriptions (...) of non-Euclidean visualization nor his arguments for conventionalism about geometry undercut this view of Kant’s account of geometrical knowledge. (shrink)