Jan Sprenger and Stephan Hartmann offer a fresh approach to central topics in philosophy of science, including causation, explanation, evidence and scientific models. Their Bayesian approach uses the concept of degrees of belief to explain and to elucidate manifold aspects of scientific reasoning.
This book grew out of previously published papers of mine composed over a period of years; they have been reworked (sometimes beyond recognition) so as to form a reasonably coherent whole.
This book also shows how Bayesianism sheds new light on nearly all areas of knowledge, from philosophy to mathematics, science and engineering, but also law, politics and everyday decision-making.
A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability.
Bayesian Epistemology is an essential tool for anyone working on probabilistic methods in philosophy, and has broad implications for many other disciplines.
This is a new, fully updated, thoroughly revised, and substantially enlarged edition of Howson and Urbach's much-acclaimed account of scientific method from the Bayesian standpoint. Scientific Reasoning is both an...
Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science.
Page references are to the reprint in Neyman and Pearson's Joint Statistical Papers (Cambridge: Cambridge University Press, 1967). Pais, A. 1982. Subtle Is the Lord. Oxford: Clarendon. Paris, J. 1994. The Uncertain Reasoner's Companion.
Nomic Probability and the Foundations of Induction. Oxford University Press, New York. Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson, London. Priest, G. (1979). The logic of paradox. Journal of Philosophical Logic, ...
... Rhodes have developed a number of efficient algorithms which determine the parameters of a Bayesian net that maximise entropy. Their approach uses Lagrange multiplier methods on the original version of the entropy equation (eqn 5.1) ...
This is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today.