Ockham's razor, the principle of parsimony, states that simpler theories are better than theories that are more complex. It has a history dating back to Aristotle and it plays an important role in current physics, biology, and psychology. The razor also gets used outside of science - in everyday life and in philosophy. This book evaluates the principle and discusses its many applications. Fascinating examples from different domains provide a rich basis for contemplating the principle's promises and perils. It is (...) obvious that simpler theories are beautiful and easy to understand; the hard problem is to figure out why the simplicity of a theory should be relevant to saying what the world is like. In this book, the ABCs of probability theory are succinctly developed and put to work to describe two 'parsimony paradigms' within which this problem can be solved. (shrink)

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics (...) as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)

Douglas proposes a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, protecting the integrity and objectivity of science.

This book is a major contribution to decision theory, focusing on the question of when it is rational to accept scientific theories. The author examines both Bayesian decision theory and confirmation theory, refining and elaborating the views of Ramsey and Savage. He argues that the most solid foundation for confirmation theory is to be found in decision theory, and he provides a decision-theoretic derivation of principles for how many probabilities should be revised over time. Professor Maher defines a notion of (...) accepting a hypothesis, and then shows that it is not reducible to probability and that it is needed to deal with some important questions in the philosophy of science. A Bayesian decision-theoretic account of rational acceptance is provided together with a proof of the foundations for this theory. A final chapter shows how this account can be used to cast light on such vexed issues as verisimilitude and scientific realism. (shrink)

Studdert-Kennedy, Gerald, Evidence and Explanation in Social Science. ... Kauffman, Stuart, "Articulation of Parts Explanation in Biology and the Rational ...

Through his S–R model of statistical relevance, Wesley Salmon offers a solution to the scientific explanation of objectively improbable events.

Scientific Realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it to be. In his book, Stathis Psillos gives us a detailed and comprehensive study, which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and modern skeptical empiricism. Scientific Realism explains that the (...) history of science does not undermine the notion of scientific realism, and instead makes it reasonable to accept scientific as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

Exploring the role of values in scientific inquiry, Hugh Lacey examines the nature and meaning of values, and looks at challenges to the view, posed by postmodernists, feminists, radical ecologists, Third-World advocates and religious fundamentalists, that science is value free. He also focuses on discussions of 'development', especially in Third World countries. This paperback edition includes a new preface.

As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. _Four Decades of Scientific Explanation_ provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay (...) by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation,” which introduced the deductive-nomological model on which most work on scientific explanation was based for the following four decades, Salmon goes beyond this model's inherent basis of describing empirical knowledge to tells us “not only _what,_ but also _why_.” Salmon examines the predominant models in chronological order and describes their development, refinement, and criticism or rejection. _Four Decades of Scientific Explanation_ underscores the need for a consensus of approach and ongoing evaluations of methodology in scientific explanation, with the goal of providing a better understanding of natural phenomena. (shrink)

The paper aims at a perspicuous representation of Isaac Levi's pragmatist epistemology, spanning from the 1967 classic "Gambling with Truth" to his 2004 book on "Mild Contraction". Based on a formal framework for Levi's notion of inquiry, I analyse his decision-theoretic approach with truth and information as basic cognitive values, and with Shackle measures as emerging structures. Both cognitive values figure prominently in Levi's model of inductive belief expansion, but only the value of information is employed in his model of (...) belief contraction. I argue that the former model is more successful than the latter. (shrink)

Mereological nihilism says that there do not exist (in the fundamental sense) any objects with proper parts. A reason to accept it is that we can thereby eliminate 'part' from fundamental ideology. Many purported reasons to reject it - based on common sense, perception, and the possibility of gunk, for example - are weak. A more powerful reason is that composite objects seem needed for spacetime physics; but sets suffice instead.

Underdetermination arguments support the conclusion that no amount of empirical data can uniquely determine theory choice. The full content of a theory outreaches those elements of it (the observational elements) that can be shown to be true (or in agreement with actual observations).2 A number of strategies have been developed to minimize the threat such arguments pose to our aspirations to scientific knowledge. I want to focus on one such strategy: the invocation of additional criteria drawn from a pool of (...) cognitive or theoretical values, such as simplicity or generality, to bolster judgements about the worth of models, theories, and hypotheses. What is the status of such criteria? Larry Laudan, in Science and Values, argued that cognitive values could not be treated as self-validating, beyond justification, but are embedded in a three-way reticulational system containing theories, methods, and aims or values, which are involved in mutually supportive relationships (Laudan, 1984). My interest in this paper is not the purportedly self-validating nature of cognitive values, but their cognitive nature. Although Laudan rejects the idea that what he calls cognitive values are exempt from rational criticism and disagreement, he does seem to think that the reticulational system he identifies is independent of non-cognitive considerations. It is this cognitive/non-cognitive distinction that I wish to query in this paper. Let me begin by summarizing those of my own views about inquiry in which this worry about the distinction arises. (shrink)

It is notoriously difficult to spell out the norms of inductive reasoning in a neat set of rules. I explore the idea that explanatory considerations are the key to sorting out the good inductive inferences from the bad. After defending the crucial explanatory virtue of stability, I apply this approach to a range of inductive inferences, puzzles, and principles such as the Raven and Grue problems, and the significance of varied data and random sampling.

The debate about the rational and the social in science has sometimes been developed in the context of a distinction between epistemic and non-epistemic values. Paying particular attention to two important discussion in the last decade, by Longino and by McMullin, I argue that a fuller understanding of values in science ultimately requires abandoning the distinction itself. This is argued directly in terms of an analysis of the lack of clarity concerning what epistemic values are. I also argue that the (...) philosophical import of much of the feminist work in philosophy of science is restricted by any kind of strict adherence to the distinction. (shrink)

This is the table of contents and first chapter of Physics Meets Philosophy at the Planck Scale (Cambridge University Press, 2001), edited by Craig Callender and Nick Huggett. The chapter discusses the question of why there should be a theory of quantum gravity. We tackle arguments that purport to show that the gravitational field *must* be quantized. We then introduce various programs in quantum gravity and discuss areas where quantum gravity and philosophy seem to have something to say to each (...) other. (shrink)