Inference to the Best Explanation

Inference to the Best Explanation PDF Author: Peter Lipton
Publisher: Taylor & Francis
ISBN: 9780415242035
Category : Philosophy
Languages : en
Pages : 236

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Book Description
Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.

Inference to the Best Explanation

Inference to the Best Explanation PDF Author: Peter Lipton
Publisher: Taylor & Francis
ISBN: 9780415242035
Category : Philosophy
Languages : en
Pages : 236

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Book Description
Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.

Best Explanations

Best Explanations PDF Author: Kevin McCain
Publisher: Oxford University Press
ISBN: 0198746903
Category : Philosophy
Languages : en
Pages : 315

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Book Description
Twenty philosophers offer new essays examining the form of reasoning known as inference to the best explanation - widely used in science and in our everyday lives, yet still controversial. Best Explanations represents the state of the art when it comes to understanding, criticizing, and defending this form of reasoning.

Epistemic Justification and the Skeptical Challenge

Epistemic Justification and the Skeptical Challenge PDF Author: H. Vahid
Publisher: Springer
ISBN: 0230596215
Category : Philosophy
Languages : en
Pages : 236

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Book Description
This book explores the concept of epistemic justification and our understanding of the problem of skepticism. Providing critical examination of key responses to the skeptical challenge, Hamid Vahid presents a theory which is shown to work alongside the internalism/externalism issue and the thesis of semantic externalism, with a deontological conception of justification at its core.

Argument and Inference

Argument and Inference PDF Author: Gregory Johnson
Publisher: MIT Press
ISBN: 0262337770
Category : Philosophy
Languages : en
Pages : 283

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Book Description
A thorough and practical introduction to inductive logic with a focus on arguments and the rules used for making inductive inferences. This textbook offers a thorough and practical introduction to inductive logic. The book covers a range of different types of inferences with an emphasis throughout on representing them as arguments. This allows the reader to see that, although the rules and guidelines for making each type of inference differ, the purpose is always to generate a probable conclusion. After explaining the basic features of an argument and the different standards for evaluating arguments, the book covers inferences that do not require precise probabilities or the probability calculus: the induction by confirmation, inference to the best explanation, and Mill's methods. The second half of the book presents arguments that do require the probability calculus, first explaining the rules of probability, and then the proportional syllogism, inductive generalization, and Bayes' rule. Each chapter ends with practice problems and their solutions. Appendixes offer additional material on deductive logic, odds, expected value, and (very briefly) the foundations of probability. Argument and Inference can be used in critical thinking courses. It provides these courses with a coherent theme while covering the type of reasoning that is most often used in day-to-day life and in the natural, social, and medical sciences. Argument and Inference is also suitable for inductive logic and informal logic courses, as well as philosophy of sciences courses that need an introductory text on scientific and inductive methods.

Inference, Explanation, and Other Frustrations

Inference, Explanation, and Other Frustrations PDF Author: John Earman
Publisher: Univ of California Press
ISBN: 0520309871
Category : Philosophy
Languages : en
Pages : 314

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Book Description
These provocative essays by leading philosophers of science exemplify and illuminate the contemporary uncertainty and excitement in the field. The papers are rich in new perspectives, and their far-reaching criticisms challenge arguments long prevalent in classic philosophical problems of induction, empiricism, and realism. By turns empirical or analytic, historical or programmatic, confessional or argumentative, the authors' arguments both describe and demonstrate the fact that philosophy of science is in a ferment more intense than at any time since the heyday of logical positivism early in the twentieth century. Contents: “Thoroughly Modern Meno,” Clark Glymour and Kevin Kelly “The Concept of Induction in the Light of the Interrogative Approach to Inquiry,” Jaakko Hintikka “Aristotelian Natures and Modern Experimental Method,” Nancy Cartwright “Genetic Inference: A Reconsideration of “David Hume's Empiricism,” Barbara D. Massey and Gerald J. Massey “Philosophy and the Exact Sciences: Logical Positivism as a Case Study,” Michael Friedman “Language and Interpretation: Philosophical Reflections and Empirical Inquiry,” Noam Chomsky “Constructivism, Realism, and Philosophical Method,” Richard Boyd “Do We Need a Hierarchical Model of Science?” Diderik Batens “Theories of Theories: A View from Cognitive Science,” Richard E. Grandy “Procedural Syntax for Theory Elements,” Joseph D. Sneed “Why Functionalism Didn't Work,” Hilary Putnam “Physicalism,” Hartry Field This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1992.

Abductive Inference

Abductive Inference PDF Author: John R. Josephson
Publisher: Cambridge University Press
ISBN: 9780521575454
Category : Computers
Languages : en
Pages : 322

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Book Description
This book analyses abduction as an information-processing phenomenon.

Material Theory of Induction

Material Theory of Induction PDF Author: John D. Norton
Publisher: Bsps Open
ISBN: 9781773852751
Category : Philosophy
Languages : en
Pages : 544

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Book Description
The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a single formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it.The content of that logic and where it can be applied are determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference.

Inference to the Best Explanation

Inference to the Best Explanation PDF Author: Peter Lipton
Publisher: Psychology Press
ISBN: 9780415242028
Category : Philosophy
Languages : en
Pages : 240

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Book Description
Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.

Thought

Thought PDF Author: Gilbert H. Harman
Publisher: Princeton University Press
ISBN: 1400868998
Category : Philosophy
Languages : en
Pages : 210

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Book Description
Thoughts and other mental states are defined by their role in a functional system. Since it is easier to determine when we have knowledge than when reasoning has occurred, Gilbert Harman attempts to answer the latter question by seeing what assumptions about reasoning would best account for when we have knowledge and when not. He describes induction as inference to the best explanation, or more precisely as a modification of beliefs that seeks to minimize change and maximize explanatory coherence. Originally published in 1973. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Reliable Reasoning

Reliable Reasoning PDF Author: Gilbert Harman
Publisher: MIT Press
ISBN: 0262517345
Category : Psychology
Languages : en
Pages : 119

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Book Description
The implications for philosophy and cognitive science of developments in statistical learning theory. In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT. After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.