Inference to the Best Explanation

Inference to the Best Explanation

Author: Peter Lipton

Publisher: Taylor & Francis

Published: 2004

Total Pages: 236

ISBN-13: 9780415242035

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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

Author: Kevin McCain

Publisher: Oxford University Press

Published: 2017

Total Pages: 315

ISBN-13: 0198746903

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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

Author: H. Vahid

Publisher: Springer

Published: 2005-08-02

Total Pages: 245

ISBN-13: 0230596215

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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

Author: Gregory Johnson

Publisher: MIT Press

Published: 2017-01-06

Total Pages: 283

ISBN-13: 0262337770

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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.


Abductive Inference

Abductive Inference

Author: John R. Josephson

Publisher: Cambridge University Press

Published: 1996-08-28

Total Pages: 322

ISBN-13: 9780521575454

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This book is about abduction, 'the logic of Sherlock Holmes', and about how some kinds of abductive reasoning can be programmed in a computer. The work brings together Artificial Intelligence and philosophy of science and is rich with implications for other areas such as, psychology, medical informatics, and linguistics. It also has subtle implications for evidence evaluation in areas such as accident investigation, confirmation of scientific theories, law, diagnosis, and financial auditing. The book is about certainty and the logico-computational foundations of knowledge; it is about inference in perception, reasoning strategies, and building expert systems.


Inference to the Best Explanation

Inference to the Best Explanation

Author: Peter Lipton

Publisher: Psychology Press

Published: 2004

Total Pages: 240

ISBN-13: 9780415242028

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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.


The Material Theory of Induction

The Material Theory of Induction

Author: John D. Norton

Publisher: Bsps Open

Published: 2021

Total Pages: 0

ISBN-13: 9781773852539

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"The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. 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. Which that is, and its extent, is 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."--


Thought

Thought

Author: Gilbert H. Harman

Publisher: Princeton University Press

Published: 2015-03-08

Total Pages: 210

ISBN-13: 1400868998

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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.


Inference and Consciousness

Inference and Consciousness

Author: Timothy Chan

Publisher: Routledge

Published: 2019-12-20

Total Pages: 251

ISBN-13: 1351366734

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Inference has long been a central concern in epistemology, as an essential means by which we extend our knowledge and test our beliefs. Inference is also a key notion in influential psychological accounts of mental capacities, ranging from problem-solving to perception. Consciousness, on the other hand, has arguably been the defining interest of philosophy of mind over recent decades. Comparatively little attention, however, has been devoted to the significance of consciousness for the proper understanding of the nature and role of inference. It is commonly suggested that inference may be either conscious or unconscious. Yet how unified are these various supposed instances of inference? Does either enjoy explanatory priority in relation to the other? In what way, or ways, can an inference be conscious, or fail to be conscious, and how does this matter? This book brings together original essays from established scholars and emerging theorists that showcase how several current debates in epistemology, philosophy of psychology and philosophy of mind can benefit from more reflections on these and related questions about the significance of consciousness for inference.


Statistical and Inductive Inference by Minimum Message Length

Statistical and Inductive Inference by Minimum Message Length

Author: C.S. Wallace

Publisher: Springer Science & Business Media

Published: 2005-05-26

Total Pages: 456

ISBN-13: 9780387237954

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The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the ‘best’ explanation of observed data is the shortest. Further, an explanation is acceptable (i.e. the induction is justified) only if the explanation is shorter than the original data. This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science. Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining. C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focused primarily on the Minimum Message Length Principle.