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Quitting Certainties

Quitting Certainties Author Michael G. Titelbaum
ISBN-10 9780199658305
Release 2013
Pages 345
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Michael G. Titelbaum presents a new Bayesian framework for modeling rational degrees of belief, called the Certainty-Loss Framework. Subjective Bayesianism is epistemologists' standard theory of how individuals should change their degrees of belief over time. But despite the theory's power, it is widely recognized to fail for situations agents face every day. Michael G. Titelbaum argues that these failures stem from a common source: the inability ofConditionalization (Bayesianism's traditional updating rule) to model claims' going from certainty at an earlier time to less-than-certainty later on. He presents the first systematic, comprehensive Bayesianframework to accurately represent rational requirements on agents who undergo certainty loss. Titelbaum compares the framework he proposes to alternatives, then applies it to cases in epistemology, decision theory, the theory of identity, and the philosophy of quantum mechanics. This is the first unified Bayesian framework capable of accurately modeling rational requirements in cases involving memory loss and context-sensitivity. It has applications to suchdiverse topics as indifference principles, relations among epistemic peers, Everettian interpretations of quantum mechanics, the Fine-Tuning Argument for the multiverse, and the controversial SleepingBeauty problem. Titelbaum develops his ambitious project with rigor and philosophical subtlety: the book makes a major contribution to the literature on formal epistemology.



Bayesian Epistemology

Bayesian Epistemology Author Luc Bovens
ISBN-10 9780199269754
Release 2003
Pages 159
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Probabilistic models have much to offer to philosophy. We continually receive information from many sources - our senses, witnesses, scientific instruments - and assess whether to believe it. The authors provide a systematic Bayesian account of these features of reasoning.



Risk and Rationality

Risk and Rationality Author Lara Buchak
ISBN-10 9780199672165
Release 2013-11
Pages 260
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Lara Buchak sets out a new account of rational decision-making in the face of risk. She argues that the orthodox view (expected utility theory) is too narrow, and suggests an alternative, more permissive theory: one that allows individuals to pay attention to the worst-case or best-case scenario, and vindicates the ordinary decision-maker.



Decision Theory as Philosophy

Decision Theory as Philosophy Author Mark Kaplan
ISBN-10 0521624967
Release 1998-01-13
Pages 248
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Kaplan presents an accessible new variant on Bayesian decision theory.



Accuracy and the Laws of Credence

Accuracy and the Laws of Credence Author Richard Pettigrew
ISBN-10 9780198732716
Release 2016-04-14
Pages 256
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Richard Pettigrew offers an extended investigation into a particular way of justifying the rational principles that govern our credences (or degrees of belief). The main principles that he justifies are the central tenets of Bayesian epistemology, though many other related principles are discussed along the way. Pettigrew looks to decision theory in order to ground his argument. He treats an agent's credences as if they were a choice she makes between differentoptions, gives an account of the purely epistemic utility enjoyed by different sets of credences, and then appeals to the principles of decision theory to show that, when epistemic utility is measured inthis way, the credences that violate the principles listed above are ruled out as irrational. The account of epistemic utility set out here is the veritist's: the sole fundamental source of epistemic utility for credences is their accuracy. Thus, Pettigrew conducts an investigation in the version of epistemic utility theory known as accuracy-first epistemology.



Decision Theory with a Human Face

Decision Theory with a Human Face Author Richard Bradley
ISBN-10 9781107003217
Release 2017-10-31
Pages 346
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Explores how decision-makers can manage uncertainty that varies in both kind and severity by extending and supplementing Bayesian decision theory.



A Critical Introduction to Formal Epistemology

A Critical Introduction to Formal Epistemology Author Darren Bradley
ISBN-10 9781780937526
Release 2015-08-27
Pages 224
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Formal methods are changing how epistemology is being studied and understood. A Critical Introduction to Formal Epistemology introduces the types of formal theories being used and explains how they are shaping the subject. Beginning with the basics of probability and Bayesianism, it shows how representing degrees of belief using probabilities informs central debates in epistemology. As well as discussing induction, the paradox of confirmation and the main challenges to Bayesianism, this comprehensive overview covers objective chance, peer disagreement, the concept of full belief, and the traditional problems of justification and knowledge. Subjecting each position to a critical analysis, it explains the main issues in formal epistemology, and the motivations and drawbacks of each position. Written in an accessible language and supported study questions, guides to further reading and a glossary, positions are placed in an historic context to give a sense of the development of the field. As the first introductory textbook on formal epistemology, A Critical Introduction to Formal Epistemology is an invaluable resource for students and scholars of contemporary epistemology.



The Foundations of Bayesian Epistemology

The Foundations of Bayesian Epistemology Author Kenny Easwaran
ISBN-10 1138647713
Release 2017-09-30
Pages
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This book introduces students and researchers to the philosophical issues at play in the growing field of formal (or Bayesian) epistemology. It focuses not on how to do particular calculations but instead on the philosophical foundations at the convergence of belief and mathematical representation. Its central questions are: What is the nature of quantifying belief? What is the source of its norms? How is it reasonable to represent belief numerically? Accessible to those without any mathematical background, this book will become a much used classic in the field.



Adversarial Risk Analysis

Adversarial Risk Analysis Author David L. Banks
ISBN-10 9781498712408
Release 2015-06-30
Pages 224
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Flexible Models to Analyze Opponent Behavior A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. The book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent’s goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities.



Truth Meaning Experience

Truth  Meaning  Experience Author Anil Gupta
ISBN-10 9780190285722
Release 2011-12-09
Pages 288
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This volume reprints eight of Anil Gupta's essays, some with additional material. The essays bring a refreshing new perspective to central issues in philosophical logic, philosophy of language, and epistemology. Gupta argues that logical interdependence is legitimate, and that it provides a key to understanding a variety of topics of interest to philosophers--including truth, rationality, and experience. The essays are highly accessible and provide a good introduction to ideas Gupta has been developing over the last three decades.



Probability Theory

Probability Theory Author E. T. Jaynes
ISBN-10 9781139435161
Release 2003-04-10
Pages
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The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.



Bayes Or Bust

Bayes Or Bust Author John Earman
ISBN-10 0262050463
Release 1992
Pages 272
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There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh.



The Oxford Handbook of Probability and Philosophy

The Oxford Handbook of Probability and Philosophy Author Alan Hájek
ISBN-10 0199607613
Release 2016-02-18
Pages 880
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Probability theory is a key tool of the physical, mathematical, and social sciences. It has also been playing an increasingly significant role in philosophy: in epistemology, philosophy of science, ethics, social philosophy, philosophy of religion, and elsewhere. A case can be made that probability is as vital a part of the philosopher's toolkit as logic. Moreover, there is a fruitful two-way street between probability theory and philosophy: the theory informs much of the work of philosophers, and philosophical inquiry, in turn, has shed considerable light on the theory. This Handbook encapsulates and furthers the influence of philosophy on probability, and of probability on philosophy. Nearly forty articles summarise the state of play and present new insights in various areas of research at the intersection of these two fields. The articles will be of special interest to practitioners of probability who seek a greater understanding of its mathematical and conceptual foundations, and to philosophers who want to get up to speed on the cutting edge of research in this area. There is plenty here to entice philosophical readers who don't work especially on probability but who want to learn more about it and its applications. Indeed, this volume should appeal to the intellectually curious generally; after all, there is much here to be curious about. We do not expect all of this volume's audience to have a thorough training in probability theory. And while probability is relevant to the work of many philosophers, they often do not have much of a background in its formalism. With this in mind, we begin with 'Probability for Everyone--Even Philosophers', a primer on those parts of probability theory that we believe are most important for philosophers to know. The rest of the volume is divided into seven main sections: History; Formalism; Alternatives to Standard Probability Theory; Interpretations and Interpretive Issues; Probabilistic Judgment and Its Applications; Applications of Probability: Science; and Applications of Probability: Philosophy.



Chance and Temporal Asymmetry

Chance and Temporal Asymmetry Author Alastair Wilson
ISBN-10 9780199673421
Release 2014
Pages 297
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Chance and Temporal Asymmetry presents a collection of cutting-edge research papers in the metaphysics of science, tackling the perplexing philosophical problems raised by recent progress in the physics and metaphysics of chance and time. The aim of the volume is both to survey and summarize recent debates about chance and temporal asymmetry and to push them forward. Familiar approaches are subjected to searching new critiques, and bold new proposals aremade concerning (inter alia) the semantics of chance-attributions, the justification of the Principal Principle connecting chance and degree of belief, and the source of the temporal asymmetry of humanexperience. This volume sets the agenda for future work on time and chance, which are central to the emerging sub-field of metaphysics of science.



Bayesian Cognitive Modeling

Bayesian Cognitive Modeling Author Michael D. Lee
ISBN-10 9781107018457
Release 2014-04-03
Pages 280
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Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results.



Degrees of Belief

Degrees of Belief Author Franz Huber
ISBN-10 9781402091988
Release 2008-12-21
Pages 354
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This anthology is the first book to give a balanced overview of the competing theories of degrees of belief. It also explicitly relates these debates to more traditional concerns of the philosophy of language and mind and epistemic logic.



Bayesian Reasoning in Data Analysis

Bayesian Reasoning in Data Analysis Author Giulio D'Agostini
ISBN-10 9789814486095
Release 2003-06-13
Pages 352
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This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The basic ideas of this “new” approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide — under well-defined assumptions! — with “standard” methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework. Contents: Critical Review and Outline of the Bayesian Alternative:Uncertainty in Physics and the Usual Methods of Handling ItA Probabilistic Theory of Measurement UncertaintyA Bayesian Primer:Subjective Probability and Bayes' TheoremProbability Distributions (A Concise Reminder)Bayesian Inference of Continuous QuantitiesGaussian LikelihoodCounting ExperimentsBypassing Bayes' Theorem for Routine ApplicationsBayesian UnfoldingFurther Comments, Examples and Applications:Miscellanea on General Issues in Probability and InferenceCombination of Experimental Results: A Closer LookAsymmetric Uncertainties and Nonlinear PropagationWhich Priors for Frontier Physics?Conclusion:Conclusions and Bibliography Readership: Graduate students and researchers interested in probability and statistics and their applications in science, particularly the evaluation of uncertainty in measurements. Keywords:Probability;Bayesian Statistics;Error Theory;Measurement Uncertainty;MetrologyReviews:“… statistics textbooks must take seriously the need to teach the foundations of statistical reasoning from the beginning … D'Agostini's new book does this admirably, building an edifice of Bayesian statistical reasoning in the physical sciences on solid foundations.”Journal of the American Statistical Association