Quitting Certainties

Quitting Certainties

This book presents a new Bayesian framework for modeling rational degrees of belief, called the Certainty-Loss Framework.

Author: Michael G. Titelbaum

Publisher: Oxford University Press

ISBN: 9780199658305

Category: Mathematics

Page: 345

View: 961

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.
Categories: Mathematics

Bayesian Philosophy of Science

Bayesian Philosophy of Science

MetaAnalysis of Free Response Studies 1992–2008: Assessing the Noise
Reduction Model in Parapsychology. Psychological Bulletin 136 ... Quitting
Certainties: A Bayesian Framework Modeling Degrees of Belief. Oxford: Oxford
University ...

Author: Jan Sprenger

Publisher:

ISBN: 9780199672110

Category: Bayesian statistical decision theory

Page: 384

View: 165

How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as beingcharacterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in "objective science", Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees ofbelief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference - the leading theory of rationality in social science - with the practice of 21st century science.Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention tomethodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners.
Categories: Bayesian statistical decision theory

The Probabilistic Foundations of Rational Learning

The Probabilistic Foundations of Rational Learning

Thurstone, L. L. 1927. A Law of Comparative Judgment. Psychological Review,
34, 266–270. Titelbaum, M. G. 2012. Quitting Certainties: A Bayesian Framework
Modeling Degrees of Belief. Oxford: Oxford University Press. Tversky, A. 1972.

Author: Simon M. Huttegger

Publisher: Cambridge University Press

ISBN: 9781107115323

Category: Philosophy

Page: 256

View: 956

This book extends Bayesian epistemology to develop new approaches to general rational learning within the framework of probability theory.
Categories: Philosophy

Reasons without Persons

Reasons without Persons

Titelbaum, Michael. 2010. “Tell Me You Love Me: Bootstrapping, Externalism,
and No-Lose Epistemology.” Philosophical Studies 149:119–34. Titelbaum,
Michael. 2013. Quitting Certainties: A Bayesian Framework Modeling Degrees of
Belief ...

Author: Brian Hedden

Publisher: OUP Oxford

ISBN: 9780191046575

Category: Philosophy

Page: 240

View: 605

Brian Hedden defends a radical view about the relationship between rationality, personal identity, and time. On the standard view, personal identity over time plays a central role in thinking about rationality. This is because, on the standard view, there are rational norms for how a person's attitudes and actions at one time should fit with her attitudes and actions at other times, norms that apply within a person but not across persons. But these norms are problematic. They make what you rationally ought to believe or do depend on facts about your past that aren't part of your current perspective on the world, and they make rationality depend on controversial, murky metaphysical facts about what binds different instantaneous snapshots (or 'time-slices') into a single person extended in time. Hedden takes a different approach, treating the relationship between different time-slices of the same person as no different from the relationship between different people. For purposes of rational evaluation, a temporally extended person is akin to a group of people. The locus of rationality is the time-slice rather than the temporally extended agent. Taking an impersonal, time-slice-centric approach to rationality yields a unified approach to the rationality of beliefs, preferences, and actions where what rationality demands of you is solely determined by your evidence, with no special weight given to your past beliefs or actions.
Categories: Philosophy

Quitting Certainties

Quitting Certainties

A Doxastic Modeling Framework Michael Gaard Titelbaum ... a kind of situation
that is supposed to be a problem for Bayesian frameworks : situations in which
the set of claims to which an agent assigns degrees of belief changes over time .

Author: Michael Gaard Titelbaum

Publisher:

ISBN: UCAL:C3488659

Category:

Page: 612

View: 329

Categories:

Encyclopedia of Internet Technologies and Applications

Encyclopedia of Internet Technologies and Applications

Recently a new field of modelling has opened with the dynamic analysis of traffic
and its structure. ... For this purpose, the Bayesian framework (Vardi, 1996) and
neural networks (Doulamis, Doulamis, & Kollias, 2003) have been proposed. ...
There can never be certainty, but as evidence accumulates, the degree of belief
in a hypothesis changes. ... several end to end traffic users entering the network
into one edge router (the origin) and exiting at an other edge router (the
destination).

Author: Freire, Mario

Publisher: IGI Global

ISBN: 9781591409946

Category: Computers

Page: 750

View: 988

Provides the most thorough examination of Internet technologies and applications for researchers in a variety of related fields. For the average Internet consumer, as well as for experts in the field of networking and Internet technologies.
Categories: Computers

Clinical Flow Cytometry

Clinical Flow Cytometry

A stopping rule and clustering method of wide applicability . Botany Gazette 1984
... Minsky M . A framework for representing knowledge . In : Winston P , ed . ...
Duda RO , Hart PE , Nilsson NJ : Subjective Bayesian methods for rulebased
inference systems . Proc AFIPS Nat ... Fuzzy mathematical models in engineering
and management science . Amsterdam ... data to arrive at a fixed set of solutions
with certainty . ... A scheme for assigning a degree of belief to a fact or rule .
Cluster ...

Author: Kenneth D. Bauer

Publisher:

ISBN: UOM:39015028450073

Category: Medical

Page: 635

View: 593

Aimed at pathologists, oncologists, haematologists and laboratory medicine specialists, this book on flow cytometry addresses such topics as fundamental principles, basic techniques and clinical applications, with an emphasis on its relation to the biology of human cancers and other diseases. Chapters on the clinical application of flow cytometry include its use in diagnosing lymphomas and a wide variety of other cancers. Each organ-system chapter is followed by a clinical commentary that provides additional perspectives on the diagnosis utility of this technology.
Categories: Medical

Stanford Bulletin

Stanford Bulletin

Issues from the range of human affairs test the student' s framework for ethical
judgment. ... Optimal stopping. ... Team decisions and stochastic programs;
quadratic costs and certainty equivalents. ... Topics : how to organize the decision
conversation, the role of the decision analysis cycle and the model sequence, ...
Object is to prepare doctoral students for research and to enable all to
understand the discipline at the most fundamental levels. ... Belief propagation
and revision.

Author:

Publisher:

ISBN: STANFORD:36105020622572

Category:

Page:

View: 949

Categories: