Foundations of Bayesianism [electronic resource] /

Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. The upshot is a plethora of new problems and directions for Bayesians to pursue. The book will be of interest to graduate students or researchers who wish to learn more about Bayesianism than can be provided by introductory textbooks to the subject. Those involved with the applications of Bayesian reasoning will find essential discussion on the validity of Bayesianism and its limits, while philosophers and others interested in pure reasoning will find new ideas on normativity and the logic of belief.

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Main Authors: Corfield, David. editor., Williamson, Jon. editor., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 2001
Subjects:Philosophy., Philosophy and science., Artificial intelligence., Probabilities., Statistics., Microeconomics., Philosophy of Science., Artificial Intelligence (incl. Robotics)., Probability Theory and Stochastic Processes., Statistics, general.,
Online Access:http://dx.doi.org/10.1007/978-94-017-1586-7
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spelling KOHA-OAI-TEST:1703012018-07-30T22:47:01ZFoundations of Bayesianism [electronic resource] / Corfield, David. editor. Williamson, Jon. editor. SpringerLink (Online service) textDordrecht : Springer Netherlands : Imprint: Springer,2001.engFoundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. The upshot is a plethora of new problems and directions for Bayesians to pursue. The book will be of interest to graduate students or researchers who wish to learn more about Bayesianism than can be provided by introductory textbooks to the subject. Those involved with the applications of Bayesian reasoning will find essential discussion on the validity of Bayesianism and its limits, while philosophers and others interested in pure reasoning will find new ideas on normativity and the logic of belief.Introduction: Bayesianism into the 21st Century -- Bayesianism, Causality and Networks -- Bayesianism and Causality, or, Why I am only a Half-Bayesian -- Causal Inference without Counterfactuals -- Foundations for Bayesian Networks -- Probabilistic Learning Models -- Logic, Mathematics and Bayesianism -- The Logic of Bayesian Probability -- Subjectivism, Objectivism and Objectivity in Bruno de Finetti’s Bayesianism -- Bayesianism in Mathematics -- Common Sense and Stochastic Independence -- Integrating Probabilistic and Logical Reasoning -- Bayesianism and Decision Theory -- Ramsey and the Measurement of Belief -- Bayesianism and Independence -- The Paradox of the Bayesian Experts -- Criticisms of Bayesianism -- Bayesian Learning and Expectations Formation: Anything Goes -- Bayesianism and the Fixity of the Theoretical Framework -- Principles of Inference and their Consequences.Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. The upshot is a plethora of new problems and directions for Bayesians to pursue. The book will be of interest to graduate students or researchers who wish to learn more about Bayesianism than can be provided by introductory textbooks to the subject. Those involved with the applications of Bayesian reasoning will find essential discussion on the validity of Bayesianism and its limits, while philosophers and others interested in pure reasoning will find new ideas on normativity and the logic of belief.Philosophy.Philosophy and science.Artificial intelligence.Probabilities.Statistics.Microeconomics.Philosophy.Philosophy of Science.Artificial Intelligence (incl. Robotics).Probability Theory and Stochastic Processes.Statistics, general.Microeconomics.Springer eBookshttp://dx.doi.org/10.1007/978-94-017-1586-7URN:ISBN:9789401715867
institution COLPOS
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-colpos
tag biblioteca
region America del Norte
libraryname Departamento de documentación y biblioteca de COLPOS
language eng
topic Philosophy.
Philosophy and science.
Artificial intelligence.
Probabilities.
Statistics.
Microeconomics.
Philosophy.
Philosophy of Science.
Artificial Intelligence (incl. Robotics).
Probability Theory and Stochastic Processes.
Statistics, general.
Microeconomics.
Philosophy.
Philosophy and science.
Artificial intelligence.
Probabilities.
Statistics.
Microeconomics.
Philosophy.
Philosophy of Science.
Artificial Intelligence (incl. Robotics).
Probability Theory and Stochastic Processes.
Statistics, general.
Microeconomics.
spellingShingle Philosophy.
Philosophy and science.
Artificial intelligence.
Probabilities.
Statistics.
Microeconomics.
Philosophy.
Philosophy of Science.
Artificial Intelligence (incl. Robotics).
Probability Theory and Stochastic Processes.
Statistics, general.
Microeconomics.
Philosophy.
Philosophy and science.
Artificial intelligence.
Probabilities.
Statistics.
Microeconomics.
Philosophy.
Philosophy of Science.
Artificial Intelligence (incl. Robotics).
Probability Theory and Stochastic Processes.
Statistics, general.
Microeconomics.
Corfield, David. editor.
Williamson, Jon. editor.
SpringerLink (Online service)
Foundations of Bayesianism [electronic resource] /
description Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. The upshot is a plethora of new problems and directions for Bayesians to pursue. The book will be of interest to graduate students or researchers who wish to learn more about Bayesianism than can be provided by introductory textbooks to the subject. Those involved with the applications of Bayesian reasoning will find essential discussion on the validity of Bayesianism and its limits, while philosophers and others interested in pure reasoning will find new ideas on normativity and the logic of belief.
format Texto
topic_facet Philosophy.
Philosophy and science.
Artificial intelligence.
Probabilities.
Statistics.
Microeconomics.
Philosophy.
Philosophy of Science.
Artificial Intelligence (incl. Robotics).
Probability Theory and Stochastic Processes.
Statistics, general.
Microeconomics.
author Corfield, David. editor.
Williamson, Jon. editor.
SpringerLink (Online service)
author_facet Corfield, David. editor.
Williamson, Jon. editor.
SpringerLink (Online service)
author_sort Corfield, David. editor.
title Foundations of Bayesianism [electronic resource] /
title_short Foundations of Bayesianism [electronic resource] /
title_full Foundations of Bayesianism [electronic resource] /
title_fullStr Foundations of Bayesianism [electronic resource] /
title_full_unstemmed Foundations of Bayesianism [electronic resource] /
title_sort foundations of bayesianism [electronic resource] /
publisher Dordrecht : Springer Netherlands : Imprint: Springer,
publishDate 2001
url http://dx.doi.org/10.1007/978-94-017-1586-7
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