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Michael Rescorla - One of the best experts on this subject based on the ideXlab platform.
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An Improved Dutch Book Theorem for Conditionalization
Erkenntnis, 2020Co-Authors: Michael RescorlaAbstract:Lewis proved a Dutch book theorem for Conditionalization. The theorem shows that an agent who follows any credal update rule other than Conditionalization is vulnerable to bets that inflict a sure loss. Lewis’s theorem is tailored to factive formulations of Conditionalization, i.e. formulations on which the conditioning proposition is true. Yet many scientific and philosophical applications of Bayesian decision theory require a non - factive formulation, i.e. a formulation on which the conditioning proposition may be false. I prove a Dutch book theorem tailored to non-factive Conditionalization. I also discuss the theorem’s significance.
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On the proper formulation of Conditionalization
Synthese, 2019Co-Authors: Michael RescorlaAbstract:Conditionalization is a norm that governs the rational reallocation of credence. I distinguish between factive and non-factive formulations of Conditionalization. Factive formulations assume that the conditioning proposition is true. Non-factive formulations allow that the conditioning proposition may be false. I argue that non-factive formulations provide a better foundation for philosophical and scientific applications of Bayesian decision theory. I furthermore argue that previous formulations of Conditionalization, factive and non-factive alike, have almost universally ignored, downplayed, or mishandled a crucial causal aspect of Conditionalization. To formulate Conditionalization adequately, one must explicitly address the causal structure of the transition from old credences to new credences. I offer a formulation of Conditionalization that takes these considerations into account, and I compare my preferred formulation with some prominent formulations found in the literature.
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a dutch book theorem and converse dutch book theorem for kolmogorov Conditionalization
Review of Symbolic Logic, 2018Co-Authors: Michael RescorlaAbstract:This paper discusses how to update one’s credences based on evidence that has initial probability 0. I advance a diachronic norm, Kolmogorov Conditionalization, that governs credal reallocation in many such learning scenarios. The norm is based upon Kolmogorov’s theory of conditional probability. I prove a Dutch book theorem and converse Dutch book theorem for Kolmogorov Conditionalization. The two theorems establish Kolmogorov Conditionalization as the unique credal reallocation rule that avoids a sure loss in the relevant learning scenarios.
Marc Lange - One of the best experts on this subject based on the ideXlab platform.
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calibration and the epistemological role of bayesian Conditionalization
The Journal of Philosophy, 1999Co-Authors: Marc LangeAbstract:Evaluation de la pertinence de la conditionnalisation bayesienne (BC) dans le domaine de la theorie de la confirmation en science. Mesurant le role epistemologique de (BC) au regard de la valeur et de la decouverte d'une nouvelle evidence, d'une part, et distinguant l'approche diachronique et le moment particulier de l'opinion, d'autre part, l'A. defend la permissibilite rationnelle d'une mise a jour pour violer (BC) et utilise la notion de calibrage afin de montrer en quel sens un argument justificatif ne peut violer (BC)
Allan Franklin - One of the best experts on this subject based on the ideXlab platform.
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bayesian Conditionalization and probability kinematics
The British Journal for the Philosophy of Science, 1994Co-Authors: Colin Howson, Allan FranklinAbstract:L'A. confronte le principe de conditionnalisation de Bayes, tel qu'il fonde la theorie personnaliste des probabilites personnelles, a la theorie cinematique de probabilite inauguree par R. C. Jeffrey, et fondee sur un autre principe de conditionnalisation dont la validite, comme celle du principe de Bayes, est garantie par l'argument du livre hollandais, et echappe a la menace de l'instabilite de l'evidence
Dmitri J Gallow - One of the best experts on this subject based on the ideXlab platform.
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how to learn from theory dependent evidence or commutativity and holism a solution for conditionalizers
The British Journal for the Philosophy of Science, 2014Co-Authors: Dmitri J GallowAbstract:Weisberg (2009) provides an argument that neither Conditionalization nor Jeffrey Conditionalization is capable of accommodating the holist’s claim that beliefs acquired directly from experience can suffer undercutting defeat. I diagnose this failure as stemming from the fact that neither Conditionalization nor Jeffrey Conditionalization give any advice about how to rationally respond to theorydependent evidence, and I propose a novel updating procedure which does tell us how to respond to evidence like this. is holistic updating rule yields Conditionalization as a special case in which our evidence is entirely theory-independent.
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how to learn from theory dependent evidence or commutativity and holism a solution for conditionalizers
The British Journal for the Philosophy of Science, 2014Co-Authors: Dmitri J GallowAbstract:AbstractWeisberg ([2009]) provides an argument that neither Conditionalization nor Jeffrey Conditionalization is capable of accommodating the holist’s claim that beliefs acquired directly from expe...
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an inaccuracy minimization argument for holistic Conditionalization
2014Co-Authors: Dmitri J GallowAbstract:It is shown that the update rule defended in Gallow (2014), holistic Conditionalization, follows from a natural strategy for minimizing the expected inaccuracy of your posterior credences when you acquire theory-dependent evidence.
Darren Bradley - One of the best experts on this subject based on the ideXlab platform.
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Conditionalization and Belief De Se
2016Co-Authors: Darren BradleyAbstract:Colin Howson (1995) offers a counter-example to the rule of Conditionalization. I will argue that the counter-example doesn’t hit its target. The problem is that Howson mis-describes the total evidence the agent has. In particular, Howson overlooks how the restriction that the agent learn ‘E and nothing else ’ interacts with the de se evidence ‘I have learnt E’.dltc_1188 247..250 Conditionalization Bayesian confirmation theory says that agents should update by Conditionalization when a new piece of evidence is learnt: Conditionalization Suppose an agent has prior probabilities P(Hi) at t0. If the agent learns some particular proposition, E, and nothing else between t0 and t1, then her t1 probabilities should be P(Hi|E), where P(E)> 0. Note the restriction that the agent learns ‘E and nothing else’. It might seem hard to ever satisfy this requirement, for whenever E is learnt, the agent is also in a position to learn ‘I learn E’.1 Nevertheless, ‘E ’ and ‘I learn E ’ are distinct propo-sitions, and Conditionalization only applies when E expresses the total evidence the agent has learnt. I will argue that a purported counter-example to condition-alization, due to Colin Howson, overlooks this point. Howson’s argument I will quote Howson’s argument in full. He claims that you can be consistent even if you now know what P2(A) will be in the event of E’s being true, and know that it differs from P1(A|E), as the following example, due to Richard Thomason shows. A husband announces ‘if my wife is unfaithful, I shall never know’; – the wife being known to be an expert in deception. The corresponding conditional probability he ascribes to his not knowing that his wife is unfaithful [A], given his wife’s infidelity [E], is presumably 1 or near 1. Yet learning that his wife was unfaithful he coul
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self location is no problem for Conditionalization
Synthese, 2011Co-Authors: Darren BradleyAbstract:How do temporal and eternal beliefs interact? I argue that acquiring a tem- poral belief should have no effect on eternal beliefs for an important range of cases. Thus, I oppose the popular view that new norms of belief change must be introduced for cases where the only change is the passing of time. I defend this position from the purported counter-examples of the Prisoner and Sleeping Beauty. I distinguish two importantly different ways in which temporal beliefs can be acquired and draw some general conclusions about their impact on eternal beliefs.
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Conditionalization and belief de se
Dialectica, 2010Co-Authors: Darren BradleyAbstract:Colin Howson (1995) offers a counter-example to the rule of Conditionalization. I will argue that the counter-example doesn't hit its target. The problem is that Howson mis-describes the total evidence the agent has. In particular, Howson overlooks how the restriction that the agent learn ‘E and nothing else’ interacts with the de se evidence ‘I have learnt E’.