A New Garber-Style Solution to the Problem of Old Evidence

2015 ◽  
Vol 82 (4) ◽  
pp. 712-717 ◽  
Author(s):  
Stephan Hartmann ◽  
Branden Fitelson
Keyword(s):  
Old Evidence ◽  
Problem Of Old Evidence

Subjectivism

2017 ◽  
Author(s):  
Lyle Zynda
Keyword(s):  
Decision Theory ◽  
Subjective Probability ◽  
Dutch Book ◽  
Scientific Theories ◽  
Confirmation Theory ◽  
Representation Theorems ◽  
Preference Theory ◽  
Betting Behavior ◽  
Old Evidence ◽  
Problem Of Old Evidence

This essay discusses subjective probability—its foundations, justification, and relation to other subjects, such as decision theory and confirmation theory. Various forms of subjectivism (the belief in subjective probability) are described, and distinguished from non-subjectivist approaches. Two broad approaches to justifying the laws of probability on subjectivist grounds are then discussed: (a) pragmatic approaches, based on betting behavior, with associated Dutch book arguments, or (more broadly) pragmatic approaches based on decision and preference theory, with its representation theorems; and (b) non-pragmatic (epistemic) approaches, with arguments based on calibration and gradational accuracy. These various arguments are assessed, and their scope and limitations spelled out in detail. Finally, the relation of subjective probability to the confirmation of scientific theories is discussed, focusing on the problem of old evidence, and its various proposed solutions.

scholarly journals A Novel Solution to the Problem of Old Evidence

2015 ◽  
Vol 82 (3) ◽  
pp. 383-401 ◽  
Author(s):  
Jan Sprenger
Keyword(s):  
Old Evidence ◽  
Problem Of Old Evidence

The Problem of Old Evidence

2019 ◽  
pp. 131-154
Author(s):  
Jan Sprenger ◽  
Stephan Hartmann
Keyword(s):  
Bayesian Models ◽  
Scientific Theories ◽  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Bayesian Confirmation ◽  
New Information ◽  
Novel Theory ◽  
Old Evidence ◽  
Problem Of Old Evidence

In science, phenomena are often unexplained by the available scientific theories. At some point, it may be discovered that a novel theory accounts for this phenomenon—and this seems to confirm the theory because a persistent anomaly is resolved. However, Bayesian confirmation theory—primarily a theory for updating beliefs in the light of learning new information—struggles to describe confirmation by such cases of “old evidence”. We discuss the two main varieties of the Problem of Old Evidence (POE)—the static and the dynamic POE—, criticize existing solutions and develop two novel Bayesian models. They show how the discovery of explanatory and deductive relationships, or the absence of alternative explanations for the phenomenon in question, can confirm a theory. Finally, we assess the overall prospects of Bayesian Confirmation Theory in the light of the POE.

scholarly journals Fragmentation and Old Evidence

Episteme ◽  
2021 ◽  
pp. 1-26
Author(s):  
Will Fleisher
Keyword(s):  
Inductive Reasoning ◽  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Bayesian Confirmation ◽  
Scientific Inference ◽  
Formal Framework ◽  
Old Evidence ◽  
Problem Of Old Evidence ◽  
Doxastic States

Abstract Bayesian confirmation theory is our best formal framework for describing inductive reasoning. The problem of old evidence is a particularly difficult one for confirmation theory, because it suggests that this framework fails to account for central and important cases of inductive reasoning and scientific inference. I show that we can appeal to the fragmentation of doxastic states to solve this problem for confirmation theory. This fragmentation solution is independently well-motivated because of the success of fragmentation in solving other problems. I also argue that the fragmentation solution is preferable to other solutions to the problem of old evidence. These other solutions are already committed to something like fragmentation, but suffer from difficulties due to their additional commitments. If these arguments are successful, Bayesian confirmation theory is saved from the problem of old evidence, and the argument for fragmentation is bolstered by its ability to solve yet another problem.

scholarly journals Ambiguity aversion, modern Bayesianism and small worlds

2021 ◽  
Vol 1 ◽  
pp. 13
Author(s):  
Nikitas Pittis ◽  
Phoebe Koundouri ◽  
Panagiotis Samartzis ◽  
Nikolaos Englezos ◽  
Andreas Papandreou
Keyword(s):  
Cognitive Dissonance ◽  
Ambiguity Aversion ◽  
Small World ◽  
Central Question ◽  
Small Worlds ◽  
Psychological Detachment ◽  
Probabilistic Beliefs ◽  
Objective Chance ◽  
Old Evidence ◽  
Problem Of Old Evidence

The central question of this paper is whether a rational agent under uncertainty can exhibit ambiguity aversion (AA). The answer to this question depends on the way the agent forms her probabilistic beliefs: classical Bayesianism (CB) vs modern Bayesianism (MB). We revisit Schmeidler's coin-based example and show that a rational MB agent operating in the context of a "small world", cannot exhibit AA. Hence we argue that the motivation of AA based on Schmeidler's coin-based and Ellsberg's classic urn-based examples, is poor, since they correspond to cases of "small worlds". We also argue that MB, not only avoids AA, but also proves to be normatively superior to CB because an MB agent (i) avoids logical inconsistencies akin to the relation between her subjective probability and objective chance, (ii) resolves the problem of "old evidence" and (iii) allows psychological detachment from actual evidence, hence avoiding the problem of "cognitive dissonance". As far as AA is concerned, we claim that it may be thought of as a (potential) property of large worlds, because in such worlds MB is likely to be infeasible.

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