Results 1  10
of
101
On the relative independence of thinking biases and cognitive ability.
 Journal of Personality and Social Psychology,
, 2008
"... ..."
Studies in Bayesian Confirmation Theory
, 2001
"... According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are ..."
Abstract

Cited by 33 (8 self)
 Add to MetaCart
According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are correlated under Pr. Surprisingly, this leads to a plethora of nonequivalent quantitative measures of the degree to which E confirms H (under Pr). In fact, many nonequivalent Bayesian measures of the degree to which E confirms (or supports) H have been proposed and defended in the literature on inductive logic. I provide a thorough historical survey of the various proposals, and a detailed discussion of the philosophical ramifications of the differences between them. I argue that the set of candidate
How to Make Sense of the Common Prior Assumption under Incomplete Information
 International Journal of Game Theory
, 1996
"... The Common Prior Assumption (CPA) is central to the economics of information and the foundations of game theory. Recent contributions (Dekel and Gul, 1997, Gul, 1996, Lipman, 1995) have questioned its meaningfulness in situations of incomplete information where there is no ex ante stage and the prim ..."
Abstract

Cited by 32 (8 self)
 Add to MetaCart
The Common Prior Assumption (CPA) is central to the economics of information and the foundations of game theory. Recent contributions (Dekel and Gul, 1997, Gul, 1996, Lipman, 1995) have questioned its meaningfulness in situations of incomplete information where there is no ex ante stage and the primitives of the model are the individuals ’ belief hierarchies. We address this conceptual issue by providing characterizations of two local versions of the CPA which are in terms of the primitives and, therefore, do not involve a counterfactual and problematic ex ante stage. The characterizations involve three notions: Comprehensive Agreement, no error of beliefs and common belief in no error. Comprehensive Agreement is defined as the absence of “agreement to disagree ” about any aspect of beliefs; it is a generalization of Aumann’s (1976) notion of agreement. The entire analysis is carried out locally, that is, with reference to the “true state ” (which represents the actual profile of belief hierarchies) and does not rely on the Truth Axiom for individual beliefs. The results are also applied to the problem of generalizing the notion of Bayesian updating to singleperson, intertemporal situations without perfect recall and without given information partitions. We are grateful to Bart Lipman and two referees for helpful and constructive comments. Seminar participants at Harvard, Penn, Princeton, USC and Yale provided useful comments. We also greatly benefited from discussions with participants at the SITE Workshop on the Epistemic Foundations of Game Theory (Stanford), in particular Steve Morris.
Probabilistic networks and explanatory coherence
 Cognitive Science Quarterly
, 2000
"... Causal reasoning can be understood qualitatively in terms of explanatory coherence or quantitatively in terms of probability theory. Comparison of these approaches can be done by looking at computational models, using my explanatory coherence networks and Pearl’s probabilistic ones. The explanatory ..."
Abstract

Cited by 24 (0 self)
 Add to MetaCart
(Show Context)
Causal reasoning can be understood qualitatively in terms of explanatory coherence or quantitatively in terms of probability theory. Comparison of these approaches can be done by looking at computational models, using my explanatory coherence networks and Pearl’s probabilistic ones. The explanatory coherence program ECHO can be given a probabilistic interpretation, but there are many conceptual and computational problems that make it difficult to replace coherence networks by probabilistic ones. On the other hand, ECHO provides a psychologically plausible and computationally efficient model of some kinds of probabilistic causal reasoning. Hence coherence theory need not give way to probability theory as the basis for epistemology and decision making.
Justifying Conditionalization: Conditionalization Maximizes Expected Epistemic Utility
 MIND
, 2006
"... According to Bayesian epistemology, the epistemically rational agent updates her beliefs by conditionalization: that is, her posterior subjective probability after taking account of evidence X, p new, is to be set equal to her prior conditional probability p old($X). Bayesians can be challenged to ..."
Abstract

Cited by 24 (3 self)
 Add to MetaCart
(Show Context)
According to Bayesian epistemology, the epistemically rational agent updates her beliefs by conditionalization: that is, her posterior subjective probability after taking account of evidence X, p new, is to be set equal to her prior conditional probability p old($X). Bayesians can be challenged to provide a justification for their claim that conditionalization is recommended by rationality—whence the normative force of the injunction to conditionalize? There are several existing justifications for conditionalization, but none directly addresses the idea that conditionalization will be epistemically rational if and only if it can reasonably be expected to lead to epistemically good outcomes. We apply the approach of cognitive decision theory to provide a justification for conditionalization using precisely that idea. We assign epistemic utility functions to epistemically rational agents; an agent’s epistemic utility is to depend both upon the actual state of the world and on the agent’s credence distribution over possible states. We prove that, under independently motivated conditions, conditionalization is the unique updating rule that maximizes expected epistemic utility.
A Mistake in Dynamic Coherence Arguments
 Philosophy of Science 60
, 1993
"... you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact inform ..."
Abstract

Cited by 12 (0 self)
 Add to MetaCart
you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at.
RESURRECTING LOGICAL PROBABILITY
 ERKENNTNIS
, 2001
"... The logical interpretation of probability, or “objective Bayesianism” – the theory that (some) probabilities are strictly logical degrees of partial implication – is defended. The main argument against it is that it requires the assignment of prior probabilities, and that any attempt to determine t ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
The logical interpretation of probability, or “objective Bayesianism” – the theory that (some) probabilities are strictly logical degrees of partial implication – is defended. The main argument against it is that it requires the assignment of prior probabilities, and that any attempt to determine them by symmetry via a “principle of insufficient reason” inevitably leads to paradox. Three replies are advanced: that priors are imprecise or of little weight, so that disagreement about them does not matter, within limits; that it is possible to distinguish reasonable from unreasonable priors on logical grounds; and that in real cases disagreement about priors can usually be explained by differences in the background information. It is argued also that proponents of alternative conceptions of probability, such as frequentists, Bayesians and Popperians, are unable to avoid committing themselves to the basic principles of logical probability.
A simple modal logic for belief revision
 and Knowledge, Rationality and Action
, 2005
"... We propose a modal logic based on three operators, representing intial beliefs, information and revised beliefs. Three simple axioms are used to provide a sound and complete axiomatization of the qualitative part of Bayes ’ rule. Some theorems of this logic are derived concerning the interaction bet ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
(Show Context)
We propose a modal logic based on three operators, representing intial beliefs, information and revised beliefs. Three simple axioms are used to provide a sound and complete axiomatization of the qualitative part of Bayes ’ rule. Some theorems of this logic are derived concerning the interaction between current beliefs and future beliefs. Information flows and iterated revision are also discussed. 1
Epistemic value theory and information ethics
 Minds and Machines
, 2004
"... Abstract. Three of the major issues in information ethics — intellectual property, speech regulation, and privacy — concern the morality of restricting people’s access to certain information. Consequently, policies in these areas have a significant impact on the amount and types of knowledge that pe ..."
Abstract

Cited by 6 (3 self)
 Add to MetaCart
Abstract. Three of the major issues in information ethics — intellectual property, speech regulation, and privacy — concern the morality of restricting people’s access to certain information. Consequently, policies in these areas have a significant impact on the amount and types of knowledge that people acquire. As a result, epistemic considerations are critical to the ethics of information policy decisions (cf. Mill, 1978 [1859]). The fact that information ethics is a part of the philosophy of information highlights this important connection with epistemology. In this paper, I illustrate how a valuetheoretic approach to epistemology can help to clarify these major issues in information ethics. However, I also identify several open questions about epistemic values that need to be answered before we will be able to evaluate the epistemic consequences of many information policies.
HARD PROBLEMS IN THE PHILOSOPHY OF SCIENCE: IDEALIZATION AND COMMENSURABILITY
, 2000
"... In the 1960s, Kuhn maintained that there is no standard higher of rationality than the assent of the relevant community. Realists have seek to evaluate the rationality of science relative to a highest standard possible—namely the truth, or approximate truth, of our best theories. Given that the rea ..."
Abstract

Cited by 5 (1 self)
 Add to MetaCart
In the 1960s, Kuhn maintained that there is no standard higher of rationality than the assent of the relevant community. Realists have seek to evaluate the rationality of science relative to a highest standard possible—namely the truth, or approximate truth, of our best theories. Given that the realist view of rationality is controversial, it seems that a more secure reply to Kuhn should be based on a less controversial objective of science—namely, the goal of predictive accuracy. Not only does this yield a more secure reply to Kuhn, but it also provides the foundation on which any realist arguments should be based. In order to make this case, it is necessary to introduce a threeway distinction between theories, models, and predictive hypotheses, and then ask some hard questions about how the methods of science can actually achieve their goals. As one example of the success of such a program, I explain how the truth of models can sometimes lower their predictive accuracy. As a second example, I describe how one can define progress across paradigms in terms of predictive accuracy. These are examples of hard problems in the philosophy of science, which fall outside the scope of social psychology.