Results 1  10
of
113
Bayesian Decision Theory and Psychophysics
 In Perception as Bayesian Inference
, 1994
"... We argue that Bayesian decision theory provides a good theoretical framework for visual perception. Such a theory involves a likelihood function specifying how the scene generates the image(s), a prior assumption about the scene, and a decision rule to determine the scene interpretation. This is ill ..."
Abstract

Cited by 41 (2 self)
 Add to MetaCart
We argue that Bayesian decision theory provides a good theoretical framework for visual perception. Such a theory involves a likelihood function specifying how the scene generates the image(s), a prior assumption about the scene, and a decision rule to determine the scene interpretation. This is illustrated by describing Bayesian theories for individual visual cues and showing that perceptual biases found in psychophysical experiments can be interpreted as biases towards prior assumptions made by the visual system. We then describe the implications of this framework for the integration of different cues. We argue that the dependence of cues on prior assumptions means that care must be taken to model these dependencies during integration. This suggests that a number of proposed schemes for cue integration, which only allow weak interaction between cues, are not adequate and instead stronger coupling is often required. These theories require the choice of decision rules and we argue that...
On the Reality of the Conjunction Fallacy
, 2001
"... Attributing higher "probability" to a sentence of form pandq compared to p is a reasoning fallacy only if (a) the word "probability" carries its modern, technical meaning, and (b) the sentence p is interpreted as a conjunct of the conjunction pandq. Legitimate doubts arise ab ..."
Abstract

Cited by 24 (3 self)
 Add to MetaCart
Attributing higher "probability" to a sentence of form pandq compared to p is a reasoning fallacy only if (a) the word "probability" carries its modern, technical meaning, and (b) the sentence p is interpreted as a conjunct of the conjunction pandq. Legitimate doubts arise about both conditions in classic demonstrations of the conjunction fallacy. We use betting paradigms to reduce these sources of ambiguity about conjunctive reasoning. Reality of the conjunction fallacy 1 Introduction The conjunction fallacy Here is the famous Linda story, to be labeled E (for "evidence") in what follows. (E) Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations. The task is to rank various statements "by their probability," including these two. (B) Linda is a bank teller. (B # F ) Linda is a bank teller and is activ...
Optimal data selection in the reduced array selection task (RAST
 Journal of Experimental Psychology: Learning, Memory & Cognition
, 1997
"... The predictions of M. Oaksford and N. Chater's (1994) optimal data selection (ODS) model for the reduced array selection task (RAST) were tested in 4 experiments. Participants tested a hypothesis, ifp then q, by selecting cards showing q or not q instances. In Experiment 1, where selections wer ..."
Abstract

Cited by 23 (6 self)
 Add to MetaCart
(Show Context)
The predictions of M. Oaksford and N. Chater's (1994) optimal data selection (ODS) model for the reduced array selection task (RAST) were tested in 4 experiments. Participants tested a hypothesis, ifp then q, by selecting cards showing q or not q instances. In Experiment 1, where selections were made from different sized stacks of q and not q cards, as P(q) increased, not q card selections rose, and q card selections fell, as predicted. Experiment 2 controlled for the possibility that stack height influenced responses; these results were also consistent with ODS. Experiment 3, which controlled further for this possibility, replicated Experiment 1. Experiment 4 addressed a final issue concerning the medium P(q) condition by concentrating on initial card selections; the results were again consistent with ODS. Although generally consistent with the ODS model, these experiments also suggest some interesting revisions. The psychology of reasoning appears to show that on some tasks people do not reason according to the rules of logic (e.g., Evans, 1982, 1989; JohnsonLaird & Byrne, 1991; Wason & JohnsonLaird, 1972). Some authors have therefore concluded that humans may be irrational (Stich,
Belief revision in probability theory
 InProceedings of the Ninth Conference on Uncertainty in Arti cial Intelligence
, 1993
"... In a probabilitybased reasoning system, Bayes’ theorem and its variations are often used to revise the system’s beliefs. However, if the explicit conditions and the implicit conditions of probability assignments are properly distinguished,it follows that Bayes ’ theorem is not a generally applicabl ..."
Abstract

Cited by 21 (17 self)
 Add to MetaCart
(Show Context)
In a probabilitybased reasoning system, Bayes’ theorem and its variations are often used to revise the system’s beliefs. However, if the explicit conditions and the implicit conditions of probability assignments are properly distinguished,it follows that Bayes ’ theorem is not a generally applicable revision rule. Upon properly distinguishing belief revision from belief updating, we see that Jeffrey’s rule and its variations are not revision rules, either. Without these distinctions, the limitation of the Bayesian approach is often ignored or underestimated. Revision, in its general form, cannot be done in the Bayesian approach, because a probability distribution function alone does not contain the information needed by the operation. 1
Inferring Conservation Laws in Particle Physics: A Case Study
 in the Problem of Induction”, The British Journal for the Philosophy of Science, Forthcoming
, 2001
"... This paper develops a meansends analysis of an inductive problem that arises in particle physics: how to infer from observed reactions conservation principles that govern all reactions among elementary particles. I show that there is a reliable inference procedure that is guaranteed to arrive at an ..."
Abstract

Cited by 16 (3 self)
 Add to MetaCart
This paper develops a meansends analysis of an inductive problem that arises in particle physics: how to infer from observed reactions conservation principles that govern all reactions among elementary particles. I show that there is a reliable inference procedure that is guaranteed to arrive at an empirically adequate set of conservation principles as more and more evidence is obtained. An interesting feature of reliable procedures for finding conservation principles is that in certain precisely defined circumstances they must introduce hidden particles. Among the reliable inductive methods there is a unique procedure that minimizes convergence time as well as the number of times that the method revises its conservation principles. Thus the aims of reliable, fast and steady convergence to an empirically adequate theory single out a unique optimal inference for a given set of observed reactions–including prescriptions for when exactly to introduce hidden particles.
Interpreting Causality
 in the Health Sciences,‖ International Studies in the Philosophy of Science
, 2007
"... Perhaps the key philosophical questions concerning causality are the following: • what are causal relationships? • how can one discover causal relationships? ..."
Abstract

Cited by 13 (5 self)
 Add to MetaCart
Perhaps the key philosophical questions concerning causality are the following: • what are causal relationships? • how can one discover causal relationships?
The Logic of Reliable and Efficient Inquiry
 Journal of Philosophical Logic
, 2001
"... This paper pursues a thoroughgoing instrumentalist, or meansends, approach to the theory of inductive inference. I consider three epistemic aims: convergence to a correct theory, fast convergence to a correct theory and steady con vergence to a correct theory (avoiding retractions). For each of ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
This paper pursues a thoroughgoing instrumentalist, or meansends, approach to the theory of inductive inference. I consider three epistemic aims: convergence to a correct theory, fast convergence to a correct theory and steady con vergence to a correct theory (avoiding retractions). For each of these, two questions arise: (1) What is the structure of inductive problems in which these aims are feasible ? (2) When feasible, what are the inference methods that attain them? Formal learning theory provides the tools for a complete set of answers to these questions.
Objective Bayesianism, Bayesian Conditionalisation
, 2008
"... Objective Bayesianism has been criticised on the grounds that objective Bayesian updating, which on a finite outcome space appeals to the maximum entropy principle, differs from Bayesian conditionalisation. The main task of this paper is to show that this objection backfires: the difference between ..."
Abstract

Cited by 11 (7 self)
 Add to MetaCart
(Show Context)
Objective Bayesianism has been criticised on the grounds that objective Bayesian updating, which on a finite outcome space appeals to the maximum entropy principle, differs from Bayesian conditionalisation. The main task of this paper is to show that this objection backfires: the difference between the two forms of updating reflects negatively on Bayesian conditionalisation rather than on objective Bayesian updating. The paper also reviews some existing criticisms and justifications of conditionalisation, arguing in particular that the diachronic Dutch book justification fails because diachronic Dutch book arguments are subject to a reductio: in certain circumstances one can Dutch book an agent however she changes her degrees of belief. One may also criticise objective Bayesianism on the grounds that its norms are not compulsory but voluntary, the result of a stance. It is argued that this second objection also misses the mark, since objective
How convinced should we be by negative evidence
 Proceedings of the Annual Conference of the Cognitive Science Society
, 2005
"... Since John Locke, the socalled argument from ignorance has been considered to be a fallacy, and is widely represented in informal logic textbooks as an example of incorrect reasoning. This might seem surprising to researchers in many scientific disciplines who routinely draw inferences from negativ ..."
Abstract

Cited by 9 (5 self)
 Add to MetaCart
(Show Context)
Since John Locke, the socalled argument from ignorance has been considered to be a fallacy, and is widely represented in informal logic textbooks as an example of incorrect reasoning. This might seem surprising to researchers in many scientific disciplines who routinely draw inferences from negative evidence. Oaksford and Hahn (2004) argued that this discrepancy can be explained within a Bayesian framework. We present here experimental evidence for this view.
Inductive influence
 British Journal for the Philosophy of Science
"... Objective Bayesianism has been criticised for not allowing learning from experience: it is claimed that an agent must give degree of belief 1 to the next raven being black, however many other black ravens have 2 been observed. I argue that this objection can be overcome by appealing to objective Bay ..."
Abstract

Cited by 9 (7 self)
 Add to MetaCart
Objective Bayesianism has been criticised for not allowing learning from experience: it is claimed that an agent must give degree of belief 1 to the next raven being black, however many other black ravens have 2 been observed. I argue that this objection can be overcome by appealing to objective Bayesian nets, a formalism for representing objective Bayesian degrees of belief. Under this account, previous observations exert an inductive influence on the next observation. I show how this approach can be used to capture the JohnsonCarnap continuum of inductive methods, as well as the NixParis continuum, and show how inductive influence can