Switch to: Citations

Add references

You must login to add references.
  1. Updating beliefs in light of uncertain evidence: Descriptive assessment of Jeffrey's rule.Daniel Osherson & Jiaying Zhao - 2010 - Thinking and Reasoning 16 (4):288-307.
    Jeffrey (1983) proposed a generalization of conditioning as a means of updating probability distributions when new evidence drives no event to certainty. His rule requires the stability of certain conditional probabilities through time. We tested this assumption (“invariance”) from the psychological point of view. In Experiment 1 participants offered probability estimates for events in Jeffrey’s candlelight example. Two further scenarios were investigated in Experiment 2, one in which invariance seems justified, the other in which it does not. Results were in (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   16 citations  
  • Support theory: A nonextensional representation of subjective probability.Amos Tversky & Derek J. Koehler - 1994 - Psychological Review 101 (4):547-567.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   94 citations  
  • The transferable belief model.Philippe Smets & Robert Kennes - 1994 - Artificial Intelligence 66 (2):191-234.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   30 citations  
  • Languages and Designs for Probability Judgment.Glenn Shafer & Amos Tversky - 1985 - Cognitive Science 9 (3):309-339.
    Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.
    No categories
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   19 citations  
  • Uncertain premises and Jeffrey's rule.David E. Over & Constantinos Hadjichristidis - 2009 - Behavioral and Brain Sciences 32 (1):97-98.
    Oaksford & Chater (O&C) begin in the halfway Bayesian house of assuming that minor premises in conditional inferences are certain. We demonstrate that this assumption is a serious limitation. They additionally suggest that appealing to Jeffrey's rule could make their approach more general. We present evidence that this rule is not limited enough to account for actual probability judgements.
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   7 citations  
  • Reasoning with uncertain categories.Gregory L. Murphy, Stephanie Y. Chen & Brian H. Ross - 2012 - Thinking and Reasoning 18 (1):81 - 117.
    Five experiments investigated how people use categories to make inductions about objects whose categorisation is uncertain. Normatively, they should consider all the categories the object might be in and use a weighted combination of information from all the categories: bet-hedging. The experiments presented people with simple, artificial categories and asked them to make an induction about a new object that was most likely in one category but possibly in another. The results showed that the majority of people focused on the (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   6 citations  
  • Probabilities of conditionals and conditional probabilities II.David Lewis - 1986 - Philosophical Review 95 (4):581-589.
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   78 citations  
  • The influence of hierarchy on probability judgment.David A. Lagnado & David R. Shanks - 2003 - Cognition 89 (2):157-178.
    Consider the task of predicting which soccer team will win the next World Cup. The bookmakers may judge Brazil to be the team most likely to win, but also judge it most likely that a European rather than a Latin American team will win. This is an example of a non-aligned hierarchy structure: the most probable event at the subordinate level (Brazil wins) appears to be inconsistent with the most probable event at the superordinate level (a European team wins). In (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  • Updating: A psychologically basic situation of probability revision.Jean Baratgin & Guy Politzer - 2010 - Thinking and Reasoning 16 (4):253-287.
    The Bayesian model has been used in psychology as the standard reference for the study of probability revision. In the first part of this paper we show that this traditional choice restricts the scope of the experimental investigation of revision to a stable universe. This is the case of a situation that, technically, is known as focusing. We argue that it is essential for a better understanding of human probability revision to consider another situation called updating (Katsuno & Mendelzon, 1992), (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   26 citations