Updating ambiguous beliefs

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The full paper details and pdf (also available here) This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), under Contract [2017-16122000003]. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion.Citation of such a paper should account for its provisional character. Ignorance is precious, for once lost it can never be regained.

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First of all the normative answer to Question 1 – based on simple Bayesian reasoning – is 20% for North Bayesland and 80% for South Bayesland.

Based on the notion of , this paper provides a unified approach for distinguishing capacity updating rules (the Dempster–Shafer updating rule, naive Bayes’ updating rule, and Fagin–Halpern updating rule) according to the degree of dynamic consistency.

We acknowledge an anonymous reviewer and the co-editor, Mark Machina, whose comments improve this paper substantially.

You observe another detonation on the border between the two countries but cannot determine the source.

Based only on the provided information: The general form of this problem is ubiquitous in many areas of life. Our paper “Updating Prior Beliefs Based on Ambiguous Evidence”, which was accepted at the prestigious 40th Annual Meeting of the Cognitive Science Society (Cog Sci 2018) in Madison, Wisconsin, addresses this problem.

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