Risk, ambiguity, and decision
By D. Ellsberg. 2001
166 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/e82bafe312dd30bdc0bb0ddd3859ccf8ddf12c8e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Alessandro Acquisti
- Jens Grossklags
- Robert J. Lempert
- M. Machina
- Marciano M. Siniscalchi
- Lorrie Faith Cranor
- Hans-Theo Normann
- Volker Benndorf
Citations in the corpus
- What Can Behavioral Economics Teach Us about Privacy (2008, background): “Individuals tend to make sometimes paradoxical, surprising, and seemingly contradictory decisions (see, for example, [35] and [36]).”
- A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios (2006, background): “ities; Ellsberg (2001), whose paradox addresses conditions of ambi-”
- What are robust strategies in the face of uncertain climate threshold responses? (2012, background): “…three potentially important problems: (i) EUM poorly describes the actual decision rules people often use under conditions of deep uncertainty (e.g. Ellsberg 1961, 2001), (ii) implementing EUM under conditions of deep uncertainty raises important methodological challenges, for instance how to…”
- Ambiguity and Ambiguity Aversion (2014, background): “79 The first was introduced by Epstein and Schneider (2003) in the context of MEU preferences, and extended to Variational Preferences by Maccheroni, Marinacci and Rustichini (2006b), to Smooth Ambiguity Preferences by Klibanoff, Marinacci and Mukerji (2009), and to Vector Expected Utility preferenc”