We present an interface for eliciting sets of acceptable gambles on a three-outcome possibility space, discuss an experiment conducted for testing this interface, and present the results of this experiment. Sets of acceptable gambles form a representation for imprecise probabilities that is close to human behavior and eliciting them directly may improve the quality of the resulting uncertainty model. The experiment consisted of a betting competition for the 2014 FIFA World Cup: For each match bets were assigned based on the sets of acceptable gambles elicited from the participants. A new algorithm was designed for generating fair bets for assignment. Participant feedback indicated that improving the usability and transparency of the interface would ease the elicitation procedure. The experiment’s results underlined that imprecision is an essential aspect of real-life uncertainty modeling.

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International Symposium on Imprecise Probability: Theories and Applications
Machine Learning

Quaeghebeur, E., Wesseling, C., Beauxis-Aussalet, E., Piovesan, T., & Sterkenburg, T. (2017). The CWI World Cup competition: Eliciting sets of acceptable gambles. In Proceedings of Machine Learning Research (pp. 277–288).