Modeling agent's conditional preferences under objective ambiguity in Dempster-Shafer theory
Autor: | Barbara Vantaggi, Davide Petturiti |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Ambiguity
Computer science media_common.quotation_subject Anscombe-Aumann acts Conditional Choquet expected value Belief and plausibility functions Ambiguity Conditional preferences Anscombe-Aumann acts Belief and plausibility functions Conditional Choquet expected value Conditional preferences 02 engineering and technology Theoretical Computer Science Lottery Artificial Intelligence 020204 information systems Dempster–Shafer theory 0202 electrical engineering electronic engineering information engineering Preference (economics) Axiom media_common Applied Mathematics Conditional probability Null (SQL) Cardinal utility 020201 artificial intelligence & image processing Mathematical economics Software |
Popis: | We manage decisions under “objective” ambiguity by considering generalized Anscombe-Aumann acts, mapping states of the world to generalized lotteries on a set of consequences. A generalized lottery is modeled through a belief function on consequences, interpreted as a partially specified randomizing device. Preference relations on these acts are given by a decision maker focusing on different scenarios (conditioning events). We provide a system of axioms which are necessary and sufficient for the representability of these “conditional preferences” through a conditional functional parametrized by a unique full conditional probability P on the algebra of events and a cardinal utility function u on consequences. The model is able to manage also “unexpected” (i.e., “null”) conditioning events and distinguishes between a systematically pessimistic or optimistic behavior, either referring to “objective” belief functions or their dual plausibility functions. Finally, an elicitation procedure is provided, reducing to a Quadratically Constrained Linear Program (QCLP). |
Databáze: | OpenAIRE |
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