Sequential Decision Making with Rank Dependent Utility: a Minimax Regret Approach

Gildas Jeantet 1 Patrice Perny 1 Olivier Spanjaard 1
1 DECISION
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : This paper is devoted to sequential decision making with Rank Dependent expected Utility (RDU). This decision criterion generalizes Expected Utility and enables to model a wider range of observed (rational) behaviors. In such a sequential decision setting, two conflicting objectives can be identified in the assessment of a strategy: maximizing the performance viewed from the initial state (optimality), and minimizing the incentive to deviate during implementation (deviation-proofness). In this paper, we propose a minimax regret approach taking these two aspects into account, and we provide a search procedure to determine an optimal strategy for this model. Numerical results are presented to show the interest of the proposed approach in terms of optimality, deviation-proofness and computability.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [11 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01273054
Contributor : Lip6 Publications <>
Submitted on : Thursday, July 13, 2017 - 5:19:52 PM
Last modification on : Thursday, March 21, 2019 - 1:21:21 PM
Document(s) archivé(s) le : Wednesday, January 24, 2018 - 5:08:47 PM

File

gjpposaaai12.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01273054, version 1

Citation

Gildas Jeantet, Patrice Perny, Olivier Spanjaard. Sequential Decision Making with Rank Dependent Utility: a Minimax Regret Approach. 26th AAAI Conference on Artificial Intelligence, Jul 2012, Toronto, Canada. pp.1931-1937. ⟨hal-01273054⟩

Share

Metrics

Record views

143

Files downloads

77