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

This paper is devoted to sequential decision making with Rank Dependent expected Utility (RDU). criterion generalizes Expected and enables model a wider range of observed (rational) behaviors. In such setting, two conflicting objectives can be identified in the assessment strategy: maximizing performance viewed from initial state (optimality), minimizing incentive deviate during implementation (deviation-proofness). this paper, we propose minimax regret approach taking these aspects into account, provide search procedure determine an optimal strategy for model. Numerical results are presented show interest proposed terms optimality, deviation-proofness computability.