271 citations · 327 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
As the operations of autonomous systems generally affect simultaneously several users, it is crucial that their designs account for fairness considerations. In contrast to standard…
Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation
Yijiong Lin, Jiancong Huang, Matthieu Zimmer +2
Deep reinforcement learning (DRL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. We…
Qualitative Decision Making Under Possibilistic Uncertainty: Toward more discriminating criteria
Paul Weng
The aim of this paper is to propose a generalization of previous approaches in qualitative decision making. Our work is based on the binary possibilistic utility (PU), which is a p…
Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility
Paul Weng
Expected Utility: Algebraic Expected Utility In this paper, we provide two axiomatizations of algebraic expected utility, which is a particular generalized expected utility, in a v…