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Multi-objective reinforcement learning: an ethical perspective

Timon Deschamps, Rémy Chaput, Laëtitia Matignon
October, 2024 · Workshop paper

Abstract

Reinforcement learning (RL) is becoming more prevalent in practical domains with human implications, raising ethical questions. Specifically, multi-objective RL has been argued to be an ideal framework for modeling real-world problems and developing human-aligned artificial intelligence. However, the ethical dimension remains underexplored in the field and no survey covers this aspect. Hence, we propose a review of multi-objective RL from an ethical perspective, highlighting existing works, gaps in the literature, important considerations, and potential areas for future research.
Type: Workshop paper
Publication: Multi-Objective Decision Making Workshop
Reinforcement learning Multi-objective decision making Machine ethics