PFIA 2024
RJCIA
Multi-objective reinforcement learning, an ethical perspective
Timon Deschamps, Rémy Chaput, Laëtitia Matignon
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. How- ever, 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, impor- tant considerations, and potential areas for future research.