Multi-Objective Reinforcement Learning

Learning to identify and settle dilemmas through contextual user preferences
This paper presents a novel Multi-Objective Reinforcement Learning approach to settle dilemmas, by putting humans in the loop.
Rémy Chaput, Laetitia Matignon, Mathieu Guillermin
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PhD Thesis
PhD thesis on Learning behaviours aligned with moral values in a multi-agent system: guiding reinforcement learning with symbolic judgments, realized at the LIRIS lab, under the supervision of Professor Salima Hassas (LIRIS), Professor Olivier Boissier (LaHC), and Dr. Mathieu Guillermin (UCLy).
Rémy Chaput
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