Pb-MORL learns a multi-objective reward model from preference comparisons and claims to achieve Pareto-optimal policies, outperforming an oracle in energy and highway tasks.
Constrained ordinal opti- mization—a feasibility model based approach,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Preference-based Multi-Objective Reinforcement Learning
Pb-MORL learns a multi-objective reward model from preference comparisons and claims to achieve Pareto-optimal policies, outperforming an oracle in energy and highway tasks.