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cs.LG2026
MIRACL: A Diverse Meta-Reinforcement Learning for Multi-Objective Multi-Echelon Combinatorial Supply Chain Optimisation
Rifny Rachman, Josh Tingey, Richard Allmendinger +3
Multi-objective reinforcement learning (MORL) is effective for multi-echelon combinatorial supply chain optimisation, where tasks involve high dimensionality, uncertainty, and comp…
cs.LG2024
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
Tenglong Liu, Yang Li, Yixing Lan +3
In offline reinforcement learning, the challenge of out-of-distribution (OOD) is pronounced. To address this, existing methods often constrain the learned policy through policy reg…