Preference-Guided Multi-Policy Optimization for Flexible Job Shop Scheduling
PGMPO is proposed, a novel learning framework consisting of a simple but effective multi-policy modeling approach that allows a single network to represent multiple decision-makers, and a preference-driven model optimization method that effectively guides policies to learn diverse and specialized problem-solving strategies without the need for explicit reward functions.
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho et al.
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