Sustainable Smart Farm Networks: A Decision Theory-Guided Deep Reinforcement Learning Approach
This work designs a decision theory (DT)-guided transfer learning (TL) framework that unifying cyber resilience and energy adaptability in agricultural monitoring, advancing methodological innovation with DT-guided TL for stable DRL convergence, and providing design insights for sustainable agricultural cyber-physical systems.