Feasibility-Aware Reinforcement Learning for Reliable Hop-Constrained Routing in Wireless Sensor Networks
The experiments show that feasibility-aware learning can approach deterministic baseline reliability while retaining learned forwarding capability under hop constraints, and confirm that action masking is the dominant mechanism for maintaining feasible routing decisions, whereas trust mainly provides reliability-aware regularization.