Introduces an execution semantics layer for event-driven industrial dispatching that constructs valid decision snapshots, standardizes action admissibility, and attributes multi-level execution divergences to reduce sim-to-real mismatch in RL policies.
Digital twins in Industry 5.0,
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Bridging the Sim-to-Real Gap in Reinforcement Learning-Based Industrial Dispatching through Execution Semantics
Introduces an execution semantics layer for event-driven industrial dispatching that constructs valid decision snapshots, standardizes action admissibility, and attributes multi-level execution divergences to reduce sim-to-real mismatch in RL policies.