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Home/Authors/Jonathan Hoss

Jonathan Hoss

1 indexed paper

Recent (6 mo)
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Publications per year

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26

Top categories

AI×1ML×1

Frequent co-authors

Noah Klarmann1×

Research Timeline

2026
Bridging the Sim-to-Real Gap in Reinforcement Learning-Based Industrial Dispatching through Execution Semantics

The paper proposes a policy-neutral execution and measurement layer to mediate between reinforcement learning policies and industrial environments, transforming ambiguous execution failures into structured, attributable data for improved reliability and interpretability.

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Papers

cs.AIcs.LGRecentMay 27, 2026

Bridging the Sim-to-Real Gap in Reinforcement Learning-Based Industrial Dispatching through Execution Semantics

Jonathan Hoss, Noah Klarmann

The paper proposes a policy-neutral execution and measurement layer to mediate between reinforcement learning policies and industrial environments, transforming ambiguous execution failures into struc…

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