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Anh Khoa Doan Ngoc

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#reinforcement learning Open access Oct 2026

Calibration Does Not Compose, Types Destroy Vagueness: The Hidden-Markov and Fuzzy Primitives Missing from System-One Decision Models

System-one decision models — fast, non-generative networks that emit typed, calibrated probabilistic decisions for machine-to-machine pipelines, of which TypeSafe AI's Jev, trained by Reinforcement Learning for Calibrated Decisions (RLCD), is the announced instance — are audited by hop-level calibration on stationary h...

Anh Khoa Doan Ngoc · 0 citations
#reinforcement learning Open access Sep 2026

Calibration Does Not Compose, Types Destroy Vagueness: The Hidden-Markov and Fuzzy Primitives Missing from System-One Decision Models

System-one decision models — fast, non-generative networks that emit typed, calibrated probabilistic decisions for machine-to-machine pipelines, of which TypeSafe AI's Jev, trained by Reinforcement Learning for Calibrated Decisions (RLCD), is the announced instance — are audited by hop-level calibration on stationary h...

Anh Khoa Doan Ngoc · 0 citations
#reinforcement learning Open access Sep 2026

Calibration Does Not Compose, Types Destroy Vagueness: The Hidden-Markov and Fuzzy Primitives Missing from System-One Decision Models

System-one decision models — fast, non-generative networks that emit typed, calibrated probabilistic decisions for machine-to-machine pipelines, of which TypeSafe AI's Jev, trained by Reinforcement Learning for Calibrated Decisions (RLCD), is the announced instance — are audited by hop-level calibration on stationary h...

Anh Khoa Doan Ngoc · 0 citations

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