Corrected source review
The active manuscript removes unsupported calibration, comparison, optimality and participant-study claims. Direct assembly requires its evaluation-evidence appendix, and prospective evaluation has explicit acceptance criteria. Native conversion, model-state loading and CI contracts have regression tests. Historical model checkpoints, datasets and participant/statistical observations remain unrecovered.
This review is bound to the linked source commit. Current summaries, downloads and extracted text retain their own source provenance; these corrections do not recover missing historical evidence or constitute a newly deposited publication edition.
Read the pinned source correction (reviewed 2026-11-05).
Overview
Curated abstract when available.
The Markdown Decision Process (MDP) framework treats Markdown documents as stochastic decision processes, enabling intelligent analysis, generation, and optimization through probabilistic modeling. Drawing from Markov Decision Process and POMDP theory, the framework operates at Marr's three levels: computational, algorithmic, and implementational. Key innovations include MarkChain for document generation, PolicyOptimizer for reinforcement learning optimization, and BeliefUpdater for probabilisti
Overview source: Curated paper metadata.
Artifacts
Tracked documentation and PDFs served directly from this folder.
README AGENTS SKILL Metadata Extracted text Citation metadata
- 2025_MarkdownDecisionProcess.pdf 796,266 bytes · extracted-text source
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