Markdown Decision Process: A Framework for Probabilistic Document Analysis

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

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