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genpark-markov-decision-process-value-iteration-skill

mcp
Guvenlik Denetimi
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SUMMARY

GenPark AI Agent Skill - Infinite-horizon Markov Decision Process (MDP) solver computing optimal state-value functions and greedy action policies via Bellman value iteration.

README.md

GenPark Markov Decision Process Value Iteration Skill

Bellman value iteration solver computing optimal values and policies for stochastic Markov Decision Processes.

Explore more at GenPark and the GenPark MCP Catalog.

graph TD
    A[Current Value Estimates V_k] --> B[Bellman Optimality Backup]
    B --> C[max_a sum P(s'|s,a) (R + gamma * V_k(s'))]
    C --> D[Update V_k+1(s)]
    D --> E{Max Delta < Threshold?}
    E -->|No| A
    E -->|Yes: Convergence| F[Extract Optimal Greedy Policy pi*]

Features

  • Bellman optimality equation backup.
  • Configurable discount factor gamma and convergence threshold theta.
  • Pure Python standard library.

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