Replacing Markdown with POMDP State Graphs Boosts Agent Success Rate by ~20%
Mysterious-Try-1966 · reddit · 2026-07-30
The author found that traditional flat Markdown files or GraphRAG make it difficult to pinpoint failure nodes when an agent's chain of actions breaks. To solve this, they modeled the agent's context as a Partially Observable MDP (POMDP):
- Graph Structure Design: Observable states become nodes, actions become edges, weighted by success probability, token cost, and outcome. The agent explores to complete the graph and then exploits it like standard RL.
- Results: Across the same task batch (tested with Claude Opus 4.8 and Codex GPT-5.5), this approach increased the task success rate from an average of 0.78 to 0.95, at a lower token cost than the flat file approach.
This framework effectively addresses the explicability and convergence bottlenecks when agent pipelines fail.
Related event: POMDP State Graphs Boost Agent Success Rates(2 posts)→
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