Unverified50% confidenceFactExact time
BLM's method is called "Discretize, Then Decide": starting from workflow logs or LLM agent run data, it reads each conversation as a discrete state and estimates probabilities and costs until no new states appear and the probabilities no longer change, then solves the MDP.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe Bellman Language Model (BLM) models repeated decisions as a Markov decision process (MDP), solves it once and reuses the solution, to improve the efficiency of LLM agents.78% similarVerifiedLLMs are fundamentally probability distribution systems trained on massive amounts of text, where each output is a sampling of the next most likely token rather than retrieval and reasoning based on real-world knowledge.70% similarUnverifiedLLMs compress both the representation and decision stages into a single forward inference pass.69% similarUnverifiedCommon engineering measures to mitigate the out-of-distribution sample problem include: setting confidence thresholds for compiled logic and falling back to the LLM at low confidence, continuously collecting online samples for regression evaluation, and maintaining a shadow mode in which the LLM and local logic run in parallel to monitor deviation.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1074722API
curl https://kongchang.com/api/v1/knowledge/claims/1074722MCP
get_claim(id=1074722)