Repo · Benchmarks & research
mcts-agent
Discriminative Monte Carlo Tree Search using TypeSafe Jev System One Primitives and Gemini.
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Discriminative Monte Carlo Tree Search using System One and Harnesses
How builders describe it
Python agent that runs Discriminative MCTS with Jev judging and Gemini 3.8 Flash proposing. Choice supplies action priors and branching width, Score evaluates states on a 1-10 rubric, and Noul checks execution and ends the loop at 0.85 confidence, with a local web UI for following runs.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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