---
title: PUCT
family: tree-search
summary: A complete but unrun tree search that starts from a prior about which columns are worth trying.
status: unknown
evidence: repository-verified
reads: public
---

A tree search that starts from a hunch about which columns are worth trying,
and is allowed to overrule the existing policy only when it is very sure.

<EvidenceLabel status="unknown" evidence="repository-verified" reads="public" />

<Callout title="No retained result" tone="warn">
This lab is complete, compiles, carries its own preregistered seed lanes and
frozen acceptance rules, and there is no record anywhere in this repository
that it was ever run. The [experiment index](/docs/research/experiment-index)
gives it the status **Unknown**: "the source exists, but neither the ledger nor
the task record establishes a trustworthy outcome." Everything on this page is
read from the source.
</Callout>

## The idea

The plain [Monte Carlo tree search](/approaches/tree-search/observable-mcts)
next door starts every position knowing nothing. Its first simulations are
spent equally on all seven columns, including columns that any reasonable
player would reject immediately, and it only learns to avoid them by trying
them. In a game where a decision budget buys a few hundred simulations, that is
a lot of the budget spent confirming the obvious.

PUCT — "predictor + upper confidence bounds applied to trees", the selection
rule made famous by AlphaGo — adds a **prior**: a cheap opinion, formed before
any simulation, about how plausible each column is. Columns the prior likes are
tried first and often; columns it dislikes are not forgotten, but must earn
attention. The prior here is not a neural network. It is three quick sampled
probes per column using the repository's shared phase policy, turned into a
distribution over columns by a softmax with a fixed temperature.

The second idea in this lab is caution. The search is not the player. The
player is the existing phase policy, and the tree is only allowed to change its
mind when the tree is emphatic: the challenger column must have been visited
at least a minimum number of times, must hold a large share of all visits, and
must lead by more than a fixed margin in value. Four such rules of increasing
strictness are laid out side by side so a run would show how the outcome
depends on how brave the override is.

## How it works, step by step

1. Read the public position: board, visible next disc, moves until the next
   rise, terminal flag. Ask the shared phase policy for its action; that is the
   baseline.
2. Form a prior over the legal columns from three sampled probes each,
   flattened through a softmax with temperature 0.75.
3. Run 256 simulations over an eight-move horizon, with at most 4,096 stored
   positions. Selection scores each column by its average result plus an
   exploration term proportional to its prior and to how little it has been
   visited relative to its parent.
4. Compare the tree's favourite with the baseline. Accept the switch only if
   the challenger has at least 32 visits, more than 65% (or 80%) of the visit
   share, and a normalized advantage over the baseline above 0.10 (or 0.25).
   Otherwise play the baseline's column.

Simulation, gray-disc reveal and next-disc randomness each draw from a separate
domain of the solver's own random stream, so the search's imagined futures
cannot line up with the game's real ones.

## What happened

Nothing happened. The approach has a finished
experiment with no result.

It is not an oversight so much as a queue. The research roadmap places PUCT
last in a sequence — first get a model that ranks moves safely, then let it
override the reference conservatively, then batch and widen. It sets one firm
rule: "Do not begin with learned action pruning. Every legal root
action remains eligible until the model has independently demonstrated safe
sibling ranking." A search that concentrates its budget by prior is exactly the
kind of thing that rule is holding back until the ranking problem is solved.

Meanwhile the family's other results argue both for and against running it.
Against: the scaled observable search showed that a bigger, better-directed
tree became a better imitator of short-horizon values while getting *worse* at
predicting long outcomes, and a prior directs the tree, it does not change what
the playouts believe. For: this is a complete program with frozen gates whose
cost an exploratory audit estimated at roughly one to three CPU-hours, and
running an experiment that already exists is cheaper per unit of knowledge than
writing a new one.

<TechnicalDetails title="The technical record">

There is no result record, no ledger entry and no artifact. What exists:

- Preregistered lanes in the source: an eight-game screen and an eight-game
  confirmation, on separate training seed ranges.
- One frozen search configuration — 256 simulations, horizon 8, exploration
  constant 1.25, at most 4,096 nodes, and four override gate profiles
  combining a 0.65 or 0.80 visit share with a 0.10 or 0.25 value margin at a
  minimum of 32 challenger visits.
- Separate random domains for simulations, reveals and next discs; a
  reflection-canonical treatment of mirrored positions; the shared public phase
  policy as both prior source and fallback.
- A build line in the [reproducibility guide](/docs/reproducibility).

[Audit 04](/docs/exploratory/audit-04-blind-spots) — exploratory, read-only —
groups this lab with two others as "finished experiments with zero recorded
outcome", estimates roughly one to three CPU-hours each, and adds a warning
that matters more than the estimate: confirm with the coordinator that the
preregistered seed ranges are still unconsumed before opening them. Eight games
is a screen, not a measurement; even a clean pass here would be a reason to run
a larger cohort, not a result about strength.

</TechnicalDetails>

## What this taught us, and what is still open

- **"Not tried" is not "does not work."** This page exists to keep those two
  apart. Nothing in this repository licenses the sentence "PUCT was tried on
  Drop7 and failed."
- **The open question is narrow and cheap:** does a prior plus a strict
  override gate beat the shared phase policy on its own preregistered eight-game
  screen? A run would produce the family's first result that is about
  *deployment* rather than about ranking stored positions.
- **The prior is the weak point to watch.** It is built from the same phase
  policy that the search is trying to improve, so a run that shows no switches
  would be telling you about the prior, not about PUCT.