---
title: Rollout
family: heuristic-search
summary: Judge a column by playing twenty-five more moves under several imagined disc streams instead of scoring only the resulting board.
status: rejected
evidence: task-record only
reads: public
---

Instead of judging a column by how the board looks afterwards, play the game
on from there (twenty-five more moves, several imagined disc streams) and
judge it by how that went.

<EvidenceLabel status="rejected" evidence="task-record only" reads="public" />

## The intuition

Every hand evaluator is a guess about the future compressed into a number. A
[rollout](/learn/glossary) replaces the guess with a rehearsal: take the board
that a column produces, keep playing with some quick policy for twenty-five
more moves, and see whether you are still alive and how much you scored. Do
that for each column over several imagined disc streams, and the column that
survives its rehearsals is the one to play.

Twenty-five moves is not an arbitrary number. It is five complete
[rise](/learn/glossary) cycles, so a rollout of that length sees the
consequences of a decision *through* the events that actually kill policies in
this game.

The idea has the best single anecdote in the repository behind it, and also
the clearest demonstration of why an anecdote is not a result. See below.

## How it works, step by step

1. **Read the public position** — board, next disc, rise clock.
2. **For each legal column, build a set of scenarios**: synthetic streams of
   future discs and gray-disc reveals, generated from a hash of the visible
   position so that every column is rehearsed against the same luck.
3. **Play each rehearsal forward** to the horizon with a quick continuation
   policy, accumulating the points actually scored.
4. **Charge a large penalty if the branch dies**, and add one evaluation of
   the final board if it survives.
5. **Collapse each column's rehearsals** into a mean, a lower bound, or a
   worst-quarter average, and play the best.

A second program in this directory does the same thing more expensively and
for a different purpose: it beam-searches each root column across fourteen
fixed synthetic tapes and votes across them, to produce *labels*: a stronger
opinion about which column is best — for training and distillation work rather
than for playing.

## What happened

The playing version was retired. With a weak continuation policy driving the
rehearsals, the rehearsals inherit that policy's mistakes: you are not seeing
what would happen, you are seeing what a weak player would do, twenty-five
times over, and preferring the columns that suit it.

The labelling version was kept, with an explicit warning attached: it is a
useful teacher and benchmark, and it is not a policy anyone may deploy. It
costs far too much per decision, and every one of its plans is made inside a
future it has been told in advance, which is the classic way to make a plan
look better than any real player could achieve.

The strongest version of this idea lives in a different family, and it is
worth knowing what happened to it, because it is the most instructive number
in the repository.

<TechnicalDetails title="The technical record">

**This directory.** The [experiment index](/docs/research/experiment-index)
records the planner as **rejected, task-record only** — *"the tested 25-move
control reproduced the weak continuation policy's mistakes"*, and the teacher
as **completed, task-record only** — *"useful as a teacher/benchmark, not a
deployable policy."* Task-record only means both outcomes are reported in a
research conversation and neither was promoted into the
[experiment history](/docs/research/history). **No cohort, score, or per-game
result for either program is retained in this repository.**

Repository-verified from the source: `rollout.cpp` defaults to a 25-move
horizon and 7 scenarios, with root aggregation selectable as mean, lower
bound, CVaR25 or a blend, one to seven continuation samples, and a scaled
phase-style leaf for surviving branches. `teacher.cpp` defaults to a 25-move
horizon, 14 tapes and a beam of 8 per root action, with optional cross-tape
voting; its tapes are keyed on a hash of the canonical *observable* state —
board, next disc, rise clock, so it reads no hidden value and no real future
disc, but it does plan inside a future it has fixed in advance.

**The properly recorded version of this idea, in the
[D4 long-outcome](/approaches/d4-long-outcome) family.** A 25-move,
seven-scenario continuation driven by a completed depth-2 search, used to veto
the reference search's move, produced a single pilot game of **404,047 points
in 250 moves against 159,616 in 105** for the reference. That is
**ledger-recorded and labelled signal only**: one game, and far outside its
runtime limit. It was rescored to the corrected 17,000-point Hardcore award as
**894,047 against 359,616** in
[audit 04](/docs/exploratory/audit-04-blind-spots), which called it the single
largest unexploited number in the repository.

It was then tested properly.
[Finding 03](/docs/exploratory/finding-03-rollout-veto-17k) is a 32-game
paired screen at corrected scoring — run validity `valid`, scientific outcome
`fail`, evidence tier development. The reference search averaged **339,290
points and 98.66 moves**; the rollout veto averaged **292,780 and 86.34**. The
paired mean difference was **−46,510.5 points and −12.31 moves**, with a
one-sided 95% bootstrap lower bound of −91,924.6, a 9–4–19 win record and a
sign test at p = 0.0436. Clear and reveal rates both fell. The same document
diagnoses why the veto almost never fired: its confidence test required the
mean advantage to exceed 0.92 standard deviations over seven scenarios, and
99.1% of the 12,314 candidate alternatives failed that one condition.

The family produced one spectacular game and a properly
powered retest that went the other way.

</TechnicalDetails>

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

- **A rollout is only as good as the player inside it.** This is the same
  diagnosis the [MCTS work](/approaches/tree-search/observable-mcts) reached
  independently: the bottleneck was the weak continuation policy and the
  reused chance samples, not the number of simulations. Increasing the budget
  buys more of the wrong future.
- **One long game is not evidence, and the repository has now proved that on
  itself.** Score in this game is heavy-tailed; a policy can win a cohort
  because a single game ran unusually long. Finding 03 exists precisely
  because someone refused to let the 404,047-point game stand as a result.
- **What is still open** is affordability. The strategy catalog's second open
  direction is to make multi-cycle sibling comparison cheap by design — a
  cheaper verified continuation, batched transitions, admissible early
  elimination, while keeping the one positive pilot out of parameter
  selection. Multi-cycle comparison remains one of the more informative
  directions in the repository; this implementation of it is not the way to
  get there.