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ar25

Select an object or separator band, push it, and cover every yellow target block with an object or its image.

8 levels · 8 rules · all levels replayed in Lean

Replay

The certified run that cleared every level, one action at a time.

ar25, first frame of the certified run

Press Play or step to load the run. Keys, while the player is on screen: ← → step, Space play / pause. A click is circled; cells that changed are outlined.

How it plays

The screen has black objects, light-blue separator bands (whole rows or whole columns) and yellow target blocks; the dark grey ones are the mirror images of the objects. First click once to select an object or a separator band, then use the arrow keys to push it one cell. The separator bands are mirrors: each object has an image with respect to each band, and when an object is pushed the image moves along with it, when a band is pushed the mirror moves one cell and the image moves two cells; when one horizontal and one vertical band cross, there is also one more image, rotated half a turn about the intersection. The level is cleared when every yellow target block is covered by an object or by its image. A band drawn solid cannot be pushed; pushing it off the board, or against another object, cannot be pushed either; images that land off the board are not drawn. There is also a key that makes the selected one step back one step.

ar25, first frame of the certified run
Start
ar25, last frame of the certified run
After the winning move

Model

The final model: 6 object types and 8 rules. Each rule is a Python check against every recorded step; 5 of them are translated into Lean (the paper's per-game table). Code under a rule is the file of the same name in the agent's Lean project.

Object types

Rules

Code is shown with comments and the agent's notes removed; the files as written are in the archive under Check it yourself.

Proof

For every level, Lean starts from the level's first screen, applies the model's rules to the certified actions, and checks that every computed state agrees with the recorded frame on the components the model represents, and that the last one wins. Each theorem is closed by the Lean kernel and is a statement about the learned model.

Every level can be won

theorem Game.Levels.L0_winnable : Winnable L0_board (L0_start : World) := …
theorem Game.Levels.L1_winnable : Winnable L1_board (L1_start : World) := …
theorem Game.Levels.L2_winnable : Winnable L2_board (L2_start : World) := …
theorem Game.Levels.L3_winnable : Winnable L3_board (L3_start : World) := …
theorem Game.Levels.L4_winnable : Winnable L4_board (L4_start : World) := …
theorem Game.Levels.L5_winnable : Winnable L5_board (L5_start : World) := …
theorem Game.Levels.L6_winnable : Winnable L6_board (L6_start : World) := …
theorem Game.Levels.L7_winnable : Winnable L7_board (L7_start : World) := …

What cannot be won under the model

theorem Game.unsolvable_of_invariant (b : Board) (P : World → Prop)
    (hkeep : ∀ w w' a, Act.legal a = true → P w → step b w a = .ok w' → P w')
    (hwin : ∀ w a, P w → step b w a ≠ .won) :
    ∀ (w : World), P w → Unsolvable b w := …

Statements only; the proofs and the full Lean project are in the archive, with the steps to re-run them, under Check it yourself.

Check it yourself

Everything on this page comes from files you can download and check. The archive holds the agent's files: the recorded run, the concept book, the concept sources, the Lean project and the sealed model file, plus the record of our kernel check.

Download ar25.zip 0.3 MB · 44 files

Re-run the proof

Before you start: our run of this check took 78 s and 5.4 GB of memory at its peak (2026-10-23).

  1. Download ar25.zip and unpack it. The model and its theorems are in archive/ar25-20260920/formal/Game.lean. Before changing it, check that its SHA-256 is
    e7af25060c66dd1183083403dabd4cbe9c7d34f649c56868fd4f424b4e1ff36c
  2. Install Lean with elan, then the version named in the archive's lean-toolchain:
    elan toolchain install leanprover/lean4:v4.34.0
  3. Copy the model file to Check.lean and append these two lines to the copy:
    #print axioms consistent
    #print axioms faithful
  4. In the folder that holds Check.lean, run:
    lean +leanprover/lean4:v4.34.0 -M60000 Check.lean
  5. Lean should finish without errors and print:
    GUARD_HITS act1_up=90,act2_down=111,act3_mover_left=113,act4_mover_right=67,act5_inert=1,act6_select=32,act7_undo_step=3,band_is_line=457,counter_tick=439,frame_is_render=457,level_clear=394,mirror=457,one_selected=457,overlap_render=457
    'consistent' depends on axioms: [propext]
    'faithful' depends on axioms: [propext]
    The first line is printed by the file itself: for each rule, how many recorded transitions meet its condition.

What a pass establishes

consistent: for every recorded transition, as read by the agent's parser and with duplicates removed, every rule whose condition holds also has its effect hold. faithful: the certified run, recomputed step by step from the first screen of each level, matches the record and ends in a win. Axioms used: propext, all among Lean's standard ones.

What it does not establish: that the parser reads the screens correctly (that step runs in Python, outside Lean), or that a rule whose condition never occurs in the record is right. The Python file that produced the readings inside the model file is in the archive at meta/repair-20260928/lib/ar25-20260920/_lib.py.