AWM
← All games‹ vc33ar25 ›

wa30

Drag every doughnut into a blue-framed container; the level is won when all sit there and nothing is carried.

9 levels · 8 rules · all levels replayed in Lean

Replay

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

wa30, 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 green square is the player; the white edge on top shows which way it faces. Every doughnut has to be brought into a blue-framed container. With empty hands, an arrow key turns the player and, where the way is open, moves it one cell; next to a piece of cargo, the action key grabs it, after which the arrow keys move the player and the cargo together, and pressing the action key again lets go. Cargo can enter fenced areas; the player cannot. After every step each mole on the field moves once: the orange helpers carry cargo that is not in a container into one, and the purple thieves carry cargo back to their own nest, even cargo the player is holding; pressing the action key while facing a thief knocks it out. The level is won when every doughnut sits in a container, the player holds nothing and no mole is carrying anything. The pink timer bar along the bottom shortens with each step; when the steps run out before the level is won, the game is over.

wa30, first frame of the certified run
Start
wa30, last frame of the certified run
After the winning move

Model

The final model: 8 object types and 8 rules. Each rule is a Python check against every recorded step; 7 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.Lv0.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv0.board Game.Lv0.start as = true := …
theorem Game.Lv1.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv1.board Game.Lv1.start as = true := …
theorem Game.Lv2.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv2.board Game.Lv2.start as = true := …
theorem Game.Lv3.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv3.board Game.Lv3.start as = true := …
theorem Game.Lv4.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv4.board Game.Lv4.start as = true := …
theorem Game.Lv5.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv5.board Game.Lv5.start as = true := …
theorem Game.Lv6.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv6.board Game.Lv6.start as = true := …
theorem Game.Lv7.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv7.board Game.Lv7.start as = true := …
theorem Game.Lv8.winnable :
    ∃ as : List Game.Act, Game.everGoal Game.step Game.Lv8.board Game.Lv8.start as = true := …

What cannot be won under the model

theorem Game.unsolvable_of_invariant (b : Board) (P : St → Prop)
    (hkeep : ∀ s s' a, P s → step b s a = .ok s' → P s')
    (hwin : ∀ s a s', P s → step b s a ≠ .won s') :
    ∀ s, P s → ∀ as : List Act, everGoal step b s as = false := …

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 wa30.zip 0.7 MB · 79 files

Re-run the proof

Before you start: our run of this check took 478 s and 23.1 GB of memory at its peak (2026-10-24).

  1. Download wa30.zip and unpack it. The model and its theorems are in archive/wa30-20260920/formal/Game.lean. Before changing it, check that its SHA-256 is
    e367f8f2fab17834869bee1bdbc5e3082bd9ef70f4292779239c48149e477bf2
  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 action1_up=715,action2_down=557,action3_left=1030,action4_right=1051,head_faces_last_move=4022,capsule_walkable=22,donut_drag_follows=1311,donut_drop_on_leave=208,donut_enters_capsule=130,donut_grab_toggle=669,donut_push_activate=3353,donut_take_back_from_mole=1254,drag_released_by_thief_block=4,grab_refused_by_still_thief=14,killed_mole_drops_cargo=5,action5_vanishes_adjacent_mole=24,action5_inert_without_target=327,levelup_on_release_iff_all_seated=349,win_needs_all_donuts_home=3808,mole_alert_ring_when_adjacent=4022,mole_blocks_move=27,mole_carry_above=2210,mole_drop_in_capsule=2210,mole_drop_target_by_skin=2210,mole_steal_on_block=1369,stolen_donut_blocks_move=7,thief_step_rule=1765,thief_strips_drag=538,timer_bar_drains=4022,thief_patrol_next=388
    '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/wa30-20260920/_lib.py.