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re86

Push coloured objects around; the level is cleared when each ring centre is covered by a same-colour object.

8 levels · 12 rules · all levels replayed in Lean

Replay

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

re86, 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

There are several coloured objects on the board (cross, diagonal cross, diamond, hollow square frame, horizontal line), and the white cursor sits at the centre of the one currently being controlled. The up, down, left and right keys push this whole object by 3 cells, and the switch key moves the cursor to another object. The dark small square frames are rings, and the colour at a ring's centre says which colour of object it is to be covered by. The solid-colour blocks in the grey frame are colour blocks, and an object that touches one turns entirely into this colour. The light-grey solid blocks are blockers and do not move: when a cross hits one, its two bars each go their own way; a hollow square frame that hits one changes shape, with the perimeter unchanged. The level is cleared when every ring centre is covered by an object of the same colour. The bottom row is the counter bar.

re86, first frame of the certified run
Start
re86, last frame of the certified run
After the winning move

Model

The final model: 7 object types and 12 rules. Each rule is a Python check against every recorded step; 8 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 L0_winnable : Winnable L0_board (L0_start : World) := …
theorem L1_winnable : Winnable L1_board (L1_start : World) := …
theorem L2_winnable : Winnable L2_board (L2_start : World) := …
theorem L3_winnable : Winnable L3_board (L3_start : World) := …
theorem L4_winnable : Winnable L4_board (L4_start : World) := …
theorem L5_winnable : Winnable L5_board (L5_start : World) := …
theorem L6_winnable : Winnable L6_board (L6_start : World) := …
theorem L7_winnable : Winnable L7_board (L7_start : World) := …

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 re86.zip 0.9 MB · 72 files

Re-run the proof

Before you start: our run of this check took 348 s and 7.5 GB of memory at its peak (2026-10-24).

  1. Download re86.zip and unpack it. The model and its theorems are in archive/re86-20260909/formal/Game.lean. Before changing it, check that its SHA-256 is
    0f3ac1ac54ecf843898ded06dea0ea7fae44624b7c6189aa2dc7487022c0e737
  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 a1_up=415,a2_down=274,a3_left=340,a4_right=274,edge_clips_arm=100,arm_len_fixed=1303,blocked_deforms=25,bar_len_conserved=25,blocked_rect_trades=65,rect_trade_needs_room=1,swatch_recolors_object=1394,other_cross_static=1394,a5_switch=60,a5_cycle_order=60,center_cell_persists=1454,diamond_center_hollow=1454,rect_center_hollow=1454,cursor_is_bbox_center=1454,cursor_hidden_by_object=1454,active_center_when_hidden=60,cursor_layer=1454,blocker_is_terrain=1454,shape_over_ring=1454,furniture_restores=1454,hud_fill_right=1454,hud_delta_01=1454,zorder_fixed_order=1454,all_on_target_levels_up=21,spent_resets_on_levelup=19,no_levelup_unless_aligned=1447,wrong_color_cover_no_levelup=3
    '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/re86-20260909/_lib.py.