| --- |
| license: mit |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - maze |
| - world-model |
| - pathfinding |
| - sequence-modeling |
| pretty_name: World Model for Maze (with X) |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # WorldModelForMazeWithX |
|
|
| Maze pathfinding sequences for training/probing sequence models (Transformer, Mamba, GRU, Gated-DeltaNet, ...). Task **C1**: relative-turn navigation on a fixed 10×10 directed grid. Includes a special **`x`** terminator marking wall-hit (illegal) paths, used to study a model's ability to recognize its own errors. |
|
|
| ## Maze |
|
|
| - 10×10 grid, 100 nodes (`0`–`99`). Directed edges (down/right, both directions added), edge probability 0.6. |
| - Graph: `maze_graph_C1_RWs.graphml` (node ids are strings `'0'`..`'99'`). |
|
|
| ## Sequence format (Task C1) |
|
|
| ``` |
| C <src> <tgt> : <turn tokens...> |
| ``` |
|
|
| - Agent starts facing **East**. Each turn token both rotates and advances one cell: |
| - `F` forward, `L` left, `R` right, `T` turn-around. |
| - Nodes `0`–`99` are single tokens; `:` separates the prompt from the path. |
| - **`x`**: wall-hit terminator. A "wrong" path is a correct path with one turn corrupted into a wall direction, then `x` appended. Only the final `x` is supervised during training. |
|
|
| ## Files (under `data/`) |
|
|
| | file | rows | wrong (`x`) ratio | note | |
| |------|------|-------------------|------| |
| | `train_C1_RWs_5M.txt` / `.bin` | 5,000,000 | 0.0 | all-correct paths | |
| | `train_C1_RWs_8M.txt` / `.bin` | 8,000,000 | 0.0 | all-correct paths | |
| | `train_C1_RWs_10M.txt` / `.bin` | 12,000,000 | 0.2 | 2M wall-hit paths ending in `x` | |
| | `test_C1_RWs_10K.txt` | ~10K | — | held-out test prompts | |
| | `val_C1_RWs_10K.bin` | — | — | tokenized validation | |
| | `meta_C1_RWs.pkl` | — | — | vocab/stoi/itos (vocab size 132, `x` id 131) | |
| | `maze_graph_C1_RWs.graphml` | — | — | the maze graph | |
|
|
| - `.txt`: human-readable sequences. `.bin`: `uint16` token stream (read with `numpy.memmap`). `.bin` can be regenerated from `.txt` via `prepare_multitask_minigpt.py`. |
| - Only the **10M** set contains wrong paths; 5M / 8M never expose `x` (models trained on them never emit `x`). |
|
|
| ## Loading |
|
|
| ```python |
| import pickle, numpy as np |
| meta = pickle.load(open("data/meta_C1_RWs.pkl", "rb")) |
| itos = meta["itos"] # x token id = 131 |
| ids = np.memmap("data/train_C1_RWs_10M.bin", dtype=np.uint16, mode="r") |
| print(" ".join(itos[i] for i in ids[:60])) |
| ``` |
|
|
| ## Citation |
|
|
| Generated with `data/maze/create_multitask_maze.py` (`--tasks C1 --path_type RWs`, `--wrong_ratio 0.2` for 10M, `0.0` for 5M/8M). |
|
|
