| --- |
| license: cc0-1.0 |
| pretty_name: "Faïence human-vs-net Azul games" |
| tags: |
| - game-records |
| - azul |
| - reinforcement-learning |
| - human-play |
| --- |
| |
| <!-- Source of truth for this card: web/ingest/DATASET.md in |
| https://github.com/RemiFabre/ludometer --> |
| |
| # Faïence: human-vs-net Azul games |
|
|
| Every game played on [Faïence](https://remifabre-faience.static.hf.space/), a |
| free browser implementation of the rules of *Azul* (Michael Kiesling) against |
| a neural net trained by self-play, unless the player switched sharing off. |
| This dataset is the training pile the playing page tells its players about, |
| and it is public precisely so that a player can read everything the project |
| collects. Records are anonymous by construction: moves, deals, which net |
| played, and the score. No names, no accounts, no IPs, no user agents. |
|
|
| ## Layout |
|
|
| `games/YYYY-MM-DD/<timestamp>-<n>.jsonl`, one file per ingest batch, one JSON |
| object per line. Nothing is ever rewritten; new batches only add files. |
|
|
| ## Record format (`faience-game/1`) |
|
|
| Each line is a canonical record rebuilt by the collector |
| ([RemiFabre/faience-ingest](https://huggingface.co/spaces/RemiFabre/faience-ingest)), |
| which replayed the game in the real engine and kept it only if the recorded |
| deals, final scores and round count reproduce exactly. Fields: |
|
|
| - `received_at` (server clock, ISO) and `created_at` (client clock, may be null) |
| - `seed`: the game's RNG seed (mulberry32, the page's own RNG) |
| - `human_seat`, `human_first`: which of the two seats the human held |
| - `net`: `{run, checkpoint, elo, params, backend}` of the opponent |
| - `think_time_s`: the AI's search budget per move (0 = policy head only) |
| - `moves`: `[{ply, player, action, sims?, value?}]`, `action` encoded as |
| `source*30 + color*6 + dest` (identical in the JS and Python engines); |
| `sims` is the positions the net searched for its move on the visitor's |
| machine, `value` its root value on a [-1, 1] scale |
| - `deals`: per round, the five factories plus bag and lid counts, so a record |
| replays independently of any RNG port |
| - `final`: `{finished, scores, outcome, rounds, exhausted}`; `finished: |
| false` marks an abandoned game (position data with no outcome; train the |
| value head on these with care, or not at all) |
|
|
| ## Caveats |
|
|
| - The collector deduplicates retried submissions by content, but a restart |
| can rarely let a duplicate through: deduplicate by |
| `(seed, human_seat, moves, final.scores, final.finished)` when it matters. |
| - An abandoned game that was later resumed and finished in the same tab can |
| appear twice: once `finished: false`, once `finished: true` with the same |
| seed and a longer move list. Prefer the finished one. |
| - Play strength varies wildly: these are self-selected browser visitors, from |
| first-time players to strong club players. |
|
|
| ## Provenance and license |
|
|
| Collected by the [Faïence ingest Space](https://huggingface.co/spaces/RemiFabre/faience-ingest) |
| from the [Faïence playing page](https://remifabre-faience.static.hf.space/); |
| code and methodology in [RemiFabre/ludometer](https://github.com/RemiFabre/ludometer). |
| The records are dedicated to the public domain (CC0). Azul is a game by |
| Michael Kiesling; this fan research project is not affiliated with or |
| endorsed by its publishers. |
|
|
