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Hexo Human Corpus
Encoding-free corpus of decisive human Hex Tac Toe games — hexagonal grid, six-in-a-row to win (player 1 opens with 1 move, then both players play 2 moves per turn; the board is theoretically infinite).
Each line is one game as a raw axial move list + outcome. Nothing about any
neural-network encoding is baked in — no planes, no fixed board size, no action
space. Read it with the stdlib json module and build whatever representation
you want.
Files
| file | description |
|---|---|
hexo_human_corpus.jsonl |
the corpus — one game per line |
SCHEMA.md |
full per-line schema + conventions |
dataset_metadata.json |
provenance: counts, sha256, source filter |
Schema
One JSON object per line:
{"game_hash":"0f8c6bdfc55e7f6f","moves":[[0,0],[2,-2],[-3,3]],"winner":1,"source":"human","elo":[898,955]}
| field | type | meaning |
|---|---|---|
game_hash |
string (16 hex) | SHA-256 of the move sequence — stable content/dedup key |
moves |
array of [x, y] |
axial hex coords (x,y)=(q,r), in play order |
winner |
1 or -1 |
1 = first player (X) wins, -1 = second player (O) |
source |
string | "human" |
elo |
[int|null, int|null] |
[elo_p1, elo_p2] |
Conventions
- Axial hex coordinates
(x, y); the board is infinite so values can be negative. The first player's forced opener is always(0, 0). - Replay
movesin order to reconstruct any board state. - Only decisive (six-in-a-row) games are included — there are no draws.
Usage
import json
games = [json.loads(line) for line in open("hexo_human_corpus.jsonl")]
g = games[0]
print(g["moves"], g["winner"]) # [[0,0], [2,-2], ...] 1
Provenance
Rated human games filtered to: rated, ≥20 moves, decisive by six-in-a-row.
Per-game elo is each player's rating at game time. Games are anonymised
(player ids dropped; only relative Elo retained). See dataset_metadata.json
for the exact game count and sha256.
License: MIT.
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