README.md

metadata

license: mit
pretty_name: Hexo Human Corpus (encoding-free)
task_categories:
  - other
tags:
  - hex
  - hex-tac-toe
  - board-games
  - game-records
  - reinforcement-learning
  - alphazero
size_categories:
  - 1K<n<10K

Hexo Human Corpus

Encoding-free corpus of 6,902 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 moves in 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")]
print(len(games), "games")          # 6902
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 sha256 and counts.

License: MIT.