Replace random 2-player pairing with the full §6.1 algorithm:
- Seed selection: bot with oldest last-match timestamp (tiebreak: lowest bot ID)
- Format selection: seed's least-played player count among {2, 3, 4, 6}
- Opponent selection: Pareto 80%/16-rank skill proximity + oldest last-pairing
with seed + fewest 24h games for game-count balance
- Map selection: least-recently-used active map for the chosen player count,
with map_scores.last_used_at updated after each match
- Random player slot assignment for all participant counts
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
|
||
|---|---|---|
| .. | ||
| .github/workflows | ||
| Dockerfile | ||
| grid.py | ||
| main.py | ||
| README.md | ||
| requirements.txt | ||
acb-starter-python
Python 3 starter kit for AI Code Battle — a competitive bot programming platform.
Quick Start
# Run locally
pip install -r requirements.txt
BOT_SECRET=dev-secret python3 main.py
# Run with Docker
docker build -t my-bot .
docker run -e BOT_SECRET=your-secret -p 8080:8080 my-bot
Your bot listens on port 8080 and responds to POST /turn with move commands.
Register Your Bot
Once your bot is deployed and accessible via HTTPS:
curl -X POST https://api.aicodebattle.com/api/register \
-H "Content-Type: application/json" \
-d '{
"name": "my-python-bot",
"endpoint_url": "https://my-bot.example.com",
"owner": "your-name",
"description": "My awesome bot"
}'
Save the bot_id and shared_secret from the response — the secret is shown only once.
Project Structure
main.py # HTTP server, HMAC auth, and strategy entry point
grid.py # Grid utilities (toroidal distance, BFS, neighbors)
requirements.txt # Python dependencies (stdlib only for this starter)
Dockerfile # Container build
Grid Helpers
grid.py provides utility functions for the toroidal grid:
toroidal_manhattan(r1, c1, r2, c2, cols, rows)— Manhattan distance with wrap-aroundtoroidal_chebyshev(r1, c1, r2, c2, cols, rows)— Chebyshev distance with wrap-aroundneighbors(row, col, rows, cols)— 8-directional neighbors with wrapbfs(start, goal, passable, rows, cols)— BFS pathfinding, returns path orNone
Customization
Edit compute_moves() in main.py to implement your strategy. The GameState object provides:
bots— all visible bots (yours and enemies)energy— visible energy pickup locationscores— visible core positionswalls— visible wall positionsyou_energy— your current energy countyou_score— your current scoreconfig— match parameters (grid size, etc.)
Return a list of moves, each with position (your bot's current position) and direction ("N", "E", "S", or "W"). Bots not included in the moves list stay in place.
Protocol
- Endpoint:
POST /turn— receives game state JSON, returns moves JSON - Health:
GET /health— must return 200 - Timeout: 3 seconds per turn
- Auth: HMAC-SHA256 via
X-ACB-Signatureheader