Snake
Snake
Description
Snake is an environment for evaluating agents on the classic multiplayer snake game. This environment wraps the Snake implementation from TextArena, a framework for text-based game environments.
Capabilities
- Spatial navigation and path planning
- Collision avoidance with walls, trails, and opponents
- Real-time strategic decision making
- Evaluation across multiple grid size variants
Compute Requirements
Snake does not require a sandbox. It has minimal compute requirements.
License
MIT.
Tasks
There are two splits: train (450 tasks) and test (450 tasks). Each split contains 50 tasks across each of 9 variants:
- Snake-v0
- Snake-v0-large
- Snake-v0-large-raw
- Snake-v0-large-train
- Snake-v0-raw
- Snake-v0-standard
- Snake-v0-standard-raw
- Snake-v0-standard-train
- Snake-v0-train
Each task is seeded for reproducibility.
Reward Structure
This is a sparse reward environment. Rewards are mapped from TextArena's native range of {-1, 0, 1} to {0.0, 0.5, 1.0} via (raw + 1) / 2.
We do not use LLM graders for this environment; reward is determined programmatically.
Data
Game state is generated procedurally by the TextArena engine using seeded randomness. No external data files are required.
Tools
Agents are given a single tool:
move(direction): Move your snake in the specified direction (up/down/left/right).
Time Horizon
Snake is a multi-turn environment.
Environment Difficulty
Medium - requires spatial awareness and planning ahead.
Other Environment Requirements
This environment requires an OpenAI API key (passed via secrets) to power the LLM opponent.
Safety
Agents in Snake interact only with a multiplayer game and have no access to external systems, the internet, or sensitive data. The environment does not present safety risks.
Citations
@software{textarena2024,
author = {Guertler, Leon and Banting, Wilfried and Pignatelli, Eduardo},
title = {TextArena},
year = {2024},
publisher = {GitHub},
url = {https://github.com/LeonGuertler/TextArena}
}