Chessenv

API Endpoint
Leaderboard
Loading leaderboard...
README

Chessenv

OpenReward Environment

Description

Chessenv is an ORS environment for evaluating agents on playing chess against an LLM opponent. This environment wraps the Chess implementation from TextArena, a framework for text-based game environments.

Capabilities

  • Strategic planning and tactical execution in chess
  • Position evaluation and move generation
  • Opening theory, middlegame strategy, and endgame technique
  • Testing long-horizon planning and competitive gameplay

Compute Requirements

Chess does not require a sandbox. It has minimal compute requirements.

License

MIT.

Tasks

There are two splits: train (150 tasks) and test (150 tasks). Each split contains 50 tasks across each of 3 variants:

  • Chess-v0
  • Chess-v0-blind
  • Chess-v0-long

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:

  • make_move(move): Make a chess move in UCI format (e.g. 'e2e4', 'g1f3', 'e7e8q' for promotion).

Time Horizon

Chess is a multi-turn environment.

Environment Difficulty

Hard to Very Hard. Chess requires deep strategic thinking, position evaluation, tactical calculation, and long-term planning. The blind variant increases difficulty by limiting board visibility.

Other Environment Requirements

This environment requires an OpenAI API key (passed via secrets) to power the LLM opponent.

Safety

Agents in Chess interact only with a board 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}
}
GeneralReasoning/Chessenv | OpenReward