Nim
Nim
Description
Nim is an environment for evaluating agents on the classic mathematical strategy game where players remove objects from piles. This environment wraps the Nim implementation from TextArena, a framework for text-based game environments.
Capabilities
- Mathematical strategy and game theory
- Optimal play discovery through combinatorial reasoning
- Sequential decision-making with perfect information
- Two-player competitive gameplay against an LLM opponent
Compute Requirements
Nim does not require a sandbox. It has minimal compute requirements.
License
MIT.
Tasks
There are two splits: train (50 tasks) and test (50 tasks). Each split contains 50 tasks across each of 1 variants:
- Nim-v0
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:
remove_objects(pile, quantity): Remove objects from a pile. Specify the pile number and quantity to remove.
Time Horizon
Nim is a multi-turn environment.
Environment Difficulty
Moderate. Nim has a well-known optimal strategy based on binary XOR (nim-sum), requiring mathematical insight or strategic reasoning to play well.
Other Environment Requirements
This environment requires an OpenAI API key (passed via secrets) to power the LLM opponent.
Safety
Agents in Nim interact only with a mathematical 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}
}