标题： 游戏推理竞技场：通过游戏玩法评估大型语言模型推理能力的框架和基准 显示英文标题

标题： Game Reasoning Arena: A Framework and Benchmark for Assessing Reasoning Capabilities of Large Language Models via Game Play

摘要： 该游戏推理竞技场库提供了一个框架，通过在Google OpenSpiel库中实现的战略棋盘游戏来评估大型语言模型（LLMs）的决策能力。 该框架通过包装多种棋盘和矩阵游戏并支持不同的代理类型，实现了基于LLM的代理与其他代理（随机、启发式、强化学习代理等）在各种游戏场景中的系统比较。 它通过liteLLM集成模型的API访问，通过vLLM实现本地模型部署，并通过Ray提供分布式执行。 本文总结了该库的结构、关键特性以及仓库的动机，强调了它如何促进对LLM推理和博弈论行为的经验评估。 显示英文摘要

摘要： The Game Reasoning Arena library provides a framework for evaluating the decision making abilities of large language models (LLMs) through strategic board games implemented in Google OpenSpiel library. The framework enables systematic comparisons between LLM based agents and other agents (random, heuristic, reinforcement learning agents, etc.) in various game scenarios by wrapping multiple board and matrix games and supporting different agent types. It integrates API access to models via liteLLM, local model deployment via vLLM, and offers distributed execution through Ray. This paper summarises the library structure, key characteristics, and motivation of the repository, highlighting how it contributes to the empirical evaluation of the reasoning of LLM and game theoretic behaviour.