WereWolf-Plus: An Update of Werewolf Game setting Based on DSGBench

TL;DR

WereWolf-Plus is a comprehensive benchmarking platform designed to evaluate multi-agent strategic reasoning in the Werewolf game, addressing previous limitations with extensibility, diverse roles, and detailed metrics.

Contribution

It introduces a multi-model, multi-dimensional platform with customizable roles and new evaluation metrics, enhancing the assessment of social reasoning in multi-agent systems.

Findings

Supports customizable roles like Seer, Witch, Hunter, Guard, Sheriff

Provides extensive quantitative metrics for all roles

Enables evaluation of reasoning, cooperation, and social influence

Abstract

With the rapid development of LLM-based agents, increasing attention has been given to their social interaction and strategic reasoning capabilities. However, existing Werewolf-based benchmarking platforms suffer from overly simplified game settings, incomplete evaluation metrics, and poor scalability. To address these limitations, we propose WereWolf-Plus, a multi-model, multi-dimensional, and multi-method benchmarking platform for evaluating multi-agent strategic reasoning in the Werewolf game. The platform offers strong extensibility, supporting customizable configurations for roles such as Seer, Witch, Hunter, Guard, and Sheriff, along with flexible model assignment and reasoning enhancement strategies for different roles. In addition, we introduce a comprehensive set of quantitative evaluation metrics for all special roles, werewolves, and the sheriff, and enrich the assessment dimensions for agent reasoning ability, cooperation capacity, and social influence. WereWolf-Plus provides a more flexible and reliable environment for advancing research on inference and strategic interaction within multi-agent communities. Our code is open sourced at https://github.com/MinstrelsyXia/WereWolfPlus.