开源工具CoGrid与MUG让多智能体人机交互实验更易开展
CoGrid & the Multi-User Gymnasium: A Framework for Multi-Agent Experimentation

- 基于网格的双后端仿真库,支持多人与AI协同实验
- 网页化实验平台,可应对任意数量参与者与延迟问题
- 适合心理学、认知科学等领域的交互研究者使用
人工智能日益融入日常生活,带来人机协作的新挑战。多智能体实验有助于研究社会决策行为,但现有工具难以支持研究者开展此类实验。本文提出两个开源工具:CoGrid 是一个支持 NumPy 和 JAX 的多智能体网格仿真库;Multi-User Gymnasium(MUG)则将仿真环境转化为可交互的网页实验平台,支持任意数量的人类与AI参与,采用服务器权威或对等网络加回滚网络协议以应对延迟。二者结合可有效推动人类-智能体交互研究,涵盖心理、认知与决策等领域核心问题。相关文档与代码已公开,网址为 {cogrid, multi-user-gymnasium}.readthedocs.io。本文还展示了多个案例,验证其在人机多智能体实验中的实用性。
原文摘要 · Abstract (English)
The increasing integration of artificial intelligence (AI) in everyday life brings with it new challenges and questions for regarding how humans interact with autonomous agents. Multi-agent experiments, where humans and AI act together, can offer important opportunities to study social decision making, but there is a lack of accessible tooling available to researchers to run such experiments. We introduce two tools designed to reduce these barriers. The first, CoGrid, is a multi-agent grid-based simulation library with dual NumPy and JAX backends. The second, Multi-User Gymnasium (MUG), translates such simulation environments directly into interactive web-based experiments. MUG supports interactions with arbitrary numbers of humans and AI, utilizing either server-authoritative or peer-to-peer networking with rollback netcode to account for latency. Together, these tools can enable researchers to deploy studies of human-AI interaction, facilitating inquiry into core questions of psychology, cognition, and decision making and their relationship to human-AI interaction. Both tools are open source and available to the broader research community. Documentation and source code is available at {cogrid, multi-user-gymnasium}.readthedocs.io. This paper details the functionality of these tools and presents several case studies to illustrate their utility in human-AI multi-agent experimentation.
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