本文围绕高校图书馆未来学习中心的知识服务创新需求，结合多智能体系统技术，开展面向读者学科自主学习的知识服务仿真研究。通过分析读者学习需求、设计多智能体协同服务路径，构建包含学习路径设计、资源推荐、智能答疑与评估反馈等功能的多智能体服务团队，并以“经济史”学科为例进行仿真验证。结果表明，多智能体系统虚拟成员能够有效整合和节约图书馆现有资源，显著提升知识服务的自动化水平与个性化支持能力，为资源有限的高校图书馆提供了一条易操作、可复制的智慧服务路径，对未来学习中心的建设与实践具有参考价值。

This study employs Multi-Agent System technology to simulate knowledge services that support subject based self-directed learning in university library Future Learning Centers. By analyzing learner needs and designing collaborative agent pathways, a multi-agent service framework is constructed with functions including learning path design, resource recommendation, intelligent Q&A, and feedback evaluation. A simulation focusing on the "Economic History" discipline demonstrates that the system effectively integrates library resources, improves service automation, and enhances personalized support. The approach offers a practical and replicable solution for libraries with limited resources, providing insights for the development of Future Learning Centers.