Collaborative multi-agent Q-learning-empowered vocational education resource matching system

Key Points

• The aim is to develop a multi-agent system that utilizes Q-learning for effective resource matching in vocational education.
• Developed a framework employing multi-agent Q-learning algorithms.
• Implemented a resource matching system for vocational education contexts.
• Evaluated the system's performance through simulations and real-world scenarios.
• Demonstrated improved efficiency in matching educational resources.
• Achieved higher user satisfaction rates in resource allocation.
• Reduced resource identification time significantly in vocational settings.

Abstract