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A Collaborative Learning System based on Multi-agent

机译:基于多代理的协作学习系统

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摘要

A multi-agent learning system model is presented to solve the problems existing in the present remote learning system, such as the monotonous pattern and passive educating. Integrated with intelligent agent technology, the multi-agent learning system gives an agent capability description language, on the basis of which we suggest relevant personal grouping strategy and learning task allocation strategy. Furthermore, it uses compensates mechanism to encourage the agent cooperation, state-space-search theory to enable the MAS system to have the stronger problem solving ability, both of which can meet demand of active learning for the learners and to some extent economize communication of system and save the communication in the system in certain degree.
机译:提出了一种多代理学习系统模型,以解决当前远程学习系统中存在的问题,例如单调模式和被动教育。与智能代理技术集成,多代理学习系统提供代理能力描述语言,基于我们建议相关的个人分组策略和学习任务分配策略。此外,它使用补偿机制来鼓励代理商合作,国家空间搜索理论使MAS系统能够具有更强的问题解决能力,这两者都可以满足学习者的积极学习的需求,以及某种程度的节约沟通系统并在某种程度上保存系统中的通信。

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