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Stigmergic agent-based adaptive content sequencing in an e-learning environment

机译:电子学习环境中基于Stigmergic Agent的自适应内容排序

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Stigmergic agents (SA) gather their strength from the ant colony metaphor and multi-agent systems (MAS). Ant-based systems provide a means of picking up information through indirect communication by exhibiting stigmergic ant behaviour and MAS lends the benefits of direct interaction among the agents. This paper presents a stigmergic agent framework for adaptive content sequencing (ACS) in e-learning using SA (ACSeLSA). Each learner enrolled in the designed e-course has a personalised stigmergic agent (PSA) that employs an ant-based adaptive content sequencing algorithm, ACSeLAnt, to generate customised content sequence for him/her. By implementing ACSeLAnt, each PSA: 1) exhibits stigmergic behaviour of producing its own pheromone trails and sensing those of other learners to generate the content sequence; 2) elicits recommendations of other similar learners through direct communication with their PSAs and incorporates them into the content sequencing process. The merger is beneficial for knowledge sharing in e-learning systems where there is a dearth of active dialogue among learners.
机译:Stigmergic代理(SA)从蚁群隐喻和多代理系统(MAS)中获得优势。基于蚂蚁的系统提供了一种通过表现出侮辱性的蚂蚁行为而通过间接通信来获取信息的方法,而MAS带来了代理之间直接交互的好处。本文提出了一种用于使用SA(ACSeLSA)进行电子学习的自适应内容排序(ACS)的双能代理框架。参加设计的电子课程的每个学习者都有一个个性化的Stigmergic代理(PSA),该代理使用基于蚂蚁的自适应内容排序算法ACSeLAnt为他/她生成定制的内容序列。通过实施ACSeLAnt,每个PSA:1)表现出耻辱行为,产生自己的信息素轨迹并感知其他学习者的信息素轨迹以生成内容序列; 2)通过与他们的PSA直接沟通,得出其他类似学习者的建议,并将其纳入内容排序过程。合并有利于在缺乏学习者之间积极对话的电子学习系统中共享知识。

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