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Research of Knowledge expression model for Non-monotonic reasoning based on Uncertain inference

机译:基于不确定推理的非单调推理知识表达模型研究

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Aiming to the application of Non-monotonic reasoning based on uncertain inference to plan recognition,a new way of knowledge expression model is proposed in mean of extending credibility of TMS node and building evidence transfer mechanism,which ensures the system to inference forward and build hypothesis under the case of the node state is noncommittal. The gene of node reliability and influence degree is introduced to overcome the shortage of only one value of credibility at one time and implement uncertain inference. Theoretical analysis and experimental results demonstrate that our method could describe clearly the process of non-monotonic reasoning based on uncertain inference,so it is expectable for our method to play a useful role in plan recognition system.
机译:针对基于不确定推理的非单调推理在计划识别中的应用,提出了一种新的知识表达模型,旨在扩展TMS节点的可信度,建立证据传递机制,以保证系统推理和建立假设。在节点状态下的状态为非承诺状态。引入节点可靠性和影响度的基因,可以一次克服一个可信度值的不足,实现不确定的推理。理论分析和实验结果表明,该方法可以基于不确定的推理清晰地描述非单调推理的过程,因此有望在计划识别系统中发挥重要作用。

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