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A belief revision method based on argumentative dialogue model

机译:基于论证对话模型的信念修正方法

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Belief is Agents' cognition of surrounding. Due to the dynamics of the environment, the new received belief may be conflicted with the original belief set when an agent got new information. Belief revision is to make sure the new belief set is a conflict-free set in this moment. This paper proposes a combined with debate way of belief revision, which use certainty-factor based argumentative framework to represent the uncertainty of knowledge and uncertainty reasoning, to get a belief set with the corresponding certainty factor. Finally the result belief set will be received by a setting certainty-factor threshold value. Proved by the experiment, the new accepted belief may not be included in the revised credible belief set, and credible belief set is conflict-free. Belief revision algorithm, therefore, have broken the traditional way of belief revision, and effectiveness.
机译:信念是特工对周围环境的认知。由于环境的动态变化,当代理商获取新信息时,新接收到的信念可能会与原始信念集合发生冲突。信念修订是为了确保新的信念集合在此刻是无冲突的集合。本文提出了一种结合信念修正的辩论方式,即采用基于确定性因子的论证框架来表示知识的不确定性和不确定性推理,从而得到具有相应确定性因子的信念集合。最后,将通过设置确定性因子阈值接收结果置信集。实验证明,新的接受的信念可能不会包含在修订的可信信念集中,并且可信信念集是无冲突的。因此,信仰修订算法打破了传统的信仰修订方式和有效性。

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