一种基于群体信念协商的矛盾知识处理模型

A Model of Processing Inconsistency Knowledge Based on Social Belief Negotiation

一个智能体从周围环境中接收到多种知识,如何将这些知识合并成单一的、一致的知识是一个非常重要的问题,从信念修正中"缩并+添加"得到启发,我们分两步解决这个问题。第一步弱化接收到的多种信息,使之一致,第二步进行简单的合并操作。本文主要研究了第一步,称为基于群体信念协商的矛盾知识处理模型,本文讨论了该模型的公理系统和该模型的过程实现,通过一个例子示范了这种模型下信息合并操作的具体实现过程。

An intelligent agent may receive information about its environment from several different sources. How should the agent merge these items of information into a single, consistent piece？ Taking our lead from the contraction ＋ expansion approach to belief revision. We envisage a two-stage approach to this problem. The first stage consists of weakening the individual pieces of information into a form in which they can be consistently added together. The second stage then consists of simply adding together the information thus obtained. This paper is devoted mainly to the first stage of this process, which we call social contraction model. We consider both a postulational and a procedural approach to social contraction. We also provide a possible instantiations of this model.