基于知识Petri网和归结规则的推理方法

本文提出了一种基于知识Petri网和归结规则的推理方法.通过知识Petri网描述命题逻辑知识库,将归结规则映射到知识Petri网上,根据库所和变迁的连接关系,定义了知识Petri网中的归结结构.利用归结结构,给出了基于知识Petri网的归结推理算法和扩展知识库的推理算法,并利用Wumpus实例验证了推理算法.该推理方法是可靠且完备的,能够利用知识Petri网的网络结构降低计算复杂性.

Reasoning method based on knowledge Petri nets and resolution rules

In this paper, a reasoning method based on knowledge Petri nets and resolution rules is proposed. First, a knowledge base in the form of propositional logic is described as a knowledge Petri net. Second, a resolution structure is defined in a knowledge Petri net according to the input and output relationship of places and transitions. Third, a reasoning algorithm is presented to perform resolution operations by resolution structures. Further, a reasoning algorithm is given for an extended knowledge base. Finally, the Wumpus world problem is taken as an example to illustrate and verify the reasoning algorithm. It is proved that the reasoning method is sound and complete. The computational complexity involved in reasoning processes can be reduced by utilizing network structures of a knowledge Petri net.