Inference Approach Based on Petri Nets
Document Type
Article
Publication Date
2-8-2021
Abstract
An inference approach is proposed by formulating reasoning processes as particular evolutions of Petri nets. It can be used to design an intelligent agent that executes tasks in a given environment. First, a symbol Petri net is defined to represent a Boolean variable describing a distinct aspect of an environment. Second, a propositional logic sentence in a conjunctive normal form, which may express some background knowledge or a sequence of percepts made by an agent, is formulated as a linear constraint, called as a semantic constraint. Third, an algorithm is constructed to design monitor places enforcing semantic constraints on symbol Petri nets, and its resultant net is called a knowledge Petri net representing relevant knowledge. Fourth, a reasoning algorithm is presented based on a newly defined transition-firing rule of the knowledge Petri net, and can be used to infer or reveal hidden facts. The proposed inference algorithm is efficient since its time computational complexity is proven to be polynomial with respect to the number of Boolean variables. The wumpus world problem is taken as an example to illustrate and verify it.
Identifier
85092223572 (Scopus)
Publication Title
Information Sciences
External Full Text Location
https://doi.org/10.1016/j.ins.2020.09.023
ISSN
00200255
First Page
1008
Last Page
1024
Volume
547
Grant
2018H0022
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Luo, Ji Liang; Tan, Kai Cheng; Luo, Huai Ju; and Zhou, Meng Chu, "Inference Approach Based on Petri Nets" (2021). Faculty Publications. 4327.
https://digitalcommons.njit.edu/fac_pubs/4327