Paper Info
Title
GAPN-LA: A framework for solving graph problems using Petri nets and learning automata.
Abstract
A fusion of learning automata and Petri nets, referred to as APN-LA, has been recently introduced in the literature for achieving adaptive Petri nets. A number of extensions to this adaptive Petri net have also been introduced; together we name them the APN-LA family. Members of this family can be utilized for solving problems in the domain of graph problems; each member is suitable for a specific category within this domain. In this paper, we aim at generalizing this family into a single framework, called generalized APN-LA (GAPN-LA), which can be considered as a framework for solving graph-based problems. This framework is an adaptive Petri net, organized into a graph structure. Each place or transition in the underlying Petri net is mapped into exactly one vertex of the graph, and each vertex of the graph represents a part of the underlying Petri net. A vertex in GAPN-LA can be considered as a module, which, in cooperation with other modules in the framework, helps in solving the problem at hand. To elaborate the problem-solving capability of the GAPN-LA, several graph-based problems have been solved in this paper using the proposed framework.
Year
DOI
Venue
2019
10.1016/j.engappai.2018.10.013
Engineering Applications of Artificial Intelligence
Keywords
Field
DocType
Adaptive Petri net,Learning automata,Modular algorithms,Graph-based problems
Graph,Mathematical optimization,Learning automata,Petri net,Vertex (geometry),Generalization,Computer science,Theoretical computer science
Journal
Volume
ISSN
Citations 
77
0952-1976
2
PageRank 
References 
Authors
0.36
31
4
Name
Order
Citations
PageRank
S. Mehdi Vahidipour1392.89
Mehdi Esnaashari213110.37
Alireza Rezvanian319813.35
Mohammad Reza Meybodi4166496.57