ESPNET: expert-system-based simulator of Petri nets

1988 ◽  
Vol 135 (4) ◽  
pp. 239 ◽  
Author(s):  
J. Duggan ◽  
J. Browne
Keyword(s):  
2008 ◽  
Vol 07 (01) ◽  
pp. 37-46 ◽  
Author(s):  
Madjid Tavana

Expert systems (ESs) are complex information systems that are expensive to build and difficult to validate. Numerous knowledge representation strategies such as rules, semantic networks, frames, objects and logical expressions are developed to provide high-level abstraction of a system. Rules are the most commonly used form of knowledge representation and they are derived from popular techniques such as decision trees and decision tables. Despite their huge popularity, decision trees and decision tables are static and cannot model the dynamic requirements of a system. In this study, we propose Petri Nets (PNs) for dynamic system representation and rule derivation. PNs with their graphical and precise nature and their firm mathematical foundation are especially useful for building ESs that exhibit a variety of situations, including: sequential execution, conflict, concurrency, synchronisation, merging, confusion, or prioritisation. We demonstrate the application of our methodology in the design and development of a medical diagnostic expert system.


Author(s):  
Xun Xu

While computers have proven to be instrumental in the advancement of product design and manufacturing processes, the role that various technologies have played over the years can never be over-estimated. Because of the intimate involvement of computers in the product development chain, technologies that have severed as enablers are in many cases all software- oriented. There are a number of issues that a technology needs to address in better support of CAD, CAPP, CAM, CNC, PDM, PLM, and so forth. Knowledge acquisition and utilization is one of the top priorities and very often the first step of actions. Intelligent reasoning and optimization is another important task. More often than not, the optimization problems have multi-objectives and multi-constraints that are highly non-linear, discrete, and sometimes fuzzy. Among the technologies that have been developed in the recent past are knowledgebased (expert) system, artificial neural network (ANN), genetic algorithm (GA), agent-based technology, fuzzy logic, Petri Nets, and ant colony optimisation. An expert system is a computer system which includes a well-organized body of knowledge in a bounded domain, and is able to simulate the problem solving skill of a human expert in a particular field. Neural networks are the techniques that can work by simulating the human neuron function, and using the weights distributed among their neurons to perform implicit inference. The genetic algorithms mimic the process of natural evolution by combining the survival of the fittest among solution structures with a structured, yet randomized, information exchange. Agent-based technology utilizes agents as intelligent entities capable of independently regulating, reasoning and decision-making to carry out actions and to achieve a specific goal or a set of goals. This chapter discusses these four technologies together with some applications of these technologies. Also briefly mentioned are the fuzzy logic, Petri Nets, and ant colony optimization methods. The objective is not to give a detailed account for each of these technologies. Instead, the intention is to introduce the technologies that are relevant to and suitable for applications such as CAD, CAPP, CAM, CNC, PDM, and PLM, as well as their integrations. This chapter can also be considered as a focal place for those who are interested in the technologies to further explore, as a collection of over 130 research publications have been cited and are all listed in the reference list at the back.


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