Investigating the applicability of Petri nets for rule-based system verification

Nazareth, Derek L.

doi:10.1109/69.224193

Cited by 76 publications

(31 citation statements)

References 25 publications

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“…in the domain-independent structural characteristics of the rules actually stored in the rule-base [3]. Since a rule-base cannot be tested, even on simple cases, until much of it is encoded, most researchers [4][5][6][7][8], contend that the ability to verify content, during rule-base construction, would be an invaluable aid in ensuring that it is free from the problems of consistency 1 , completeness 2 , conciseness 3 that usually remain dormant until performance errors occur. In fact the ability to content verify rule-bases, as Nazareth [7] argues, would enhance the viability of rule-based system technology itself.…”

Section: Introductionmentioning

confidence: 99%

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Rule-base content verification using a digraph-based modelling approach

Gursaran

Kanungo

Sinha

1999

Artificial Intelligence in Engineering

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Section: Introductionmentioning

confidence: 99%

“…The method does not assume any control strategy on the part of the rule-based system. Nazareth [7] shows how to model a rule-base, used with forward chaining, with petri-nets. Rigorous proofs certifying content verification capabilities have been presented by him.…”

Section: Introductionmentioning

confidence: 99%

Rule-base content verification using a digraph-based modelling approach

Gursaran

Kanungo

Sinha

1999

Artificial Intelligence in Engineering

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“…On the other hand, many different procedures for verifying rule based expert systems are proposed, covering a broad range of methods [8,10,23,24,[27][28][29]41]. Unfortunately, the underlying semantics of the rules is not uniform: some systems interpret rules purely declarative as logical implications [25,28], whereas in other systems rules have an operational semantics, in which facts are added or removed from a pool of working knowledge (state space model) [8,14,27].…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand their simplicity and level of abstraction facilitates formal verification. There is, however, no generally accepted formalism for the verification of rule-based systems, so many different techniques have been proposed [1,23,25,28], and the verification of real-world industrial applications is still rare.…”

Section: Introductionmentioning

confidence: 99%

Detection of dynamic execution errors in IBM system automation's rule-based expert system

Sinz

Lumpp

Schneider

et al. 2002

Information and Software Technology

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We formally verify aspects of the rule-based expert system of IBM's System Automation software for IBM's zSeries mainframes. Starting with a formalization of the expert system in Propositional Dynamic Logic (PDL), we encode termination and determinism properties in PDL and its extension ¥ PDL. We then translate our decision problems to propositional logic and apply advanced SAT techniques for automated proofs. In order to locate real program bugs for each failed proof attempt, we apply extra formalization steps and represent propositional error formulae in concise normal form as Binary Decision Diagrams (BDDs). In our experiments, we revealed residual non-termination bugs in a tested program version close to shipment, and, after correcting them, we formally verified the absence of this class of bugs in the production code.

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“…It is noted that there are very few other approaches based on Petri net theory in literature to model or verify expert systems. The typical ones might be [1,13,14,16,18,24]. However, none of these approaches use the sort of Coloured Petri Nets [10,11] that are used in our approach to resolve some verification issues and problems as highlighted in [20,21].…”

Section: Introductionmentioning

confidence: 99%

Formal verification of the correctness in hybrid expert systems

Shiu

Liu

Yeung

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97

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It has been increasingly recognized over recent years that expert systems which combine one or more techniques greatly increase the problem solving capability and help overcome some of the shortcomings associated with any single technique. The verification of these expert systems requires methods which could tackle the multiple knowledge representation paradigms and integrated inference mechanisms used. This paper provides a formal description technique for verifying the correctness of Hybrid Expert Systems (HES) that emphasizes an integration of object hierarchy, property inheritance and production rules. The main idea is to convert the HES into a State Controlled Coloured Petri Net (SCCPN) where the object hierarchy, property inheritance and production rules are modelled as separated components in the same SCCPN. The detection and analysis of the anomalies in the system are done by constructing and examining the reachability tree spanned by the knowledge inference. This provides a formal basis for automating the deduction process and a means of verifying HES. A set of propositions is formulated to verify errors and anomalies in HES. Lastly, future extension of our approach is discussed.

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Investigating the applicability of Petri nets for rule-based system verification

Cited by 76 publications

References 25 publications

Rule-base content verification using a digraph-based modelling approach

Rule-base content verification using a digraph-based modelling approach

Detection of dynamic execution errors in IBM system automation's rule-based expert system

Formal verification of the correctness in hybrid expert systems

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