A Petri net model for reasoning in the presence of inconsistency

Murata, Tadao; Subrahmanian, V. S.; Wakayama, Toshiro

doi:10.1109/69.91059

Cited by 58 publications

(12 citation statements)

References 13 publications

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“…Semantically we allow functors in the arc labels as well as negation and binary expressions over terms to compare variable/constants: This is not allowed in their frameworks. In their paper [17] Tadao Murata, V.S. Subrahmanian and Toshiro Wakayama extend the basic Pr/T Net approach by applying paraconsistency to the nets, thus allowing negation.…”

Section: Related Workmentioning

confidence: 97%

Model checking multi-agent systems with logic based Petri nets

Behrens

Dix

2007

Ann Math Artif Intell

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We introduce a class of Petri nets, simple logic Petri nets (SLPN), that are based on logical expressions. We show how this type of nets can be efficiently mapped into logic programs with negation: the corresponding answer sets describe interleaved executions of the underlying nets (Theorem 1). The absence of an answer set indicates a deadlock situation. We also show how to correctly model and specify AgentSpeak agents and multi-agent systems with SLPN's (Theorem 2). Both theorems allow us to solve the task of model checking AgentSpeak multi-agent systems by computing answer sets of the obtained logic program with any ASP system.

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Section: Related Workmentioning

confidence: 97%

Model checking multi-agent systems with logic based Petri nets

Behrens

Dix

2007

Ann Math Artif Intell

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“…This has been accommodated by further extensions to Petri nets which capture and reflect fuzzy knowledge [10]. Generally, threshold values and certainty values are associated with rules which in turn are m~xtelled by the Petri net.…”

Section: Petri Nets Process Models and Fuzzy Logicmentioning

confidence: 99%

Software engineering process support based on fuzzy imploding Petri nets

Bechtold

1992

Proceedings of the 30th Annual Southeast Regional Conference on - ACM-SE 30

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Software engineering process management and control is increasingly recognized as critical to the timely engineering of quality products. Automated process support within an integrated environment provides otherwise unachievable levels of insight, coordination, control, and flexibility in governing the activities and resources that comprise the engineering process. Crucial to process flexibility and robustness is the ability of a process to both withstand and react to the impact of unexpected or uncontrollable events. Using Petri nets as a basis for process modelling, this paper proposes an extension to fuzzy Petri nets which meaningfully models the impact of and response to the chaotic events that typically disrupt any complex process. Concepts introduced include: transition release thresholds, transition recall thresholds, transition backfiring, token recalls, token maturity, and token chains. OVERVIEWVirtually all complex software engineering efforts require coordinating, scheduling, and managing highly interactive resources. Efficient and successful software engineering efforts are often based on the preplanned institution of one or more processes which serve to govern the activities and interactions of involved personnel and resources. There are. however, aspects of software engineering process support that are not characterized by the orderliness and precision needed by most automated information systems. When a large-scale engineering operation is subjected to an excessive number of unanticipated events, this can potentially exceed the ability of an automated environment to continue exerting overall control. Chaos develops and all too readily becomes self-perpetuating. Consequently, investigation into software process models in general and into the possibilities for providing automated or environment based support to the software engineering process must include investigations into maintaining process support under highly volatile or even hostile conditions. Furthermore, in addition to the need for process models and their environments to be dynamically flexible, it is also important for such models to be capable of handling the uncertainty and unpredictability inherent in attempting to anticipate the consequences of actually instantiating a given process. Although various static approaches exist for better understanding the uncertainty in software development, dynamically changing uncertainty within the software engineering process is an area still largely unaddressed.Fuzzy logic can be leveraged to make contributions specifically in this area--an area where computers are traditionally most inept. That is, fuzzy logic does not insist on absolute certainty, nor on total confidence, nor on complete information. From this perspective, there is considerable potential for the application of fuzzy logic principles in the robust support and enforcement of software engineering processes--particularly if there are reasonable expectations that such processes are at risk of disorganizing influences from either unpre...

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“…Thus, Petri nets and their modified models have also been used to study RBS [3]. Murata et al used Petri nets to model Horn clauses, and then studied consistency problems of rules [4]. Yang et al proposed a Petri net formalism for the verification of RBS based on incidence matrix operations [5].…”

Section: Introductionmentioning

confidence: 98%

Using Petri nets to verify acyclic rule-based system

Ding

Pan

Jiang

et al. 2008

Front. Electr. Electron. Eng. Ch

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A series of Petri net-based definitions were formulated for describing four types of structural errors in a rule-based system (RBS), including inconsistency, incompleteness, redundancy and circularity. A marked v-Petri net model of acyclic RBS was constructed. Then, its reachability tree was generated to record all reachable relations between propositions in RBS. Moreover, a backward reasoning forest of a reachable marking was generated for explicitly representing reachable paths in RBS. Finally, a set of theorems and algorithms were provided to analyze and check structural errors. The usability of the research results presented in this paper was illustrated by an example.

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A Petri net model for reasoning in the presence of inconsistency

Cited by 58 publications

References 13 publications

Model checking multi-agent systems with logic based Petri nets

Model checking multi-agent systems with logic based Petri nets

Software engineering process support based on fuzzy imploding Petri nets

Using Petri nets to verify acyclic rule-based system

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