A deductive system for proving workflow models from operational procedures
Data(s) |
01/05/2012
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Resumo |
Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several differ- ent approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational struc- tures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments. |
Formato |
application/pdf |
Identificador | |
Publicador |
Elsevier |
Relação |
http://eprints.qut.edu.au/48181/1/FGCS_RasmussenBrown2011.pdf DOI:10.1016/j.future.2012.01.001 Rasmussen, Rune K. & Brown, Ross A. (2012) A deductive system for proving workflow models from operational procedures. Future Generation Computer Systems, 28(5), pp. 732-742. |
Direitos |
Copyright 2012 Elsevier B.V. |
Fonte |
Faculty of Science and Technology; Information Systems |
Palavras-Chave | #080101 Adaptive Agents and Intelligent Robotics #080110 Simulation and Modelling #080111 Virtual Reality and Related Simulation #080699 Information Systems not elsewhere classified #Workflow #Planning #Petri-net #Automation #Management #Modelling |
Tipo |
Journal Article |