Conference Paper

Automated Planning for Supporting Knowledge-Intensive Processes

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Authors Sheila Katherine Venero Bradley Schmerl Leonardo Montecchi Julio Cesar dos Reis Cecilia Mary Fischer Rubira
Abstract
Knowledge-intensive processes (KiPs) are processes characterized by high levels of unpredictability and dynamism. Their process structure may not be known before their execution. One way to cope with this uncertainty is to defer decisions regarding the process structure until run time. In this paper, we consider the definition of the process structure as a planning problem. Our approach uses automated planning techniques to generate plans that define process models according to the current context. The generated plan model relies on a metamodel called METAKIP that represents the basic elements of KiPs. Our solution explores Markov Decision Processes (MDP) to generate plan models. This technique allows uncertainty representation by defining state transition probabilities, which gives us more flexibility than traditional approaches. We construct an MDP model and solve it with the help of the PRISM model-checker. The solution is evaluated by means of a proof of concept in the medical domain and reveals the feasibility of our approach.
DOI https://doi.org/10.1007/978-3-030-49418-6_7
Event 21st International Conference on Business Process Modeling, Development and Support (BPMDS 2020)
Venue Grenoble, France
Date June 8-9, 2020
Pages 101-116
Publisher Springer, Cham
Series LNBIP
Volume 387
ISBN PRINT: 978-3-030-49417-9
ELECTRONIC: 978-3-030-49418-6
Citation
Bibtex
@inproceedings{2020BPMDS,
  author = {Venero, Sheila Katherine and Schmerl, Bradley and Montecchi, Leonardo and dos Reis, Julio Cesar and Fischer Rubira, Cecilia Mary},
  title = {{Automated Planning for Supporting Knowledge-Intensive Processes}},
  booktitle = {21st International Conference on Business Process Modeling, Development and Support (BPMDS 2020)},
  address = {Grenoble, France},
  date = {2020-06-08/2020-06-09},
  pages = {101-116},
  year = {2020}
}

Plain Text
S. Venero, B. Schmerl, L. Montecchi, J. dos Reis, C. Rubira. Automated Planning for Supporting Knowledge-Intensive Processes. In: 21st International Conference on Business Process Modeling, Development and Support (BPMDS 2020), pp. 101-116. Grenoble, France, June 8-9, 2020.
 
 

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