Planning is concerned with the automated solution of action sequencing problems described in declarative languages giving the action preconditions and e ects. One important application area for such technology is the creation of new processes in Business Process Management (BPM), which is essential in an ever more dynamic business environment. A major obstacle for the application of Planning in this area lies in the modeling. Obtaining a suitable model to plan with { ideally a description in PDDL, the most commonly used planning language { is often prohibitively complicated and/or costly. Our core observation in this work is that this problem can be ameliorated by leveraging synergies with model-based software development. Our application at SAP, one of the leading vendors of enterprise software, demonstrates that even one-to-one model re-use is possible. The model in question is called Status and Action Management (SAM). It describes the behavior of Business Objects (BO), i.e., large-scale data structures, at a level of abstraction corresponding to the language of business experts. SAM covers more than 400 kinds of BOs, each of which is described in terms of a set of status variables and how their values are required for, and a ected by, processing steps (actions) that are atomic from a business perspective. SAM was developed by SAP as part of a major model-based software engineering e ort. We show herein that one can use this same model for planning, thus obtaining a BPM planning application that incurs no modeling overhead at all. We compile SAM into a variant of PDDL, and adapt an o -the-shelf planner to solve this kind of problem. Thanks to the resulting technology, business experts may create new processes simply by specifying the desired behavior in terms of status variable value changes: e ectively, by describing the process in their own language. © 2012 AI Access Foundation. All rights reserved.
CITATION STYLE
Hoffmann, J., Weber, I., & Kraft, F. M. (2012). SAP speaks PDDL: Exploiting a software-engineering model for planning in business process management. Journal of Artificial Intelligence Research, 44, 587–632. https://doi.org/10.1613/jair.3636
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