EURO 2024 Copenhagen
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4369. Dynamic Condition Response Graphs as Explainable AI in Business Processes

Invited abstract in session MC-27: XAI in Business Processes, stream Mathematical Optimization for XAI.

Monday, 12:30-14:00
Room: 047 (building: 208)

Authors (first author is the speaker)

1. Thomas Troels Hildebrandt
Computer Science Departement, University of Copenhagen

Abstract

We present the uses of Dynamic Condition Response (DCR) Graphs as Explainable AI in Business Process Management. DCR Graphs is a declarative process modelling notation that can be used by domain experts to model, simulate and support workflows and business processes in a flexible and maintainable way. The first version of the DCR notation was published in 2010 in a PhD project of Mukkamala at IT University of Copenhagen, as part of the Trustworthy pervasive healthcare services project lead by Hildebrandt. The notation was further extended and accompanied by the first graphical editor as part of an industrial PhD project by Slaats (2015), at the danish company Exformatics and IT University of Copenhagen. The development was significantly advanced during the EcoKnow.org research project (2017-2021) lead by Hildebrandt, leading to major additions to the language, such as sub processes, decision modelling and data, and the development of tools for transformation of natural language textual regulations and requirements to formal models process models, lead by López (2018), award winning algorithms for process mining (lead by Back and Slaats), and the creation of the company DCR Solutions (DCRSolutions.net), offering industrial strength design, simulation and execution tools. Recently, the tool chain has been extended in the PhD project of Cosma (2024) with tools for mining hierarchical and timed DCR Graphs and for transforming DCR Graphs to Petri Nets.

Keywords

Status: accepted

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