AAAI Publications, Thirty-First AAAI Conference on Artificial Intelligence

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On the Disruptive Effectiveness of Automated Planning for LTLf-Based Trace Alignment
Giuseppe De Giacomo, Fabrizio Maria Maggi, Andrea Marrella, Fabio Patrizi

Last modified: 2017-02-12

Abstract


One major task in business process management is that of aligning real process execution traces to a process model by (minimally) introducing and eliminating steps. Here, we look at declarative process specifications expressed in Linear Temporal Logic on finite traces (LTLf). We provide a sound and complete technique to synthesize the alignment instructions relying on finite automata theoretic manipulations. Such a technique can be effectively implemented by using planning technology. Notably, the resulting planning-based alignment system significantly outperforms all current state-of-the-art ad-hoc alignment systems. We report an in-depth experimental study that supports this claim.

Keywords


Business Processes; Trace Alignment; Linear Time Temporal Logic on Finite Traces; Automated Planning; Declare

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