Dr. Martin Wehrle
I have left the Artificial Intelligence research group.
ResearchMy research is focused on the areas of automated planning and model checking. In particular, I am interested in the analysis, the design, and the application of (heuristic) search methods and state space pruning techniques for solving planning and model checking problems. Although such problems can occur in various shapes, they can be similar when considered from an abstract point of view. I am specifically interested in gaining a better understanding of their relationships, and based on this, in designing specialized problem solving algorithms.
- Most of my publications are available online.
- See also DBLP.
- Mcta: A directed model checking tool for timed systems. Mcta applies heuristic search techniques with automatically generated distance heuristics to find short error traces in concurrent systems of timed automata. For more information, see the Mcta website.
- SoCS 2016 Best Paper Award for the paper Sleep Sets Meet Duplicate Elimination (PDF) with Yusra Alkhazraji at the 9th Annual Symposium on Combinatorial Search (SoCS 2016).
- Winner, Unsolvability IPC 2016 for the planning system Fast Downward Aidos (PDF) with Jendrik Seipp, Florian Pommerening, Silvan Sievers, Chris Fawcett and Yusra Alkhazraji at the 1st Unsolvability International Planning Competition (UIPC 2016) at ICAPS 2016.
- AAAI 2014 Outstanding Paper Award Honorable Mention for the paper Generalized Label Reduction for Merge-and-Shrink Heuristics (PDF) with Silvan Sievers and Malte Helmert at the 28th AAAI Conference on Artificial Intelligence (AAAI 2014).
- ICAPS 2013 Best Paper Award for the paper The Relative Pruning Power of Strong Stubborn Sets and Expansion Core (PDF) with Malte Helmert, Yusra Alkhazraji and Robert Mattmüller at the 23rd International Conference on Automated Planning and Scheduling (ICAPS 2013).
- AI 2007 Best Paper Award for the paper Planning as Satisfiability with Relaxed E-Step Plans (PDF) with Jussi Rintanen at the 20th Australian Joint Conference on Artificial Intelligence (AI 2007).