Daniel Gnad

Assistant Professor

About Me

I am assistant professor at Linköping University. My research interests are in the fields of artificial intelligence planning and model checking. More concretely, I am working on state space search methods such as decoupled state space search and have some experience in developing domain-independent heuristics such as red-black heuristics. More recently, I got interested in the grounding process that most planning systems perform as preprocessing. Together with my co-authors, I work on partial grounding methods that try to tackle the exponential blow-up that can occur during grounding by leveraging machine learning techniques.

Short bio

I did my studies in Computer Science at Saarland University. After finishing my MSc. degree, I stayed on as a PhD student in the group of Prof. Jörg Hoffmann. In 2022, I joined the Machine Reasoning Lab at Linköping University as a postdoctoral researcher, where I became assistant professor in 2023.

Awards

Winner of the International Planning Competition 2023 Learning Track for the system GOFAI with Álvaro Torralba at ICAPS 2023 in Prague.
Winner, Deterministic Optimal Track for the Ragnarok planner with Dominik Drexler, Paul Höft, Jendrik Seipp, David Speck, and Simon Ståhlberg at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
Winner, Deterministic Agile Track for the DecStar-2023 planner with Álvaro Torralba and Alexander Shleyfman at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
Dr.-Eduard-Martin-Preis for the best dissertation of the Faculty for Mathematics and Computer Science in 2021 awarded by Saarland University.
SoCS 2022 Best Paper Award for the paper Additive Pattern Databases for Decoupled Search with Silvan Sievers and Álvaro Torralba at the 15th Annual Symposium on Combinatorial Search (SoCS 2022).
ICAPS 2022 Best Dissertation Award for the doctoral thesis Star-Topology Decoupled State-Space Search in AI Planning and Model Checking at the 32th International Conference on Automated Planning and Scheduling (ICAPS 2022).
Nominated for the Dissertation Award 2021 of the German Society for Computer Science (GI). This is a national award (joint with Switzerland and Austria) for the best dissertation in the field of Computer Science. Nominated by Saarland University.
Runner-Up, Deterministic Sequential Agile Track for the planning system Saarplan with Maximilian Fickert, Patrick Speicher, and Jörg Hoffmann at the 9th International Planning Competition (IPC 2018) at ICAPS 2018.
Runner-Up, Deterministic Sequential Bounded-Cost Track for the planning system Saarplan with Maximilian Fickert, Patrick Speicher, and Jörg Hoffmann at the 9th International Planning Competition (IPC 2018) at ICAPS 2018.
Special Recognition for the planning system Saarplan for solving the highest number of problems of all planners in both the Agile and the Satisficing track with Maximilian Fickert, Patrick Speicher, and Jörg Hoffmann at the 9th International Planning Competition (IPC 2018) at ICAPS 2018.
SPIN 2018 Best Paper Award for the paper Star-Topology Decoupling in SPIN with Patrick Dubbert, Alberto Lluch-Lafuente, and Jörg Hoffmann at the 25th International Symposium on Model Checking of Software (SPIN 2018).

Publications

2024

David Speck and Daniel Gnad.
Decoupled Search for the Masses: A Novel Task Transformation for Classical Planning.
In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024). 2024.
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2023

Dominik Drexler, Daniel Gnad, Paul Höft, Jendrik Seipp, David Speck and Simon Ståhlberg.
Ragnarok.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
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Maximilian Fickert and Daniel Gnad.
DiSCO: Decoupled Search + COnjunctions.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
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Daniel Gnad, Silvan Sievers and Álvaro Torralba.
DecAbStar.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
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Daniel Gnad, Álvaro Torralba and Alexander Shleyfman.
DecStar-2023.
In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
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David Speck, Paul Höft, Daniel Gnad and Jendrik Seipp.
Finding Matrix Multiplication Algorithms with Classical Planning — Extended Abstract.
In The 35th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS). 2023.
paper code citation (Superseded by the ICAPS 2023 paper with the same name.)
Daniel Gnad, Malte Helmert, Peter Jonsson and Alexander Shleyfman.
Planning over Integers: Compilations and Undecidability.
In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS 2023), pp. 148–152. 2023.
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Daniel Gnad, Silvan Sievers and Álvaro Torralba.
Efficient Evaluation of Large Abstractions for Decoupled Search: Merge-and-Shrink and Symbolic Pattern Databases.
In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS 2023), pp. 138–147. 2023.
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David Speck, Paul Höft, Daniel Gnad and Jendrik Seipp.
Finding Matrix Multiplication Algorithms with Classical Planning.
In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS 2023), pp. 411–416. 2023.
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Alexander Shleyfman, Daniel Gnad and Peter Jonsson.
Structurally Restricted Fragments of Numeric Planning – A Complexity Analysis.
In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), pp. 12112–12119. 2023.
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2022

Silvan Sievers, Daniel Gnad and Álvaro Torralba.
Additive Pattern Databases for Decoupled Search.
In Proceedings of the 15th Annual Symposium on Combinatorial Search (SoCS 2022), pp. 180–189. 2022.
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Daniel Gnad, Álvaro Torralba and Daniel Fišer.
Beyond Stars - Generalized Topologies for Decoupled Search.
In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 110–118. 2022.
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2021

Daniel Gnad.
Star-Topology Decoupled State-Space Search in AI Planning and Model Checking.
PhD thesis, Saarland University, 2021.
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Daniel Fišer, Daniel Gnad, Michael Katz and Jörg Hoffmann.
Custom-Design of FDR Encodings: The Case of Red-Black Planning.
In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), pp. 4054–4061. 2021.
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Daniel Gnad, Jan Eisenhut, Alberto Lluch Lafuente and Jörg Hoffmann.
Model Checking omega-Regular Properties with Decoupled Search.
In Computer Aided Verification - 33rd International Conference, CAV 2021, Virtual Event, July 20-23, 2021, Proceedings, Part II, pp. 411–434. 2021.
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Daniel Gnad.
Revisiting Dominance Pruning in Decoupled Search.
In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), pp. 11809–11817. 2021.
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2020

Jörg Hoffmann, Malte Helmert, Daniel Gnad and Florian Pommerening.
Planen.
Book chapter in Handbuch der Künstlichen Intelligenz, pp. 395–428. 2020.
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2019

Daniel Gnad, Jörg Hoffmann and Martin Wehrle.
Strong Stubborn Set Pruning for Star-Topology Decoupled State Space Search.
Journal of Artificial Intelligence Research 65, pp. 343–392. 2019.
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Daniel Gnad and Jörg Hoffmann.
On the Relation between Star-Topology Decoupling and Petri Net Unfolding.
In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling (ICAPS 2019), pp. 172–180. 2019.
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Frederik Schmitt, Daniel Gnad and Jörg Hoffmann.
Advanced Factoring Strategies for Decoupled Search Using Linear Programming.
In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling (ICAPS 2019), pp. 377–381. 2019.
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Daniel Gnad, Álvaro Torralba, Martin Domínguez, Carlos Areces and Facundo Bustos.
IPALAMA - Planner Abstract.
In Sparkle Planning Challenge: Planner Abstracts. 2019.
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Daniel Gnad, Álvaro Torralba, Martín Ariel Domínguez, Carlos Areces and Facundo Bustos.
Learning How to Ground a Plan – Partial Grounding in Classical Planning.
In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 7602–7609. 2019.
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2018

Maximilian Fickert, Daniel Gnad and Jörg Hoffmann.
Unchaining the Power of Partial Delete Relaxation, Part II: Finding Plans with Red-Black State Space Search.
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 4750–4756. 2018.
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Daniel Gnad, Alexander Shleyfman and Jörg Hoffmann.
DecStar – STAR-topology DECoupled Search at its best.
In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 42–46. 2018.
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Maximilian Fickert, Daniel Gnad, Patrick Speicher and Jörg Hoffmann.
SaarPlan: Combining Saarland’s Greatest Planning Techniques.
In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 11–16. 2018.
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Daniel Gnad, Patrick Dubbert, Alberto Lluch-Lafuente and Jörg Hoffmann.
Star-Topology Decoupling in SPIN.
In Model Checking Software - 25th International Symposium, SPIN 2018, Malaga, Spain, June 20-22, 2018, Proceedings, pp. 103–114. 2018.
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Daniel Gnad and Jörg Hoffmann.
Star-Topology Decoupled State Space Search.
Artificial Intelligence 257, pp. 24–60. 2018.
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2017

Daniel Gnad, Valerie Poser and Jörg Hoffmann.
Beyond Forks: Finding and Ranking Star Factorings for Decoupled Search.
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 4310–4316. 2017.
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Daniel Gnad, Álvaro Torralba, Alexander Shleyfman and Jörg Hoffmann.
Symmetry Breaking in Star-Topology Decoupled Search.
In Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS 2017), pp. 125–134. 2017.
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Patrick Speicher, Marcel Steinmetz, Daniel Gnad, Jörg Hoffmann and Alfonso Gerevini.
Beyond Red-Black Planning: Limited-Memory State Variables.
In Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS 2017), pp. 269–273. 2017.
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Daniel Gnad, Álvaro Torralba and Jörg Hoffmann.
Symbolic Leaf Representation in Decoupled Search.
In Proceedings of the 10th Annual Symposium on Combinatorial Search (SoCS 2017). 2017.
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2016

Daniel Gnad, Martin Wehrle and Jörg Hoffmann.
Decoupled Strong Stubborn Sets.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 3110–3116. 2016.
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Álvaro Torralba, Daniel Gnad, Patrick Dubbert and Jörg Hoffmann.
On State-Dominance Criteria in Fork-Decoupled Search.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 3265–3271. 2016.
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Daniel Gnad, Marcel Steinmetz, Mathäus Jany, Jörg Hoffmann, Ivan Serina and Alfonso Gerevini.
Partial Delete Relaxation, Unchained: On Intractable Red-Black Planning and Its Applications.
In Proceedings of the Ninth Annual Symposium on Combinatorial Search (SoCS 2016). 2016.
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Daniel Gnad, Álvaro Torralba, Jörg Hoffmann and Martin Wehrle.
Decoupled Search for Proving Unsolvability.
In Unsolvability International Planning Competition: Planner Abstracts, pp. 16–18. 2016.
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Daniel Gnad, Marcel Steinmetz and Jörg Hoffmann.
Django: Unchaining the Power of Red-Black Planning.
In Unsolvability International Planning Competition: Planner Abstracts, pp. 19–22. 2016.
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2015

Daniel Gnad and Jörg Hoffmann.
Red-Black Planning: A New Tractability Analysis and Heuristic Function.
In Proceedings of the Eighth Annual Symposium on Combinatorial Search (SoCS 2015), pp. 44–52. 2015.
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Daniel Gnad, Jörg Hoffmann and Carmel Domshlak.
From Fork Decoupling to Star-Topology Decoupling.
In Proceedings of the Eighth Annual Symposium on Combinatorial Search (SoCS 2015), pp. 53–61. 2015.
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Daniel Gnad and Jörg Hoffmann.
Beating LM-Cut with hmax (Sometimes): Fork-Decoupled State Space Search.
In Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS 2015), pp. 88–96. 2015.
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