Daniel Gnad

Daniel Gnad (he/him)

Assistant Professor

About Me

I am assistant professor at Linköping University and lecturer at Heidelberg University. My research interests are in the fields of artificial intelligence planning and model checking. More concretely, I am working on techniques that exploit the problem structure to find solutions more effectively. Methods I developed include compact state space representations like decoupled search and novel domain-independent heuristics for classical and numeric planning. Further more, I am interested in the computational complexity of planning formalisms, the grounding process that most planning systems perform as preprocessing, and in general combinations of symbolic planning algorithms and machine learning. Recently, I started looking into Explainable AI Planning, in particular in employing symbolic reasoning methods like SAT or ASP to analyze the solution space of planning problems.

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. In June 2025 I obtained my docent qualification (Swedish Habilitation) at Linköping University. Since May 2025 I am lecturer in Heidelberg and part-time in Linköping.

Awards

  • Winner of the Explainability Challenge of the Beluga Competition organized by the TUPLES Consortium.
  • ICAPS 2024 Best Paper Award for the paper Decoupled Search for the Masses: A Novel Task Transformation for Classical Planning at the 34th International Conference on Automated Planning and Scheduling (ICAPS 2024).
  • Winner of the International Planning Competition 2023 Learning Track for the system GOFAI at ICAPS 2023 in Prague.
  • Winner, Deterministic Optimal Track for the Ragnarok planner at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
  • Winner, Deterministic Agile Track for the DecStar-2023 planner 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 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 32nd 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 at the 9th International Planning Competition (IPC 2018) at ICAPS 2018.
  • Runner-Up, Deterministic Sequential Bounded-Cost Track for the planning system Saarplan 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 at the 9th International Planning Competition (IPC 2018) at ICAPS 2018.
  • SPIN 2018 Best Paper Award for the paper Star-Topology Decoupling in SPIN at the 25th International Symposium on Model Checking of Software (SPIN 2018).

Publications

2025

  • Daniel Gnad, Markus Hecher, Sarah Gaggl, Dominik Rusovac, David Speck and Johannes K. Fichte.
    Interactive Exploration of Plan Spaces.
    In Proceedings of the Twenty-Second International Conference on Principles of Knowledge Representation and Reasoning (KR 2025). 2025.
    code | citation

  • Farid Musayev, Dominik Drexler, Daniel Gnad and Jendrik Seipp.
    Combining Heuristics and Transition Classifiers in Classical Planning.
    In Proceedings of the 28th European Conference on Artificial Intelligence (ECAI 2025). 2025.
    citation

  • Gregor Behnke, David Speck and Daniel Gnad.
    AxSAT – Bringing Axioms to SAT Planning.
    In Logics in Artificial Intelligence, pp. 77–93. 2025.
    paper | code | citation

  • Daniel Gnad, Lee or Alon, Eyal Weiss and Alexander Shleyfman.
    PDBs Go Numeric: Pattern-Database Heuristics for Simple Numeric Planning.
    In Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2025). 2025.
    paper | code | citation

  • David Speck, Markus Hecher, Daniel Gnad, Johannes K. Fichte and Augusto B. Corrêa.
    Counting and Reasoning with Plans.
    In Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2025), pp. 26688–26696. 2025.
    paper | code | citation

2024

  • Mika Skjelnes, Daniel Gnad and Jendrik Seipp.
    Cost Partitioning for Multiple Sequence Alignment.
    In Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024), pp. 4224–4231. 2024.
    paper | code | citation

  • 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), pp. 546–554. 2024.
    paper | slides | code | citation

  • Daniel Gnad, Lee or Alon, Eyal Weiss and Alexander Shleyfman.
    PDBs Go Numeric: Pattern-Database Heuristics for Simple Numeric Planning.
    In ICAPS 2024 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP). 2024.
    paper | citation

  • Daniel Gnad and David Speck.
    On an Attempt at Casting Orbit Search as a Task Transformation.
    In ICAPS 2024 Workshop on Echoing (failed) Efforts in Planning (WEEP). 2024.
    paper | citation

  • Mika Skjelnes, Daniel Gnad and Jendrik Seipp.
    Cost Partitioning for Multiple Sequence Alignment.
    In ICAPS 2024 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP). 2024.
    paper | slides | citation (Superseded by the ECAI 2024 paper with the same name.)

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.
    paper | citation

  • Maximilian Fickert and Daniel Gnad.
    DiSCO: Decoupled Search + COnjunctions.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Daniel Gnad, Silvan Sievers and Álvaro Torralba.
    DecAbStar.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Daniel Gnad, Álvaro Torralba and Alexander Shleyfman.
    DecStar-2023.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • 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 | slides | poster | 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.
    paper | citation

  • 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.
    paper | code | citation

  • 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.
    paper | slides | poster | code | citation

  • 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.
    paper | citation

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.
    paper | code | citation

  • 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.
    paper | code | citation

2021

  • Daniel Gnad.
    Star-Topology Decoupled State-Space Search in AI Planning and Model Checking.
    PhD thesis, Saarland University, 2021.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

2020

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

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.
    data | citation

  • 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.
    paper | technical report | citation

  • 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.
    paper | technical report | citation

  • Daniel Gnad, Álvaro Torralba, Martin Domínguez, Carlos Areces and Facundo Bustos.
    IPALAMA - Planner Abstract.
    In Sparkle Planning Challenge: Planner Abstracts. 2019.
    paper | citation

  • 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.
    paper | citation

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.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

  • Daniel Gnad and Jörg Hoffmann.
    Star-Topology Decoupled State Space Search.
    Artificial Intelligence 257, pp. 24–60. 2018.
    data | citation

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.
    paper | citation

  • 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.
    paper | technical report | citation

  • 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.
    paper | technical report | citation

  • 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.
    paper | technical report | citation

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.
    paper | technical report | citation

  • 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.
    paper | technical report | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | citation

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.
    paper | citation

  • 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.
    paper | citation

  • 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.
    paper | technical report | citation