Jendrik Seipp

Jendrik Seipp (he/him)

Senior Associate Professor

About me

I'm a Senior Associate Professor in Artificial Intelligence at Linköping University, Sweden, and I lead the Machine Reasoning Lab in the AIICS division. My main research interests are AI planning and its connections to machine learning.

Short bio

I received my MSc in computer science from the University of Freiburg, Germany, in December 2012. In March 2018, I completed my PhD under the supervision of Prof. Malte Helmert with the Artificial Intelligence group at the University of Basel, Switzerland. Afterwards, I stayed on as a postdoc until I was appointed assistant professor at Linköping University, Sweden, in January 2021. I became docent (habilitation) in September 2022, associate professor in September 2023 and senior associate professor in September 2024.

For more information, please see my academic CV.

My office 2G:466 is located in the E-building at Campus Valla in Linköping.

Software

Tutorials

Awards

Publications

2025

  • Paul Höft, David Speck and Jendrik Seipp.
    Representing Perfect Saturated Cost Partitioning Heuristics in Classical Planning.
    In Proceedings of the Twenty-Second International Conference on Principles of Knowledge Representation and Reasoning (KR 2025). 2025.
    paper | code | citation

  • Augusto B. Corrêa and Jendrik Seipp.
    Alternation-Based Novelty Search.
    In Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling (ICAPS 2025). 2025.
    paper | 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

  • Mauricio Salerno, Raquel Fuentetaja, David Speck and Jendrik Seipp.
    Merging Cartesian Abstractions for Classical Planning.
    In Proceedings of the 28th European Conference on Artificial Intelligence (ECAI 2025). 2025.
    citation

  • Martín Pozo and Jendrik Seipp.
    Abstraction Heuristics for Classical Planning Tasks with Conditional Effects.
    In Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025). 2025.
    paper | code | citation

  • Augusto B. Corrêa, André Grahl Pereira and Jendrik Seipp.
    Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code.
    In arXiv:2503.18809 [cs.AI]. 2025.
    paper | citation

  • David Speck, Jendrik Seipp and Álvaro Torralba.
    Symbolic Search for Cost-Optimal Planning with Expressive Model Extensions.
    Journal of Artificial Intelligence Research 82, pp. 1349–1405. 2025.
    paper | code | citation

2024

  • Jendrik Seipp.
    Dissecting Scorpion: Ablation Study of an Optimal Classical Planner.
    In Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024), pp. 39–42. 2024.
    paper | slides | code | citation

  • 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

  • Clemens Büchner, Patrick Ferber, Jendrik Seipp and Malte Helmert.
    Abstraction Heuristics for Factored Tasks.
    In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024), pp. 40–49. 2024.
    paper | slides | poster | code | citation

  • Paul Höft, David Speck, Florian Pommerening and Jendrik Seipp.
    Versatile Cost Partitioning with Exact Sensitivity Analysis.
    In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024), pp. 276–280. 2024.
    paper | slides | poster | code | citation

  • Jendrik Seipp.
    Efficiently Computing Transitions in Cartesian Abstractions.
    In Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2024), pp. 509–513. 2024.
    paper | slides | code | citation

  • Elliot Gestrin, Marco Kuhlmann and Jendrik Seipp.
    NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions.
    In ICAPS 2024 Workshop on Human-Aware and Explainable Planning (HAXP). 2024.
    paper | slides | citation

  • Augusto B. Corrêa and Jendrik Seipp.
    Consolidating LAMA with Best-First Width Search.
    In ICAPS 2024 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP). 2024.
    paper | slides | citation

  • Kristina Levina, Nikolaos Pappas, Athanasios Karapantelakis, Aneta Vulgarakis Feljan and Jendrik Seipp.
    Numeric Reward Machines.
    In ICAPS 2024 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL). 2024.
    paper | poster | 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.)

  • Dominik Drexler, Jendrik Seipp and Hector Geffner.
    Expressing and Exploiting Subgoal Structure in Classical Planning Using Sketches.
    Journal of Artificial Intelligence Research 80, pp. 171–208. 2024.
    paper | code | citation

  • Damien Van Meerbeeck, Gilles Pesant and Jendrik Seipp.
    End-to-End Classical Planning using CP and Belief Propagation (Extended Abstract).
    In Extended Abstracts Presented at CPAIOR 2024. 2024.
    paper | poster | citation

  • Ayal Taitler, Ron Alford, Joan Espasa, Gregor Behnke, Daniel Fišer, Michael Gimelfarb, Florian Pommerening, Scott Sanner, Enrico Scala, Dominik Schreiber, Javier Segovia-Aguas and Jendrik Seipp.
    The 2023 International Planning Competition.
    AI Magazine 45, pp. 280–296. 2024.
    paper | citation

2023

  • Remo Christen, Salomé Eriksson, Michael Katz, Christian Muise, Alice Petrov, Florian Pommerening, Jendrik Seipp, Silvan Sievers and David Speck.
    PARIS: Planning Algorithms for Reconfiguring Independent Sets.
    In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pp. 453–460. 2023.
    paper | slides | poster | code | citation

  • Paul Höft, David Speck and Jendrik Seipp.
    Sensitivity Analysis for Saturated Post-hoc Optimization in Classical Planning.
    In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pp. 1044–1051. 2023.
    paper | slides | poster | code | citation

  • Thorsten Klößner, Jendrik Seipp and Marcel Steinmetz.
    Cartesian Abstractions and Saturated Cost Partitioning in Probabilistic Planning.
    In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pp. 1272–1279. 2023.
    paper | slides | poster | code | citation

  • Dominik Drexler, Jendrik Seipp and Hector Geffner.
    Learning Hierarchical Policies by Iteratively Reducing the Width of Sketch Rules.
    In Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), pp. 208–218. 2023.
    paper | slides | code | citation

  • Mauricio Salerno, Raquel Fuentetaja and Jendrik Seipp.
    Eliminating Redundant Actions from Plans using Classical Planning.
    In Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), pp. 774–778. 2023.
    paper | code | citation

  • Clemens Büchner, Remo Christen, Augusto B. Corrêa, Salomé Eriksson, Patrick Ferber, Jendrik Seipp and Silvan Sievers.
    Fast Downward Stone Soup 2023.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | code | citation

  • Augusto B. Corrêa, Guillem Francès, Markus Hecher, Davide Mario Longo and Jendrik Seipp.
    Levitron: Combining Ground and Lifted Planning.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Augusto B. Corrêa, Guillem Francès, Markus Hecher, Davide Mario Longo and Jendrik Seipp.
    The Powerlifted Planning System in the IPC 2023.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Augusto B. Corrêa, Guillem Francès, Markus Hecher, Davide Mario Longo and Jendrik Seipp.
    Scorpion Maidu: Width Search in the Scorpion Planning System.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • 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

  • Dominik Drexler, Jendrik Seipp and David Speck.
    Odin: A Planner Based on Saturated Transition Cost Partitioning.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Patrick Ferber, Michael Katz, Jendrik Seipp, Silvan Sievers, Daniel Borrajo, Isabel Cenamor, Tomas de la Rosa, Fernando Fernandez-Rebollo, Carlos Linares López, Sergio Nuñez, Alberto Pozanco, Horst Samulowitz and Shirin Sohrabi.
    Hapori Stone Soup.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Paul Höft, David Speck and Jendrik Seipp.
    Dofri.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Mauricio Salerno, Raquel Fuentetaja and Jendrik Seipp.
    Spock: Fast Downward Stone Soup with Redundant Action Elimination.
    In Tenth International Planning Competition (IPC-10): Planner Abstracts. 2023.
    paper | citation

  • Jendrik Seipp.
    Scorpion 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.)

  • Dominik Drexler and Jendrik Seipp.
    DLPlan: Description Logics State Features for Planning.
    In ICAPS 2023 System Demonstrations and Exhibits. 2023.
    paper | 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

2022

  • Patrick Ferber, Liat Cohen, Jendrik Seipp and Thomas Keller.
    Learning and Exploiting Progress States in Greedy Best-First Search.
    In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), pp. 4740–4746. 2022.
    paper | slides | poster | code | citation

  • Dominik Drexler, Javier Segovia-Aguas and Jendrik Seipp.
    Learning General Policies and Helpful Action Classifiers from Partial State Spaces.
    In IJCAI 2022 Workshop on Generalization in Planning. 2022.
    paper | slides | citation

  • Remo Christen, Salomé Eriksson, Michael Katz, Emil Keyder, Christian Muise, Alice Petrov, Florian Pommerening, Jendrik Seipp, Silvan Sievers and David Speck.
    (PARIS) Planning Algorithms for Reconfiguring Independent Sets.
    In First CoRe Challenge: Solver and Graph Descriptions, pp. 15–22. 2022.
    paper | citation

  • Augusto B. Corrêa and Jendrik Seipp.
    Best-First Width Search for Lifted Classical Planning.
    In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 11–15. 2022.
    paper | slides | poster | code | citation

  • Dominik Drexler, Jendrik Seipp and Hector Geffner.
    Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width.
    In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 62–70. 2022.
    paper | slides | poster | code | citation

  • David Speck and Jendrik Seipp.
    New Refinement Strategies for Cartesian Abstractions.
    In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 348–352. 2022.
    paper | slides | recording | poster | code | citation

  • Christian Muise, Florian Pommerening, Jendrik Seipp and Michael Katz.
    Planutils: Bringing Planning to the Masses.
    In ICAPS 2022 System Demonstrations and Exhibits. 2022.
    paper | recording | poster | citation

  • Clemens Büchner, Patrick Ferber, Jendrik Seipp and Malte Helmert.
    A Comparison of Abstraction Heuristics for Rubik's Cube.
    In ICAPS 2022 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP). 2022.
    paper | slides | recording | code | citation

  • André Biedenkapp, David Speck, Silvan Sievers, Frank Hutter, Marius Lindauer and Jendrik Seipp.
    Learning Domain-Independent Policies for Open List Selection.
    In ICAPS 2022 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL). 2022.
    paper | slides | recording | citation

  • Patrick Ferber and Jendrik Seipp.
    Explainable Planner Selection for Classical Planning.
    In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), pp. 9741–9749. 2022.
    paper | slides | poster | code | citation

2021

  • Dominik Drexler, Jendrik Seipp and Hector Geffner.
    Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches.
    In Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2021), pp. 258–268. 2021.
    paper | slides | recording | poster | citation

  • Simon Ståhlberg, Guillem Francès and Jendrik Seipp.
    Learning Generalized Unsolvability Heuristics for Classical Planning.
    In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), pp. 4175–4181. 2021.
    paper | slides | poster | code | citation

  • Dominik Drexler, Jendrik Seipp and David Speck.
    Subset-Saturated Transition Cost Partitioning.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 131–139. 2021.
    paper | slides | poster | code | citation

  • Florian Pommerening, Thomas Keller, Valentina Halasi, Jendrik Seipp, Silvan Sievers and Malte Helmert.
    Dantzig-Wolfe Decomposition for Cost Partitioning.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 271–280. 2021.
    paper | technical report | slides | recording | poster | code | citation

  • Jendrik Seipp.
    Online Saturated Cost Partitioning for Classical Planning.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 317–321. 2021.
    paper | slides | poster | code | citation

  • Álvaro Torralba, Jendrik Seipp and Silvan Sievers.
    Automatic Instance Generation for Classical Planning.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 376–384. 2021.
    paper | slides | poster | code | citation

  • Jendrik Seipp, Thomas Keller and Malte Helmert.
    Saturated Post-hoc Optimization for Classical Planning.
    In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), pp. 11947–11953. 2021.
    paper | slides | recording | poster | code | citation

2020

  • Jendrik Seipp, Samuel von Allmen and Malte Helmert.
    Incremental Search for Counterexample-Guided Cartesian Abstraction Refinement.
    In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (ICAPS 2020), pp. 244–248. 2020.
    paper | slides | recording | poster | code | citation

  • Jendrik Seipp.
    Online Saturated Cost Partitioning for Classical Planning.
    In ICAPS 2020 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP), pp. 16–22. 2020.
    paper | slides | recording | code | citation (Superseded by the ICAPS 2021 paper with the same name.)

  • Patrick Ferber and Jendrik Seipp.
    Explainable Planner Selection.
    In ICAPS 2020 Workshop on Explainable AI Planning (XAIP). 2020.
    paper | slides | recording | poster | citation (Superseded by the AAAI 2022 paper "Explainable Planner Selection for Classical Planning".)

  • Álvaro Torralba, Jendrik Seipp and Silvan Sievers.
    Automatic Configuration of Benchmark Sets for Classical Planning.
    In ICAPS 2020 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP), pp. 58–66. 2020.
    paper | slides | recording | citation (Superseded by the ICAPS 2021 paper "Automatic Instance Generation for Classical Planning".)

  • Gabriele Röger, Malte Helmert, Jendrik Seipp and Silvan Sievers.
    An Atom-Centric Perspective on Stubborn Sets.
    In Proceedings of the 13th Annual Symposium on Combinatorial Search (SoCS 2020), pp. 57–65. 2020.
    paper | slides | recording | code | citation

  • Jendrik Seipp, Thomas Keller and Malte Helmert.
    Saturated Cost Partitioning for Optimal Classical Planning.
    Journal of Artificial Intelligence Research 67, pp. 129–167. 2020.
    paper | code | citation

2019

  • Jendrik Seipp.
    Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning.
    In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 5621–5627. 2019.
    paper | slides | code | citation

  • Jendrik Seipp and Malte Helmert.
    Subset-Saturated Cost Partitioning for Optimal Classical Planning.
    In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling (ICAPS 2019), pp. 391–400. 2019.
    paper | technical report | slides | code | citation

  • Jendrik Seipp.
    Planner Metrics Should Satisfy Independence of Irrelevant Alternatives.
    In ICAPS 2019 Workshop on the International Planning Competition (WIPC), pp. 40–41. 2019.
    paper | slides | citation

  • Jendrik Seipp.
    Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning.
    In ICAPS 2019 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP), pp. 72–80. 2019.
    paper | slides | citation (Superseded by the IJCAI 2019 paper with the same name.)

2018

  • Jendrik Seipp and Malte Helmert.
    Counterexample-Guided Cartesian Abstraction Refinement for Classical Planning.
    Journal of Artificial Intelligence Research 62, pp. 535–577. 2018.
    paper | citation

  • Jendrik Seipp.
    Fast Downward Remix.
    In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 74–76. 2018.
    paper | citation

  • Jendrik Seipp.
    Fast Downward Scorpion.
    In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 77–79. 2018.
    paper | citation

  • Jendrik Seipp and Gabriele Röger.
    Fast Downward Stone Soup 2018.
    In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 80–82. 2018.
    paper | citation

  • Jendrik Seipp.
    Counterexample-guided Cartesian Abstraction Refinement and Saturated Cost Partitioning for Optimal Classical Planning.
    PhD thesis, University of Basel, 2018.
    paper | slides | recording | citation

2017

  • Jendrik Seipp, Thomas Keller and Malte Helmert.
    A Comparison of Cost Partitioning Algorithms for Optimal Classical Planning.
    In Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS 2017), pp. 259–268. 2017.
    paper | slides | recording | poster | citation

  • Jendrik Seipp.
    Better Orders for Saturated Cost Partitioning in Optimal Classical Planning.
    In Proceedings of the 10th Annual Symposium on Combinatorial Search (SoCS 2017), pp. 149–153. 2017.
    paper | slides | citation

  • Jendrik Seipp, Thomas Keller and Malte Helmert.
    Narrowing the Gap Between Saturated and Optimal Cost Partitioning for Classical Planning.
    In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 3651–3657. 2017.
    paper | slides | citation

2016

  • Thomas Keller, Florian Pommerening, Jendrik Seipp, Florian Geißer and Robert Mattmüller.
    State-dependent Cost Partitionings for Cartesian Abstractions in Classical Planning.
    In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 3161–3169. 2016.
    paper | technical report | citation

  • Jendrik Seipp, Florian Pommerening, Gabriele Röger and Malte Helmert.
    Correlation Complexity of Classical Planning Domains.
    In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 3242–3250. 2016.
    paper | slides | poster | citation

  • Florian Pommerening and Jendrik Seipp.
    Fast Downward Dead-End Pattern Database.
    In Unsolvability International Planning Competition: Planner Abstracts, pp. 2. 2016.
    paper | citation

  • Jendrik Seipp, Florian Pommerening, Silvan Sievers, Martin Wehrle, Chris Fawcett and Yusra Alkhazraji.
    Fast Downward Aidos.
    In Unsolvability International Planning Competition: Planner Abstracts, pp. 28–38. 2016.
    paper | code | citation

  • Jendrik Seipp, Florian Pommerening, Gabriele Röger and Malte Helmert.
    Correlation Complexity of Classical Planning Domains.
    In ICAPS 2016 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP), pp. 12–20. 2016.
    paper | slides | citation (Superseded by the IJCAI 2016 paper with the same name.)

2015

  • Jendrik Seipp, Florian Pommerening and Malte Helmert.
    New Optimization Functions for Potential Heuristics.
    In Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS 2015), pp. 193–201. 2015.
    paper | slides | recording | citation

  • Jendrik Seipp, Silvan Sievers, Malte Helmert and Frank Hutter.
    Automatic Configuration of Sequential Planning Portfolios.
    In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 3364–3370. 2015.
    paper | technical report | slides | code | data | citation

  • Florian Pommerening, Malte Helmert, Gabriele Röger and Jendrik Seipp.
    From Non-Negative to General Operator Cost Partitioning.
    In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 3335–3341. 2015.
    paper | technical report | erratum | slides | citation

2014

  • Jendrik Seipp, Silvan Sievers and Frank Hutter.
    Fast Downward SMAC.
    In Eighth International Planning Competition (IPC-8) Planning and Learning Part: Planner Abstracts. 2014.
    paper | code | citation

  • Jendrik Seipp, Silvan Sievers and Frank Hutter.
    Fast Downward Cedalion.
    In Eighth International Planning Competition (IPC-8) Planning and Learning Part: Planner Abstracts. 2014.
    paper | code | citation

  • Jendrik Seipp, Silvan Sievers and Frank Hutter.
    Fast Downward Cedalion.
    In Eighth International Planning Competition (IPC-8): Planner Abstracts, pp. 17–27. 2014.
    paper | code | citation

  • Jendrik Seipp, Manuel Braun and Johannes Garimort.
    Fast Downward Uniform Portfolio.
    In Eighth International Planning Competition (IPC-8): Planner Abstracts, pp. 32. 2014.
    paper | citation

  • Gabriele Röger, Florian Pommerening and Jendrik Seipp.
    Fast Downward Stone Soup 2014.
    In Eighth International Planning Competition (IPC-8): Planner Abstracts, pp. 28–31. 2014.
    paper | citation

  • Jendrik Seipp and Malte Helmert.
    Diverse and Additive Cartesian Abstraction Heuristics.
    In Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2014), pp. 289–297. 2014.
    paper | slides | recording | citation

2013

  • Jendrik Seipp and Malte Helmert.
    Additive Counterexample-guided Cartesian Abstraction Refinement.
    In Late-Breaking Developments in the Field of Artificial Intelligence – Papers Presented at the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2013) – AAAI Technical Report WS-13-17, pp. 119–121. 2013.
    paper | citation

  • Jendrik Seipp and Malte Helmert.
    Counterexample-guided Cartesian Abstraction Refinement.
    In Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling (ICAPS 2013), pp. 347–351. 2013.
    paper | slides | recording | citation

2012

  • Jendrik Seipp.
    Counterexample-guided Abstraction Refinement for Classical Planning.
    Master's thesis, University of Freiburg, 2012.
    paper | citation

  • Jendrik Seipp, Manuel Braun, Johannes Garimort and Malte Helmert.
    Learning Portfolios of Automatically Tuned Planners.
    In Proceedings of the Twenty-Second International Conference on Automated Planning and Scheduling (ICAPS 2012), pp. 368–372. 2012.
    paper | technical report | slides | code | citation (This version of the paper fixes a small mistake in the published version. In Section "Tuning Planners", the published version states that preferred operators are used in 20 of the 21 configurations. The correct statement is that they are used in 19 of the 21 configurations.)

2011

  • Carmel Domshlak, Malte Helmert, Erez Karpas, Emil Keyder, Silvia Richter, Gabriele Röger, Jendrik Seipp and Matthias Westphal.
    BJOLP: The Big Joint Optimal Landmarks Planner.
    In IPC 2011 Planner Abstracts, pp. 91–95. 2011.
    paper | citation

  • Chris Fawcett, Malte Helmert, Holger Hoos, Erez Karpas, Gabriele Röger and Jendrik Seipp.
    FD-Autotune: Automated Configuration of Fast Downward.
    In IPC 2011 Planner Abstracts, pp. 31–37. 2011.
    paper | citation

  • Chris Fawcett, Malte Helmert, Holger Hoos, Erez Karpas, Gabriele Röger and Jendrik Seipp.
    FD-Autotune: Domain-Specific Configuration of Fast Downward.
    In IPC 2011 Planner Abstracts, Planning and Learning Part. 2011.
    paper | citation

  • Malte Helmert, Gabriele Röger, Jendrik Seipp, Erez Karpas, Jörg Hoffmann, Emil Keyder, Raz Nissim, Silvia Richter and Matthias Westphal.
    Fast Downward Stone Soup.
    In IPC 2011 Planner Abstracts, pp. 38–45. 2011.
    paper | citation

  • Chris Fawcett, Malte Helmert, Holger Hoos, Erez Karpas, Gabriele Röger and Jendrik Seipp.
    FD-Autotune: Domain-Specific Configuration using Fast Downward.
    In ICAPS 2011 Workshop on Planning and Learning, pp. 13–17. 2011.
    paper | citation

  • Jendrik Seipp and Malte Helmert.
    Fluent Merging for Classical Planning Problems.
    In ICAPS 2011 Workshop on Knowledge Engineering for Planning and Scheduling, pp. 47–53. 2011.
    paper | slides | code | citation (This version of the paper fixes two mistakes (in Def. 2 and in the text after Def. 3) that are present in the version of the paper that is linked from the workshop webpage.)

2009

  • Jendrik Seipp.
    Fluent Merging für klassische Planungsprobleme.
    Bachelor's thesis, University of Freiburg, 2009.
    paper | citation (In German.)