I have left the Machine Reasoning Lab. Please see my personal website.
David Speck

David Speck

Postdoctoral Researcher

About Me

My primary research interest is in the field of artificial intelligence, with a focus on automated planning, i.e., the problem of finding a course of action that allows an intelligent agent to move from any situation it finds itself in to one that satisfies its goals.

Short bio

I completed my bachelor’s degree in 2015 and my master’s degree in 2018 in computer science at the University of Freiburg. From April 2018 to May 2022, I was a scientific employee at the University of Freiburg, Germany, at the Chair of Foundations of Artificial Intelligence of Prof. Dr. Bernhard Nebel and received my PhD in February 2022. From June 2022 to May 2024 I was part of the Machine Reasoning lab at Linköping University, Sweden.

Awards

  • 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).
  • ICAPS 2024 Best Dissertation Award for the doctoral thesis Symbolic Search for Optimal Planning with Expressive Extensions at the 34th International Conference on Automated Planning and Scheduling (ICAPS 2024).
  • 4x First Place, 2x Second Place at the Second CoRe Challenge for the system PARIS 2023: Planning Algorithms for Reconfiguring Independent Sets.
  • Winner, Deterministic Optimal Track for the Ragnarok planner at the 10th International Planning Competition (IPC 2023) at ICAPS 2023.
  • Wolfgang-Gentner-Award for Young Researchers for outstanding scientific achievements in his dissertation awarded by the University of Freiburg.
  • 4x First Place, 3x Second Place, 1x Third Place (in nine tracks) at the First CoRe Challenge for the system PARIS: Planning Algorithms for Reconfiguring Independent Sets at the ICALP 2022 Workshop on Combinatorial Reconfiguration, Paris.
  • ICAPS 2021 Best Student Paper Runner-Up Award for the paper On the Compilability and Expressive Power of State-Dependent Action Costs at the 31st International Conference on Automated Planning and Scheduling (ICAPS 2021).
  • Winner, Discrete MDP Track for the planning system PROST-DD at the 6th International Probabilistic Planning Competition (IPPC 2018) at ICAPS 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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 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

2023

2022

  • Kilian Hu and David Speck.
    On Bidirectional Heuristic Search in Classical Planning: An Analysis of BAE*.
    In Proceedings of the 15th Annual Symposium on Combinatorial Search (SoCS 2022), pp. 91–99. 2022.
    paper | slides | code | 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

  • 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

  • Julian von Tschammer, Robert Mattmüller and David Speck.
    Loopless Top-K Planning.
    In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pp. 380–384. 2022.
    paper | slides | recording | poster | 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

  • David Speck.
    Symbolic Search for Optimal Planning with Expressive Extensions.
    PhD thesis, University of Freiburg, 2022.
    paper | citation

2021

  • 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

  • David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller and Marius Lindauer.
    Learning Heuristic Selection with Dynamic Algorithm Configuration.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 597–605. 2021.
    paper | citation

  • David Speck, David Borukhson, Robert Mattmüller and Bernhard Nebel.
    On the Compilability and Expressive Power of State-Dependent Action Costs.
    In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021), pp. 358–366. 2021.
    paper | citation

  • Gregor Behnke and David Speck.
    Symbolic Search for Optimal Total-Order HTN Planning.
    In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), pp. 11744–11754. 2021.
    paper | citation

  • David Speck and Michael Katz.
    Symbolic Search for Oversubscription Planning.
    In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), pp. 11972–11980. 2021.
    paper | citation

2020

  • David Speck, Florian Geißer and Robert Mattmüller.
    When Perfect Is Not Good Enough: On the Search Behaviour of Symbolic Heuristic Search.
    In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (ICAPS 2020), pp. 263–271. 2020.
    paper | citation

  • David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller and Marius Lindauer.
    Learning Heuristic Selection with Dynamic Algorithm Configuration.
    In ICAPS 2020 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL), pp. 61–69. 2020.
    paper | citation (Superseded by the ICAPS 2021 paper with the same name.)

  • Florian Geißer, David Speck and Thomas Keller.
    Trial-Based Heuristic Tree Search for MDPs with Factored Action Spaces.
    In Proceedings of the 13th Annual Symposium on Combinatorial Search (SoCS 2020), pp. 38–47. 2020.
    paper | code | citation

  • David Speck, Robert Mattmüller and Bernhard Nebel.
    Symbolic Top-k Planning.
    In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), pp. 9967–9974. 2020.
    paper | citation

2019

  • David Speck, Florian Geißer, Robert Mattmüller and Álvaro Torralba.
    Symbolic Planning with Axioms.
    In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling (ICAPS 2019), pp. 464–472. 2019.
    paper | citation

  • Florian Geißer, David Speck and Thomas Keller.
    An Analysis of the Probabilistic Track of the IPC 2018.
    In ICAPS 2019 Workshop on the International Planning Competition (WIPC), pp. 27–35. 2019.
    paper | code | citation

  • Sumitra Corraya, Florian Geißer, David Speck and Robert Mattmüller.
    An Empirical Study of the Usefulness of State-Dependent Action Costs in Planning.
    In Proceedings of the 42nd Annual German Conference on Artificial Intelligence (KI 2019), pp. 123–130. 2019.
    paper | citation

  • Olga Speck, Rafael Horn, David Speck, Johannes Gantner and Philip Leistner.
    Biomimetics meets Sustainability.
    In Bionik: Patente aus der Natur. Tagungsbeiträge zum 9. Bionik-Kongress, pp. 81–91. 2019.
    citation

2018

  • David Speck, Florian Geißer and Robert Mattmüller.
    Symbolic Planning with Edge-Valued Multi-Valued Decision Diagrams.
    In Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS 2018), pp. 250–258. 2018.
    paper | citation

  • Florian Geißer and David Speck.
    Prost-DD – Utilizing Symbolic Classical Planning in THTS.
    In Sixth International Probabilistic Planning Competition (IPC-6): Planner Abstracts, pp. 13–16. 2018.
    paper | citation

  • David Speck, Florian Geißer and Robert Mattmüller.
    SYMPLE: Symbolic Planning based on EVMDDs.
    In Ninth International Planning Competition (IPC-9): Planner Abstracts, pp. 91–94. 2018.
    paper | citation

2017

  • Olga Speck, David Speck, Rafael Horn, Johannes Gantner and Klaus Peter Sedlbauer.
    Biomimetic bio-inspired biomorph sustainable? An attempt to classify and clarify biology-derived technical developments.
    Bioinspiration and Biomimetics 12, pp. 011004. 2017.
    citation

  • David Speck, Christian Dornhege and Wolfram Burgard.
    Shakey 2016 – How Much Does it Take to Redo Shakey the Robot?.
    IEEE Robotics and Automation Letters 2, pp. 1203–1209. 2017.
    citation

2015

  • David Speck, Manuela Ortlieb and Robert Mattmüller.
    Necessary Observations in Nondeterministic Planning.
    In Proceedings of the 38th Annual German Conference on Artificial Intelligence (KI 2015), pp. 181–193. 2015.
    paper | citation