2025

  • Towards Holistic Approach to Robust Execution of MAPF Plans. [PDF]
    David Zahrádka, Denisa Muzíková, Miroslav Kulich, Jirí Svancara, Roman Barták. In proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART), 2025.
  • Generating Safe Policies for Multi-Agent Path Finding with Temporal Uncertainty. [PDF]
    Jiří Švancara, David Zahrádka, Mrinalini Subramanian, Roman Barták, and Miroslav Kulich. In proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART), 2025.

2024

  • The Effectiveness of Autonomous Intersections in a City. [PDF]
    Eliáš Cizl, Jiří Švancara, Roman Barták. In proceedings of the 37th International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2024.
  • Which Objective Function is Solved Faster in Multi-Agent Pathfinding? It Depends. [PDF]
    Jiří Švancara,Dor Atzmon, Klaus Strauch, Roland Kaminski and Torsten Schaub. In proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART), 2024.
  • Improving the Sum-of-Cost Methods for Reduction-based Multi-agent Pathfinding Solvers [PDF]
    Roland Kaminski, Torsten Schaub, Klaus Strauch and Jiří Švancara. In proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART), 2024.

2023

  • Multi-Agent Pathfinding with Predefined Paths: To Wait, or Not to Wait, That Is the Question [Extended Abstract]. [PDF]
    Jiří Švancara, Etienne Tignon, Roman Barták, Torsten Schaub, Philipp Wanko, Roland Kaminski. In proceedings of the 16th International Symposium on Combinatorial Search (SOCS), 2023.
  • Multi-Agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way? [PDF]
    Jiří Švancara, Philipp Obermeier, Matej Husár, Roman Barták and Torsten Schaub. In proceedings of the 15th International Conference on Agents and Artificial Intelligence (ICAART), 2023.
  • Routing and Scheduling in different ways: Abridged Preliminary Report [PDF]
    Jan Behrens, Roland Kaminski, Torsten Schaub, Tran Cao Son, Jiri Svancara, Philipp Wanko. At workshop at the 39th International Conference on Logic Programming (ICLP), 2023.
  • Multi-agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way? [PDF]
    Jiří Švancara, Philipp Obermeier, Matej Husár, Roman Barták and Torsten Schaub. At workshop on Multi-Agent Path Finding at the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
  • To Wait, or Not to Wait, That Is the Question. [PDF]
    Jiří Švancara, Etienne Tignon, Roman Barták, Torsten Schaub, Philipp Wanko, Roland Kaminski. At workshop on Multi-Agent Path Finding at the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.

2022

  • Multi-agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way? [PDF]
    Jiří Švancara, Philipp Obermeier, Matej Husár, Roman Barták and Torsten Schaub. In proceedings of the Fifteenth International Symposium on Combinatorial Search (SOCS), 2022.
  • Reduction-based Solving of Multi-agent Pathfinding on Large Maps Using Graph Pruning. [PDF]
    Matej Husár, Jiří Švancara, Philipp Obermeier, Roman Barták, Torsten Schaub. In proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2022.
  • Coordinated Collision-free Movement of Groups of Agents. [PDF]
    Jiří Švancara, Marika Ivanová, Roman Barták. In proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART), 2022.
  • Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling [PDF]
    Jiří Švancara, Roman Barták. In proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART), 2022.

2021

  • From Classical to Colored Multi-Agent Path Finding [PDF]
    Roman Barták, Marika Ivanová, Jiří Švancara. In proceedings of the Fourteenth International Symposium on Combinatorial Search (SOCS), 2021.
  • Colored Multi-Agent Path Finding: Solving Approaches [PDF]
    Roman Barták, Marika Ivanová, Jiří Švancara. The proceedings of the 34th International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2021.

2020

  • On Modelling Multi-Agent Path Finding as a Classical Planning Problem [PDF]
    Jindrich Vodrážka, Roman Barták, Jiří Švancara. In proceedings of the 32th International Conference on Tools with Artificial Intelligence (ICTAI), 2020.
  • MAPF Scenario: Software for Evaluating MAPF Plans on Real Robots [PDF]
    Roman Barták, Jiří Švancara, Ivan Krasičenko. In proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020.
  • On Modelling Multi-Agent Path Finding as a Classical Planning Problem [PDF]
    Jindrich Vodrážka, Roman Barták, Jiří Švancara. In proceedings of the Thirteenth International Symposium on Combinatorial Search (SOCS), 2020.
  • What Does Multi-agent Path-finding Tell Us About Intelligent Intersections [PDF]
    Věra Škopková, Roman Barták, Jiří Švancara. In proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART), 2020.

2019

  • Multi-Agent Path Finding on Real Robots (Demo session) [PDF]
    Roman Barták, Ivan Krasičenko, Jiří Švancara. International Conference on Automated Planning and Scheduling (ICAPS), 2019.
  • Multi-Agent Path Finding on Ozobots (Demo session) [PDF]
    Roman Barták, Ivan Krasičenko, Jiří Švancara. In proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  • On SAT-Based Approaches for Multi-Agent Path Finding with the Sum-of-Costs Objective [PDF]
    Roman Barták, Jiří Švancara. In proceedings of the Twelfth International Symposium on Combinatorial Search (SOCS), 2019.
  • Multi-agent path finding on real robots [PDF]
    Roman Barták, Jiří Švancara, Věra Škopková, David Nohejl, Ivan Krasičenko. AI Communications 32 (2019) journal.
  • Multi-Agent Path Finding on Real Robots (Demo session) [PDF]
    Roman Barták, Ivan Krasičenko, Jiří Švancara. In proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2019.
  • Combining Strengths of Optimal Multi-Agent Path Finding Algorithms [PDF]
    Jiří Švancara, Roman Barták. In proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART), 2019.
  • Online Multi-Agent Pathfinding [PDF]
    Jiří Švancara, Marek Vlk, Roni Stern, Dor Atzmon, Roman Barták. In proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2019.

2018

  • Multi-agent Path Finding on Real Robots: First Experience with Ozobots [PDF]
    Roman Barták, Jiří Švancara, Věra Škopková, David Nohejl. In proceedings of the Ibero-American Conference on Artificial Intelligence (IBERAMIA), 2018. Lecture Notes in Computer Science, vol 11238.
    Best Paper Award
  • A Scheduling-Based Approach to Multi-Agent Path Finding with Weighted and Capacitated Arcs [PDF]
    Roman Barták, Jiří Švancara, Marek Vlk. In proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
  • Bringing Multi-agent Path Finding Closer to Reality (Doctoral Consortium) [PDF]
    Jiří Švancara. AAMAS 2018 – Doctoral Consortium.
  • Bringing Multi-agent Path Finding Closer to Reality (Doctoral Consortium) [PDF]
    Jiří Švancara. IJCAI 2018 – Doctoral Consortium.
  • Variants of Independence Detection in SAT-Based Optimal Multi-agent Path Finding [PDF]
    Pavel Surynek, Jiří Švancara, Ariel Felner, Eli Boyarski. Agents and Artificial Intelligence – 9th International Conference (ICAART 2017), Revised Selected Papers, pp. 116-136, Lecture Notes in Computer Science 10839, Springer 2018, ISBN 978-3-319-93580-5.

2017

  • Scheduling Models for Multi-Agent Path Finding [PDF]
    Roman Barták, Jiří Švancara, Marek Vlk. In proceedings of the 8th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA), 2017.
  • Independence Detection in SAT-based Multi-Agent Path Finding [PDF]
    Pavel Surynek, Jiří Švancara, Ariel Felner, Eli Boyarski. In proceedings of the 31st Annual Conference of The Japanese Society for Artificial Intelligence (JSAI), 2017.
  • New Flow-based Heuristic for Search Algorithms Solving Multi-Agent Path Finding [PDF]
    Jiří Švancara, Pavel Surynek. In proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART), 2017
  • Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding: A Novel SAT-Based Optimal MAPF Solver [PDF]
    Pavel Surynek, Jiří Švancara, Ariel Felner, Eli Boyarski. In proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART), 2017.