Jiri Svancara

According to our database, Jiri Svancara authored at least 27 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Routing and Scheduling in Answer Set Programming applied to Multi-Agent Path Finding: Preliminary Report.

Roland Kaminski, Torsten Schaub, Tran Cao Son, Jirí Svancara, Philipp Wanko

CoRR, 2024

Which Objective Function is Solved Faster in Multi-Agent Pathfinding? It Depends.

Jirí Svancara, Dor Atzmon, Klaus Strauch, Roland Kaminski, Torsten Schaub

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

Improving the Sum-of-Cost Methods for Reduction-Based Multi-Agent Pathfinding Solvers.

Roland Kaminski, Torsten Schaub, Klaus Strauch, Jirí Svancara

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

Multi-Agent Pathfinding with Predefined Paths: To Wait, or Not to Wait, That Is the Question [Extended Abstract].

Jirí Svancara, Etienne Tignon, Roman Barták, Torsten Schaub, Philipp Wanko, Roland Kaminski

Proceedings of the Sixteenth International Symposium on Combinatorial Search, 2023

Routing and Scheduling in different ways: Abridged Preliminary Report.

Jan Behrens, Roland Kaminski, Torsten Schaub, Tran Cao Son, Jiri Svancara, Philipp Wanko

Proceedings of the International Conference on Logic Programming 2023 Workshops co-located with the 39th International Conference on Logic Programming (ICLP 2023), 2023

Multi-Agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way?

Jirí Svancara, Philipp Obermeier, Matej Husár, Roman Barták, Torsten Schaub

Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023

2022

Multi-agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way? (Extended Abstract).

Jirí Svancara, Philipp Obermeier, Matej Husár, Roman Barták, Torsten Schaub

Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022

Coordinated Collision-free Movement of Groups of Agents.

Jirí Svancara, Marika Ivanová, Roman Barták

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

Tackling Train Routing via Multi-agent Pathfinding and Constraint-based Scheduling.

Jirí Svancara, Roman Barták

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

Reduction-based Solving of Multi-agent Pathfinding on Large Maps Using Graph Pruning.

Matej Husár, Jirí Svancara, Philipp Obermeier, Roman Barták, Torsten Schaub

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

From Classical to Colored Multi-Agent Path Finding.

Roman Barták, Marika Ivanová, Jirí Svancara

Proceedings of the Fourteenth International Symposium on Combinatorial Search, 2021

Colored Multi-Agent Path Finding: Solving Approaches.

Roman Barták, Marika Ivanová, Jirí Svancara

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

2020

On Modelling Multi-Agent Path Finding as a Classical Planning Problem.

Jindrich Vodrázka, Roman Barták, Jirí Svancara

Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

What Does Multi-agent Path-finding Tell Us About Intelligent Intersections.

Vera Skopková, Roman Barták, Jirí Svancara

Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020

MAPF Scenario: Software for Evaluating MAPF Plans on Real Robots.

Roman Barták, Jirí Svancara, Ivan Krasicenko

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Multi-agent path finding on real robots.

Roman Barták, Jirí Svancara, Vera Skopková, David Nohejl, Ivan Krasicenko

AI Commun., 2019

On SAT-Based Approaches for Multi-Agent Path Finding with the Sum-of-Costs Objective.

Roman Barták, Jirí Svancara

Proceedings of the Twelfth International Symposium on Combinatorial Search, 2019

Multi-Agent Path Finding on Ozobots.

Roman Barták, Ivan Krasicenko, Jirí Svancara

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Combining Strengths of Optimal Multi-Agent Path Finding Algorithms.

Jirí Svancara, Roman Barták

Proceedings of the 11th International Conference on Agents and Artificial Intelligence, 2019

Multi-Agent Path Finding on Real Robots.

Roman Barták, Ivan Krasicenko, Jirí Svancara

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Online Multi-Agent Pathfinding.

Jirí Svancara, Marek Vlk, Roni Stern, Dor Atzmon, Roman Barták

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Bringing Multi-agent Path Finding Closer to Reality.

Jirí Svancara

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Multi-agent Path Finding on Real Robots: First Experience with Ozobots.

Roman Barták, Jirí Svancara, Vera Skopková, David Nohejl

Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2018, 2018

A Scheduling-Based Approach to Multi-Agent Path Finding with Weighted and Capacitated Arcs.

Roman Barták, Jiri Svancara, Marek Vlk

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

New Flow-based Heuristic for Search Algorithms Solving Multi-agent Path Finding.

Jiri Svancara, Pavel Surynek

Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017

Variants of Independence Detection in SAT-Based Optimal Multi-agent Path Finding.

Pavel Surynek, Jiri Svancara, Ariel Felner, Eli Boyarski

Proceedings of the Agents and Artificial Intelligence - 9th International Conference, 2017

Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver.

Pavel Surynek, Jiri Svancara, Ariel Felner, Eli Boyarski

Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017