mapf.info | Main / All Publications by Year

We are listing the publications of the participants of the joint NSF-BSF project "NSF-BSF:RI:Small:Collaborative Research:Next-Generation Multi-Agent Path Finding Algorithms" and the publications of their collaborators. You can download the bibtex file for all publications. The bibtex entries in that file include the meta information needed to generate all mapf.info publication pages automatically but can also be used with LaTex to generate the bibliographies for publications.

2023

J. Li, T. Hoang, E. Lin, H. Vu and S. Koenig. Intersection Coordination with Priority-Based Search for Autonomous Vehicles. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023.
Z. Ren, J. Li, H. Zhang, S. Koenig, S. Rathinam and H. Choset. Binary Branching Multi-Objective Conflict-Based Search for Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2023.
Y. Zheng, H. Ma, S. Koenig, E. Kline and S. Kumar. Priority-Based Search for the Virtual Network Embedding Problem. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2023.
T. Huang, V. Shivashankar, M. Caldara, J. Durham, J. Li, B. Dilkina and S. Koenig. Deadline-Aware Multi-Agent Tour Planning. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2023.
C. Leet, C. Oh, M. Lora, S. Koenig and P. Nuzzo. Task Assignment, Scheduling, and Motion Planning for Automated Warehouses for Million Product Workloads. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2023.
D. Vainshtein, Y. Sherma, K. Solovey and O. Salzman. Multi-Agent Terraforming: Efficient Multi-Agent Path Finding via Environment Manipulation. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2023.
Y. Wang, B. Xiang, S. Huang and G. Sartoretti. SCRIMP: Scalable Communication for Reinforcement- and Imitation-Learning-Based Multi-Agent Pathfinding [Extended Abstract]. 2023.
Z. Ren, S. Rathinam and H. Choset. A Conflict-Based Search Framework for Multiobjective Multiagent Path Finding. IEEE Transactions on Automation Science and Engineering, 20, (2), 1262-1274, 2023.
Z. Ren, S. Rathinam and H. Choset. CBSS: A New Approach for Multiagent Combinatorial Path Finding. IEEE Transactions on Robotics, 39, (4), 2669-2683, 2023.
E. Lam, D. Harabor, P. Stuckey and J. Li. Exact Anytime Multi-Agent Path Finding Using Branch-and-Cut-and-Price and Large Neighborhood Search. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2023.
B. Shen, Z. Chen, J. Li, M. A. Cheema, D. Harabor and P. Stuckey. Beyond Pairwise Reasoning in Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2023.
Y. Zhang, M. C. Fontaine, V. Bhatt, S. Nikolaidis and J. Li. Multi-Robot Coordination and Layout Design for Automated Warehousing. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2023.
A. Paul, Y. Feng and J. Li. A Fast Rescheduling Algorithm for Real-Time Multi-Robot Coordination. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2023.
B. Li and H. Ma. Double-Deck Multi-Agent Pickup and Delivery: Multi-Robot Rearrangement in Large-Scale Warehouses. IEEE Robotics and Automation Letters, 8, (6), 3701-3708, 2023.
A. Natan, R. Stern and M. Kalech. Blame Attribution for Multi-Agent Pathfinding Execution Failures. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2358-2360, 2023.
D. Atzmon, S. Bernardini, F. Fagnani and D. Fairbairn. Exploiting Geometric Constraints in Multi-Agent Pathfinding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 17-25, 2023.
Y. Livne, D. Atzmon, S. Skyler, E. Boyarski, A. Shapiro and A. Felner. Optimally Solving the Multiple Watchman Route Problem with Heuristic Search. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 905-913, 2023.
G. Fine, D. Atzmon and N. Agmon. Anonymous Multi-Agent Path Finding with Individual Deadlines. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 869-877, 2023.
P. Surynek. Candidate Path Selection Heuristics for Multi-Agent Path Finding: A Novel Compilation-Based Method. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 2023.

2022

J. Li. Efficient and Effective Techniques for Large-Scale Multi-Agent Path Finding. PhD thesis, Department of Computer Science, University of Southern California, Los Angeles (California), 2022.
J. Li, Z. Chen, D. Harabor, P. Stuckey and S. Koenig. MAPF-LNS2: Fast Repairing for Multi-Agent Path Finding via Large Neighborhood Search. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.
C. Leet, J. Li and S. Koenig. Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.
T. Huang, J. Li, S. Koenig and B. Dilkina. Anytime Multi-Agent Path Finding via Machine Learning-Guided Large Neighborhood Search. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.
S.-H. Chan, J. Li, G. Gange, D. Harabor, P. Stuckey and S. Koenig. Flex Distribution for Bounded-Suboptimal Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.
Y. Zheng, S. Ravi, E. Kline, S. Koenig and S. Kumar. Conflict-Based Search for the Virtual Network Embedding Problem. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2022.
H. Zhang, J. Chen, J. Li, B. Williams and S. Koenig. Multi-Agent Path Finding for Precedence-Constrained Goal Sequences. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1464-1472, 2022.
X. Zhong, J. Li, S. Koenig and H. Ma. Optimal and Bounded-Suboptimal Multi-Goal Task Assignment and Path Finding. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2022.
S. Zhang, J. Li, T. Huang, S. Koenig and B. Dilkina. Learning a Priority Ordering for Prioritized Planning in Multi-Agent Path Finding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2022.
S. Varambally, J. Li and S. Koenig. Which MAPF Model Works Best for Automated Warehousing?. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2022.
H. Zhang, Y. Li, J. Li, S. Kumar and S. Koenig. Mutex Propagation in Multi-Agent Path Finding for Large Agents. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2022.
H. Zhang, J. Li, P. Surynek, S. Kumar and S. Koenig. Multi-Agent Path Finding with Mutex Propagation. Artificial Intelligence, 311, 103766, 2022.
C. Leet, J. Li and S. Koenig. Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 9386-9395, 2022.
Q. Xu, J. Li, S. Koenig and H. Ma. Multi-Goal Multi-Agent Pickup and Delivery. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 9964-9971, 2022.
N. Madar, K. Solovey and O. Salzman. Leveraging Experience in Lifelong Multi-Agent Pathfinding. In Proceedings of the Symposium on Combinatorial Search (SoCS), (in print), 2022.
E. Lam, P. Le Bodic, D. Harabor and P. Stuckey. Branch-and-Cut-and-Price for Multi-Agent Path Finding. Computers and Operations Research, 2022.
H. Ma. Intelligent Planning for Large-Scale Multi-Agent Systems. AI Magazine, 43, (4), 376-382, 2022.
H. Ma. Graph-Based Multi-Robot Path Finding and Planning. Current Robotics Reports, 3, (3), 77-84, 2022.
J. Morag, A. Felner, R. Stern, D. Atzmon and E. Boyarski. Online Multi-Agent Path Finding: New Results. In Proceedings of the Symposium on Combinatorial Search (SoCS), 229-233, 2022.
J. Kottinger, S. Almagor and M. Lahijanian. Conflict-Based Search for Explainable Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), (in print), 2022.
P. Surynek. Problem Compilation for Multi-Agent Path Finding: A Survey. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2022.
A. Andreychuk, K. Yakovlev, P. Surynek, D. Atzmon and R. Stern. Multi-Agent Pathfinding with Continuous Time. Artificial Intelligence, 305, 103662, 2022.
P. Surynek, R. Stern, E. Boyarski and A. Felner. Migrating Techniques from Search-Based Multi-Agent Path Finding Solvers to SAT-Based Approach. Journal of Artificial Intelligence Research (JAIR), 73, 553-618, 2022.
Z. Ren, S. Rathinam and H. Choset. Conflict-Based Steiner Search for Multi-Agent Combinatorial Path Finding. In Proceedings of Robotics: Science and Systems, 2022.

2021

J. Li, D. Harabor, P. Stuckey, H. Ma, G. Gange and S. Koenig. Pairwise Symmetry Reasoning for Multi-Agent Path Finding Search. Artificial Intelligence, 301, 103574, 2021.
J. Li, Z. Chen, D. Harabor, P. Stuckey and S. Koenig. Anytime Multi-Agent Path Finding via Large Neighborhood Search. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 4127-4135, 2021.
J. Li, W. Ruml and S. Koenig. EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 12353-12362, 2021.
J. Li, A. Tinka, S. Kiesel, J. Durham, S. Kumar and S. Koenig. Lifelong Multi-Agent Path Finding in Large-Scale Warehouses. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 11272-11281, 2021.
T. Huang, S. Koenig and B. Dilkina. Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 11246-11253, 2021.
E. Boyarski, A. Felner, P. Le Bodic, D. Harabor, P. Stuckey and S. Koenig. f-Aware Conflict Prioritization & Improved Heuristics for Conflict-Based Search. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 12241-12248, 2021.
T. Huang, B. Dilkina and S. Koenig. Learning Node-Selection Strategies in Bounded-Suboptimal Conflict-Based Search for Multi-Agent Path Finding. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 611-619, 2021.
J. Li, Z. Chen, Y. Zheng, S.-H. Chan, D. Harabor, P. Stuckey, H. Ma and S. Koenig. Scalable Rail Planning and Replanning: Winning the 2020 Flatland Challenge. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 477-485, 2021.
H. Zhang, N. Tiruviluamala, S. Koenig and S. Kumar. Temporal Reasoning with Kinodynamic Networks. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 415-425, 2021.
H. Zhang, M. Yao, Z. Liu, J. Li, L. Terr, S.-H. Chan, S. Kumar and S. Koenig. A Hierarchical Approach to Multi-Agent Path Finding. In ICAPS-21 Workshop on Hierarchical Planning (HPLAN), 2021.
E. Boyarski, A. Felner, P. Le Bodic, D. Harabor, P. Stuckey and S. Koenig. Further Improved Heuristics for Conflict-Based Search [Doctoral Dissertation Abstract]. In Proceedings of the Symposium on Combinatorial Search (SoCS), 213-215, 2021.
N. Greshler,, O. Gordon, O. Salzman and N. Shimkin. Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance. In Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems (MRS), 20-28, 2021.
O. Gordon,, Y. Filmus, and O. Salzman. Revisiting the Complexity Analysis of Conflict-Based Search: New Computational Techniques and Improved Bounds. In Proceedings of the Symposium on Combinatorial Search (SoCS), 64-72, 2021.
M. Damani, Z. Luo, E. Wenzel and G. Sartoretti. PRIMAL2: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Lifelong. IEEE Robotics and Automation Letters, 6, (2), 2666-2673, 2021.
Z. Ma, Y. Luo and H. Ma. Distributed Heuristic Multi-Agent Path Finding with Communication. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2021', PAGES.
H. Ma. A Competitive Analysis of Online Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 234-242, 2021.
T. Shahar, S. Shekhar, D. Atzmon, A. Saffidine, B. Juba and R. Stern. Safe Multi-Agent Pathfinding with Time Uncertainty. Journal of Artificial Intelligence Research (JAIR), 70, 923-954, 2021.
J. Chudy and P. Surynek. ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021.
P. Surynek. Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021.
T. Walker, N. Sturtevant, A. Felner, H. Zhang, J. Li and S. Kumar. Conflict-Based Increasing Cost Search. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 385-395, 2021.
J. Kottinger, S. Almagor and M. Lahijanian. MAPS-X: Explainable Multi-Robot Motion Planning via Segmentation. In Proceedings of the International Conference on Robotics and Automation (ICRA), 7994-8000, 2021.
P. Surynek. Sum of Costs Optimal Multi-Agent Path Finding with Continuous Time via Satisfiability Modulo Theories. In Proceedings of the International Symposium on Combinatorial Search (SoCS), 200-202, 2021.
P. Surynek. Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering. In Proceedings of the International Symposium on Combinatorial Search (SoCS), 197-199, 2021.
P. Surynek. Conceptual Comparison of Compilation-Based Solvers for Multi-Agent Path Finding: MIP vs. SAT. In Proceedings of the Fourteenth International Symposium on Combinatorial Search (SoCS), 203-205, 2021.
M. Capek and P. Surynek. DPLL(MAPF): an Integration of Multi-Agent Path Finding and SAT Solving Technologies. In Proceedings of the International Symposium on Combinatorial Search (SoCS), 153-155, 2021.
M. Ivanova and P. Surynek. Adversarial Multi-Agent Path Finding is Intractable. In Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI), 481-486, 2021.
P. Surynek. Sparse Real-Time Decision Diagrams for Continuous Multi-Robot Path Planning. In Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI), 91-96, 2021.
K. Janovska and P. Surynek. Hierarchical Control of Swarms during Evacuation. In Proceedings of the International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KEOD), 61-73, 2021.
P. Surynek. Sparsification for Fast Optimal Multi-Robot Path Planning in Lazy Compilation Schemes. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 7931-7938, 2021.
Z. Ren, S. Rathinam and H. Choset. Multi-Objective Conflict-Based Search for Multi-Agent Path Finding. In Proceedings of the International Conference on Robotics and Automation (ICRA), 8786-8791, 2021.
Z. Ren, S. Rathinam and H. Choset. MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-Goal Sequencing and Path Finding. In Proceedings of the International Conference on Robotics and Automation (ICRA), 11560-11565, 2021.
Z. Ren, S. Rathinam and H. Choset. Subdimensional Expansion for Multi-Objective Multi-Agent Path Finding. IEEE Robotics and Automation Letters, 6, (4), 7153-7160, 2021.
Z. Ren, S. Rathinam and H. Choset. Loosely Synchronized Search for Multi-Agent Path Finding with Asynchronous Actions. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 9714-9719, 2021.
J. Chen, J. Li, C. Fan and B. Williams. Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 11237-11245, 2021.
D. Atzmon, S. Freiman, O. Epshtein, O. Shichman and A. Felner. Conflict-Free Multi-Agent Meeting. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 16-24, 2021.
Z. Chen, D. Harabor, J. Li and P. Stuckey. Symmetry Breaking for k-Robust Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 12267-12274, 2021.

2020

H. Ma. Target Assignment and Path Planning for Navigation Tasks with Teams of Agents. PhD thesis, Department of Computer Science, University of Southern California, Los Angeles (California), 2020.
E. Boyarski, A. Felner, D. Harabor, P. Stuckey, L. Cohen, J. Li and S. Koenig. Iterative-Deepening Conflict-Based Search. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), (in print), 2020.
G. Belov, W. Du, M. Garcia de la Banda, D. Harabor, S. Koenig and X. Wei. From Multi-Agent Pathfinding to 3D Pipe Routing. In Proceedings of the Symposium on Combinatorial Search (SoCS), (in print), 2020.
J. Li, G. Gange, D. Harabor, P. Stuckey, H. Ma and S. Koenig. New Techniques for Pairwise Symmetry Breaking in Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), (in print), 2020.
H. Zhang, J. Li, P. Surynek, S. Koenig and S. Kumar. Multi-Agent Path Finding with Mutex Propagation. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), (in print), 2020. Outstanding ICAPS Student Paper Award.
D. Atzmon, R. Stern, A. Felner, N. Sturtevant and S. Koenig. Probabilistic Robust Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), (in print), 2020.
J. Li, K. Sun, H. Ma, A. Felner, S. Kumar and S. Koenig. Moving Agents in Formation in Congested Environments. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), (in print), 2020.
S.-H. Chan, J. Li, D. Harabor, P. Stuckey, G. Gange, L. Cohen and S. Koenig. Nested ECBS for Bounded-Suboptimal Multi-Agent Path Finding. In Proceedings of the IJCAI Workshop on Multi-Agent Path Finding, 2020.
J. Li, A. Tinka, S. Kiesel, J. Durham, S. Kumar and S. Koenig. Lifelong Multi-Agent Path Finding in Large-Scale Warehouses. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), (in print), 2020.
P. Surynek, J. Li, H. Zhang, S. Kumar and S. Koenig. Mutex Propagation for SAT-Based Multi-Agent Path Finding. In Proceedings of the International Conference on Principles and Practice of Multi-Agent Systems (PRIMA), 2020.
O. Salzman and R. Stern. Research Challenges and Opportunities in Multi-Agent Path Finding and Multi-Agent Pickup and Delivery Problems. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1711-1715, 2020.
T. Walker, N. Sturtevant and A. Felner. Generalized and Sub-Optimal Bipartite Constraints for Conflict-Based Search. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 7277-7284, 2020.
D. Atzmon, R. Stern, A. Felner, G. Wagner, R. Bartak and N.-F. Zhou. Robust Multi-Agent Path Finding and Executing. Journal of Artificial Intelligence Research (JAIR), 67, 549-579, 2020.
D. Atzmon, Y. Zax, E. Kivity, L. Avitan, J. Morag and A. Felner. Generalizing Multi-Agent Path Finding for Heterogeneous Agents. In Proceedings of the Symposium on Combinatorial Search (SoCS), 101-105, 2020.
P. Surynek. On Satisfiability Modulo Theories in Continuous Multi-Agent Path Finding: Compilation-Based and Search-Based Approaches Compared. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 2020.
P. Surynek. Bounded Sub-Optimal Multi-Robot Path Planning Using Satisfiability Modulo Theory (SMT) Approach. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
J. Chudy, N. Popov and P. Surynek. Deployment of Multi-Agent Pathfinding on a Swarm of Physical Robots Centralized Control via Reflex-Based Behavior. In Proceedings of the International Conference on Robotics, Computer Vision and Intelligent Systems (ROBOVIS), 2020.
J. Chudy, N. Popov and P. Surynek. Emulating Centralized Control in Multi-Agent Pathfinding Using Decentralized Swarm of Reflex-Based Robots. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020.
S. Almagor and M. Lahijanian. Explainable Multi Agent Path Finding. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 34-42, 2020.
E. Lam and P. Le Bodic. New Valid Inequalities in Branch-and-Cut-and-Price for Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 184-192, 2020.
P. Surynek. Continuous Multi-Agent Path Finding via Satisfiability Modulo Theories (SMT). In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 399-420, 2020. Revised Selected Papers.

2019

J. Li, A. Felner, E. Boyarski, H. Ma and S. Koenig. Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), (in print), 2019.
R. Stern, N. Sturtevant, A. Felner, S. Koenig, H. Ma, T. Walker, J. Li, D. Atzmon, L. Cohen, S. Kumar, E. Boyarski and R. Bartak. Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks [Position Paper]. In Proceedings of the Symposium on Combinatorial Search (SoCS), (in print), 2019.
J. Li, H. Zhang, M. Gong, Z. Liang, W. Liu, Z. Tong, L. Yi, R. Morris, C. Pasareanu and S. Koenig. Scheduling and Airport Taxiway Path Planning under Uncertainty. In Proceedings of the AIAA Aviation Forum and Exposition (AIAA), (in print), 2019.
H. Ma, D. Harabor, P. Stuckey, J. Li and S. Koenig. Searching with Consistent Prioritization for Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), (in print), 2019.
H. Ma, W. Hoenig, S. Kumar, N. Ayanian and S. Koenig. Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), (in print), 2019.
J. Li, P. Surynek, A. Felner, H. Ma, S. Kumar and S. Koenig. Multi-Agent Path Finding for Large Agents. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), (in print), 2019.
J. Li, D. Harabor, P. Stuckey, H. Ma and S. Koenig. Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), (in print), 2019.
G. Sartoretti, J. Kerr, Y. Shi, G. Wagner, S. Kumar, S. Koenig and H. Choset. PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning. IEEE Robotics and Automation Letters, (in print), 2019.
M. Liu, H. Ma, J. Li and S. Koenig. Task and Path Planning for Multi-Agent Pickup and Delivery. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), (in print), 2019.
J. Wang, J. Li, H. Ma, S. Koenig and S. Kumar. A New Constraint Satisfaction Perspective on Multi-Agent Path Finding: Preliminary Results. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), (in print), 2019.
J. Li, D. Harabor, P. Stuckey, A. Felner, H. Ma and S. Koenig. Disjoint Splitting for Multi-Agent Path Finding with Conflict-Based Search. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), (in print), 2019.
W. Hoenig, S. Kiesel, A. Tinka, J. Durham and N. Ayanian. Persistent and Robust Execution of MAPF Schedules in Warehouses. IEEE Robotics and Automation Letters, 4, (2), 1125-1131, 2019.
D. Albani, W. Hoenig, N. Ayanian, D. Nardi, and V. Trianni. Summary: Distributed Task Assignment and Path Planning with Limited Communication for Robot Teams. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), (in print), 2019.
D. Atzmon, A. Diei and D. Rave. Multi-Train Path Finding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 125-129, 2019.
P. Surynek. Unifying Search-Based and Compilation-Based Approaches to Multi-Agent Path Finding through Satisfiability Modulo Theories. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1177-1183, 2019.
P. Surynek. Conflict Handling Framework in Generalized Multi-Agent Path Finding: Advantages and Shortcomings of Satisfiability Modulo Approach. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 192-203, 2019.
P. Surynek. Lazy Compilation of Variants of Multi-Robot Path Planning with Satisfiability Modulo Theory (SMT) Approach. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 3282-3287, 2019.
P. Surynek. Multi-Agent Path Finding with Generalized Conflicts: An Experimental Study. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 118-142, 2019.
E. Lam, P. Le Bodic, D. Harabor and P. Stuckey. Branch-and-Cut-and-Price for Multi-Agent Pathfinding. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), (in print), 2019.
G. Gange, D. Harabor and P. Stuckey. Lazy CBS: Implict Conflict-Based Search Using Lazy Clause Generation. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2019.
J. Svancara, M. Vlk, R. Stern, D. Atzmon and R. Bartak. Online Multi-Agent Pathfinding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), (in print), 2019.
J. Svancara and R. Bartak. Combining Strengths of Optimal Multi-Agent Path Finding Algorithms. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 226-231, 2019.
T. Walker and N. Sturtevant. Collision Detection for Agents in Multi-Agent Pathfinding. arXiv preprint arXiv:1908.09707, 2019.

2018

H. Ma, G. Wagner, A. Felner, J. Li, S. Kumar and S. Koenig. Multi-Agent Path Finding with Deadlines. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 417-423, 2018.
L. Cohen, M. Greco, H. Ma, C. Hernandez, A. Felner, S. Kumar and S. Koenig. Anytime Focal Search with Applications. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1434-1441, 2018.
D. Sigurdson, V. Bultiko, W. Yeoh, C. Hernandez and S. Koenig. Multi-Agent Pathfinding with Real-Time Heuristic Search. In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG), 1-8, 2018.
A. Felner, J. Li, E. Boyarski, H. Ma, L. Cohen, S. Kumar and S. Koenig. Adding Heuristics to Conflict-Based Search for Multi-Agent Path Finding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 83-87, 2018.
L. Cohen, S. Koenig, S. Kumar, G. Wagner, H. Choset, D. Chan and N. Sturtevant. Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1909-1911, 2018.
H. Ma, G. Wagner, A. Felner, J. Li, S. Kumar and S. Koenig. Multi-Agent Path Finding with Deadlines: Preliminary Results. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2004-2006, 2018.
W. Hoenig, J. Preiss, S. Kumar, G. Sukhatme and N. Ayanian. Trajectory Planning for Quadrotor Swarms. IEEE Transactions on Robotics, 34, (4), 856-869, 2018.
W. Hoenig, S. Kiesel, A. Tinka, J. Durham and N. Ayanian. Conflict-Based Search with Optimal Task Assignment. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 757-765, 2018.
R. Bartak, J. Svancara, V. Skopkova and D. Nohejl. Multi-Agent Path Finding on Real Robots: First Experience with Ozobots. In Proceedings of the Ibero-American Conference on Artificial Intelligence (IBERAMIA), 290-301, 2018. Best IBERAMIA Paper Award.
R. Bartak, J. Svancara and M. Vlk. A Scheduling-Based Approach to Multi-Agent Path Finding with Weighted and Capacitated Arcs. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 748-756 , 2018.
J. Svancara. Bringing Multi-Agent Path Finding Closer to Reality. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 5787-5788, 2018.
J. Svancara. Bringing Multi-Agent Path Finding Closer to Reality. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1784-1785, 2018.
A. Botea, D. Bonusi and P. Surynek. Solving Multi-Agent Path Finding on Strongly Biconnected Digraphs. Journal of Artificial Intelligence Research (JAIR), 62, (06/18), 273-314, 2018.
A. Botea, D. Bonusi and P. Surynek. Solving Multi-Agent Path Finding on Strongly Biconnected Digraphs. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 5563-5567, 2018.
T. Walker, N. Sturtevant and A. Felner. Extended Increasing Cost Tree Search for Non-Unit Cost Domains. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 534-540, 2018.

2017

H. Ma, W. Hoenig, L. Cohen, T. Uras, H. Xu, S. Kumar, N. Ayanian and S. Koenig. Overview: A Hierarchical Framework for Plan Generation and Execution in Multirobot Systems. IEEE Intelligent Systems, 32, (6), 6-12, 2017.
H. Ma, S. Kumar and S. Koenig. Multi-Agent Path Finding with Delay Probabilities. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 3605-3612, 2017.
H. Ma, J. Li, S. Kumar and S. Koenig. Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 837-845, 2017.
H. Ma and S. Koenig. AI Buzzwords Explained: Multi-Agent Path Finding (MAPF). AI Matters, 3, (3), 15-19, 2017.
P. Surynek, J. Svancara, A. Felner and E. Boyarski. Integration of Independence Detection into SAT-Based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 85-95, 2017.
P. Surynek, J. Svancara, A. Felner and E. Boyarski. Variants of Independence Detection in SAT-Based Optimal Multi-Agent Path Finding. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 116-136, 2017.
A. Felner, R. Stern, E. Shimony, M. Goldenberg, G. Sharon, N. Sturtevant, G. Wagner and P. Surynek. Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges. In Proceedings of the Symposium on Combinatorial Search (SoCS), 28-37, 2017.
D. Atzmon, A. Felner, R. Stern, G. Wagner, R. Bartak and N. Zhou. k-Robust Multi-Agent Path Finding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 157-158, 2017.
P. Surynek, A. Felner, R. Stern and E. Boyarski. Modifying Optimal SAT-Based Approach to Multi-Agent Path-Finding Problem to Suboptimal Variants. In Proceedings of the Symposium on Combinatorial Search (SoCS), 169-170, 2017.
R. Bartak, J. Svancara and M. Vlk. Scheduling Models for Multi-Agent Path Finding. In Proceedings of the Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA), 189-200, 2017.
J. Svancara and P. Surynek. New Flow-based Heuristic for Search Algorithms Solving Multi-Agent Path Finding. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 451-458, 2017.
R. Barak, N. Zhou, R. Stern, E. Boyarski and P. Surynek. Modeling and Solving the Multi-Agent Pathfinding Problem in Picat. In Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI), 959-966, 2017.
P. Surynek. Time-Expanded Graph-Based Propositional Encodings for Makespan-Optimal Solving of Cooperative Path Finding Problems. Annals of Mathematics and Artificial Intelligence, 81, (3-4), 329-375, 2017.
F. Xie, A. Botea and A. Kishimoto. A Scalable Approach to Chasing Multiple Moving Targets with Multiple Agents. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 4470-4476, 2017.
T. Walker, D. Chan and N. Sturtevant. Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 316-324, 2017.
V. Nguyen, P. Obermeier, T. Son, T. Schaub and W. Yeoh. Generalized Target Assignment and Path Finding Using Answer Set Programming. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1216-1223, 2017.

2016

H. Ma, C. Tovey, G. Sharon, S. Kumar and S. Koenig. Multi-Agent Path Finding with Payload Transfers and the Package-Exchange Robot-Routing Problem. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 3166-3173, 2016.
L. Cohen, T. Uras, S. Kumar, H. Xu, N. Ayanian and S. Koenig. Improved Solvers for Bounded-Suboptimal Multi-Agent Path Finding. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 3067-3074, 2016.
H. Ma and S. Koenig. Optimal Target Assignment and Path Finding for Teams of Agents. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1144-1152, 2016.
W. Hoenig, S. Kumar, L. Cohen, H. Ma, H. Xu, N. Ayanian and S. Koenig. Multi-Agent Path Finding with Kinematic Constraints. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 477-485, 2016. Best ICAPS Paper Award (Robotics Track).
W. Hoenig, S. Kumar, H. Ma, S. Koenig and N. Ayanian. Formation Change for Robot Groups in Occluded Environments. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 4836-4842, 2016.
H. Ma, S. Koenig, N. Ayanian, L. Cohen, W. Hoenig, S. Kumar, T. Uras, H. Xu, C. Tovey and G. Sharon. Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios. In Proceedings of the IJCAI-16 Workshop on Multi-Agent Path Finding, 2016.
P. Surynek, A. Felner, R. Stern and E. Boyarski. Boolean Satisfiability Approach to Optimal Multi-Agent Path Finding under the Sum of Costs Objective. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1435-1436, 2016.
P. Surynek, A. Felner, R. Stern and E. Boyarski. Efficient SAT Approach to Multi-Agent Path Finding Under the Sum of Costs Objective. In Proceedings of the European Conference on Artificial Intelligence (ECAI), 810-818, 2016.
P. Surynek, A. Felner, R. Stern and E. Boyarski. An Empirical Comparison of the Hardness of Multi-Agent Path Finding under the Makespan and the Sum of Costs Objectives. In Proceedings of the Symposium on Combinatorial Search (SoCS), 145-147, 2016.
P. Karkus, G. Wagner and H. Choset. Recursive Constraint Manifold Subsearch for Multirobot Path Planning with Cooperative Tasks. In Proceedings of the Symposium on Combinatorial Search (SoCS), 54-62, 2016.
G. Wagner, H. Choset and A. Siravuru. Multirobot Sequential Composition. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2081-2088, 2016.
P. Surynek and P. Michalik. The Joint Movement of Pebbles in Solving the (N^2-1)-Puzzle Suboptimally and its Applications in Rule-Based Cooperative Path-Finding. Autonomous Agents and Multi-Agent Systems, 31, (3), 715-763, 2016.

2015

L. Cohen, T. Uras and S. Koenig. Feasibility Study: Using Highways for Bounded-Suboptimal Multi-Agent Path Finding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2-8, 2015.
G. Sharon, R. Stern, A. Felner and N. Sturtevant. Conflict-Based Search for Optimal Multi-Agent Pathfinding. Artificial Intelligence, 219, 40-66, 2015.
E. Boyarski, A. Felner, G. Sharon and R. Stern. Don't Split, Try To Work It Out: Bypassing Conflicts in Multi-Agent Pathfinding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 47-51, 2015.
G. Wagner and H. Choset. Subdimensional Expansion for Multirobot Path Planning. Artificial Intelligence, 219, 1-24, 2015.
G. Wagner, J. Kim, K. Urban and H. Choset. Constraint Manifold Subsearch for Multirobot Path Planning with Cooperative Tasks. In Proceedings of the International Conference on Robotics and Automation (ICRA), 6094-6100, 2015.
P. Surynek. Reduced Time-Expansion Graphs for Solving Cooperative Path Finding Sub-Optimally. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1916-1922, 2015.

2014

M. Cirillo, T. Uras and S. Koenig. A Lattice-Based Approach to Multi-Robot Motion Planning for Non-Holonomic Vehicles. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 232-239, 2014.
M. Cirillo, F. Pecora, H. Andreasson, T. Uras and S. Koenig. Integrated Motion Planning and Coordination for Industrial Vehicles. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 463-471, 2014.
M. Barer, G. Sharon, R. Stern and A. Felner. Suboptimal Variants of the Conflict-Based Search Algorithm for the Multi-Agent Pathfinding Problem. In Proceedings of the European Conference on Artificial Intelligence (ECAI), 961-962, 2014.
P. Surynek. Compact Representations of Cooperative Path-Finding as SAT Based on Matchings in Bipartite Graphs. In Proceedings of the 26th International Conference on Tools with Artificial Intelligence (ICTAI), 875-882, 2014.
M. Ivanova and P. Surynek. Adversarial Cooperative Path-Finding: Complexity and Algorithms. In Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI), 75-82, 2014.
P. Surynek. On the Complexity of Optimal Parallel Cooperative Path-Finding. Fundamenta Informaticae, 137, (4), 517-548, 2014.
P. Surynek. Solving Abstract Cooperative Path-Finding in Densely Populated Environments. Computational Intelligence, 30, (2), 402-450, 2014.
C. Wilt and A. Botea. Spatially Distributed Multiagent Path Planning. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 332-340, 2014.

2013

G. Sharon, R. Stern, M. Goldenberg and A. Felner. The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding. 470-495, 2013.
Z. Bnaya, R. Stern, A. Felner, R. Zivan and S. Okamoto. Multi-Agent Path Finding for Self Interested Agents. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2013.
C. Ferner, G. Wagner and H. Choset. ODrM*: Optimal Multirobot Path Planning in Low Dimensional Search Spaces. In Proceedings of the International Conference on Robotics and Automation (ICRA), 3854-3859, 2013.

2012

P. Surynek. Towards Optimal Cooperative Path Planning in Hard Setups through Satisfiability Solving. In Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), 564-576, 2012.
M. Goldenberg, A. Felner, R. Stern, G. Sharon and J. Schaeffer. A* Variants for Optimal Multi-Agent Pathfinding. In AAAI-12 Workshop on Multi-Agent Pathfinding, 2012.
G. Sharon, R. Stern, A. Felner and N. Sturtevant. Meta-Agent Conflict-Based Search For Optimal Multi-Agent Path Finding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2012.
G. Sharon, R. Stern, A. Felner and N. Sturtevant. Conflict-Based Search for Optimal Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2012.
A. Botea, D. Harabor and K. Wang. Towards Search-Free Multiagent Pathfinding. In Proceedings of the AAAI-12 Workshop on Multiagent Pathfinding, 2012.
G. Wagner, M. Kang and H. Choset. Probabilistic Path Planning for Multiple Robots with Subdimensional Expansion. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2886-2892, 2012.
G. Wagner, H. Choset and N. Ayanian. Subdimensional Expansion and Optimal Task Reassignment. In Proceedings of the Symposium on Combinatorial Search (SoCS), 177-178, 2012.

2011

G. Sharon, R. Stern, A. Felner and N. Sturtevant. The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 662-667, 2011.
G. Sharon, R. Stern, M. Goldenberg and A. Felner. Pruning Techniques for the Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2011.
G. Wagner and H. Choset. M*: A Complete Multirobot Path Planning Algorithm with Performance Bounds. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 3260-3267, 2011.
C. Wang and A. Botea. MAPP: A Scalable Multi-Agent Path Planning Algorithm with Tractability and Completeness Guarantees. 55-90, 2011.
C. Wang, A. Botea and P. Kilby. On Improving the Quality of Solutions in Large-Scale Cooperative Multi-Agent Pathfinding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 2011.
C. Wang, A. Botea and P. Kilby. Solution Quality Improvements for Massively Multi-Agent Pathfinding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 1824-1825, 2011.
M. Khorshid, R. Holte and N. Sturtevant. A Polynomial-Time Algorithm for Non-Optimal Multi-Agent Pathfinding. In Proceedings of the Symposium on Combinatorial Search (SoCS), 76-83, 2011.

2010

C. Wang and A. Botea. Scalable Multi-Agent Pathfinding on Grid Maps with Tractability and Completeness Guarantees. In Proceedings of the European Conference on Artificial Intelligence (ECAI), 977-978, 2010.

2009

P. Surynek. A Novel Approach to Path Planning for Multiple Robots in Bi-Connected Graphs. In Proceedings of the International Conference on Robotics and Automation (ICRA), 3613-3619, 2009.
C. Wang and A. Botea. Tractable Multi-Agent Path Planning on Grid Maps. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1870-1875, 2009.

2008

C. Wang and A. Botea. Fast and Memory-Efficient Multi-Agent Pathfinding. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 380-387, 2008.
M. Jansen and N. Sturtevant. Direction Maps for Cooperative Pathfinding. In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 185-190, 2008.
M. Jansen and N. Sturtevant. A New Approach to Cooperative Pathfinding. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1401-1404, 2008.

2006

N. Sturtevant and M. Buro. Improving Collaborative Pathfinding using Map Abstraction. In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 80-85, 2006.