{"type":"ScholarlyArticle","title":"Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding","authors":[{"name":"Keisuke Okumura","slug":"keisuke-okumura","given":"Keisuke","family":"Okumura","affiliation":"National Institute of Advanced Industrial Science and Technology (AIST ); University of Cambridge"}],"abstract":"This study extends the recently-developed LaCAM algorithm for multi-agent pathfinding (MAPF). LaCAM is a sub-optimal search-based algorithm that uses lazy successor generation to dramatically reduce the planning effort. We present two enhancements. First, we propose its anytime version, called LaCAM*, which eventually converges to optima, provided that solution costs are accumulated transition costs. Second, we improve the successor generation to quickly obtain initial solutions. Exhaustive experiments demonstrate their utility. For instance, LaCAM* sub-optimally solved 99% of the instances retrieved from the MAPF benchmark, where the number of agents varied up to a thousand, within ten seconds on a standard desktop PC, while ensuring eventual convergence to optima; developing a new horizon of MAPF algorithms.","doi":"10.24963/ijcai.2023/28","url":"https://ijcai.org/proceedings/2023/28","pdf":"https://ijcai.org/proceedings/2023/0028.pdf","markdown":"https://ijcai.org/proceedings/2023/28.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/28","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":28,"pages":{"first":243,"last":251},"keywords":["Planning and Scheduling: PS: Distributed and multi-agent planning","Planning and Scheduling: PS: Planning algorithms","Agent-based and Multi-agent Systems: MAS: Multi-agent planning","Robotics: ROB: Motion and path planning"],"videos":[],"references":[{"position":1,"raw":"[Andreychuk and Yakovlev, 2018] Anton Andreychuk and Konstantin Yakovlev. Two techniques that enhance the performance of multi-robot prioritized path planning. In Proc. Int. Joint Conf. on Autonomous Agents & Multiagent Systems (AAMAS), 2018.","title":"Two techniques that enhance the performance of multi-robot prioritized path planning","authors":"Yakovlev Andreychuk, Anton Andreychuk, Konstantin Yakovlev","year":"2018","venue":"Proc. Int. Joint Conf. on Autonomous Agents & Multiagent Systems (AAMAS)","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Cohen et al., 2018a] Liron Cohen, Matias Greco, Hang Ma, Carlos Hernández, Ariel Felner, TK Satish Kumar, and Sven Koenig. Anytime focal search with applications. In Proc Int. Joint Conf. on Artificial Intelligence (IJCAI), 2018.","title":"Anytime focal search with applications","authors":"Cohen","year":"2018","venue":"Proc Int. Joint Conf. on Artificial Intelligence (IJCAI)","doi":null,"url":null,"internal_url":"/proceedings/2018/199"},{"position":3,"raw":"[Cohen et al., 2018b] Liron Cohen, Glenn Wagner, David Chan, Howie Choset, Nathan Sturtevant, Sven Koenig, and TK Satish Kumar. Rapid randomized restarts for multi- agent path finding solvers. In Proc. Annu. Symp. on Com- binatorial Search (SOCS), 2018.","title":"Rapid randomized restarts for multiagent path finding solvers","authors":"Cohen","year":"2018","venue":"Proc. Annu. Symp. on Combinatorial Search (SOCS)","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[De Wilde et al., 2014] Boris De Wilde, Adriaan W Ter Mors, and Cees Witteveen. Push and rotate: a complete multi-agent pathfinding algorithm. Journal of Artificial Intelligence Research (JAIR), 2014.","title":"Push and rotate: a complete multi-agent pathfinding algorithm","authors":"Boris De Wilde, Adriaan W Ter Mors, Cees Witteveen","year":"2014","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Goldenberg et al., 2014] Meir Goldenberg, Ariel Felner, Roni Stern, Guni Sharon, Nathan Sturtevant, Robert Holte, and Jonathan Schaeffer. Enhanced partial expansion A * . Journal of Artificial Intelligence Research (JAIR), 2014.","title":"Enhanced partial expansion A","authors":"Meir Goldenberg, Ariel Felner, Roni Stern, Guni Sharon, Nathan Sturtevant, Robert Holte, Jonathan Schaeffer","year":"2014","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Hart et al., 1968] Peter E Hart, Nils J Nilsson, and Bertram Raphael. A formal basis for the heuristic determination of minimum cost paths. IEEE transactions on Systems Sci- ence and Cybernetics, 1968.","title":"A formal basis for the heuristic determination of minimum cost paths","authors":"Nils J Peter E Hart, Bertram Nilsson, Raphael","year":"1968","venue":"IEEE transactions on Systems Science and Cybernetics","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Karaman and Frazzoli, 2011] Sertac Karaman and Emilio Frazzoli. Sampling-based algorithms for optimal mo- tion planning. International Journal of Robotics Research (IJRR), 2011.","title":"Sampling-based algorithms for optimal motion planning","authors":"Frazzoli Karaman, Sertac Karaman, Emilio Frazzoli","year":"2011","venue":"International Journal of Robotics Research","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Kautz et al., 2002] Henry Kautz, Eric Horvitz, Yongshao Ruan, Carla Gomes, and Bart Selman. Dynamic restart policies. In Proc. AAAI Conf. on Artificial Intelligence (AAAI), 2002.","title":"Dynamic restart policies","authors":"Henry Kautz, Eric Horvitz, Yongshao Ruan, Carla Gomes, Bart Selman","year":"2002","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Lam et al., 2022] Edward Lam, Pierre Le Bodic, Daniel Harabor, and Peter J Stuckey. Branch-and-cut-and-price for multi-agent path finding. Computers & Operations Re- search (COR), 2022.","title":"Branch-and-cut-and-price for multi-agent path finding","authors":"Edward Lam, Pierre Le Bodic, Daniel Harabor, Peter J Stuckey","year":"2022","venue":"Computers & Operations Research","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Li et al., 2021a] Jiaoyang Li, Zhe Chen, Daniel Harabor, P Stuckey, and Sven Koenig. Anytime multi-agent path finding via large neighborhood search. In Proc Int. Joint Conf. on Artificial Intelligence (IJCAI), 2021.","title":"Anytime multi-agent path finding via large neighborhood search","authors":"Li","year":"2021","venue":"Proc Int. Joint Conf. on Artificial Intelligence (IJCAI)","doi":null,"url":null,"internal_url":"/proceedings/2021/568"},{"position":11,"raw":"[Li et al., 2021b] Jiaoyang Li, Wheeler Ruml, and Sven Koenig. Eecbs: A bounded-suboptimal search for multi- agent path finding. In Proc. AAAI Conf. on Artificial Intel- ligence (AAAI), 2021.","title":"Eecbs: A bounded-suboptimal search for multiagent path finding","authors":"Li","year":"2021","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Li et al., 2022] Jiaoyang Li, Zhe Chen, Daniel Harabor, Pe- ter J Stuckey, and Sven Koenig. Mapf-lns2: Fast repair- ing for multi-agent path finding via large neighborhood search. In Proc. AAAI Conf. on Artificial Intelligence (AAAI), 2022.","title":"Mapf-lns2: Fast repairing for multi-agent path finding via large neighborhood search","authors":"Jiaoyang Li, Zhe Chen, Daniel Harabor, Peter J Stuckey, Sven Koenig","year":"2022","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Luna and Bekris, 2011] Ryan Luna and Kostas E Bekris. Push and swap: Fast cooperative path-finding with com- pleteness guarantees. In Proc Int. Joint Conf. on Artificial Intelligence (IJCAI), 2011.","title":"Push and swap: Fast cooperative path-finding with completeness guarantees","authors":"Ryan Luna, Kostas E Bekris","year":"2011","venue":"Proc Int. Joint Conf. on Artificial Intelligence (IJCAI)","doi":null,"url":null,"internal_url":"/proceedings/2011/59"},{"position":14,"raw":"[Okumura and Défago, 2023] Keisuke Okumura and Xavier Défago. Quick multi-robot motion planning by combining sampling and search. In Proc Int. Joint Conf. on Artificial Intelligence (IJCAI), 2023.","title":"Quick multi-robot motion planning by combining sampling and search","authors":"Keisuke Okumura, Xavier Défago","year":"2023","venue":"Proc Int. Joint Conf. on Artificial Intelligence (IJCAI)","doi":null,"url":null,"internal_url":"/proceedings/2023/29"},{"position":15,"raw":"[Okumura et al., 2021] Keisuke Okumura, Yasumasa Tamura, and Xavier Défago. Iterative refinement for real-time multi-robot path planning. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2021.","title":"Iterative refinement for real-time multi-robot path planning","authors":"Keisuke Okumura, Yasumasa Tamura, Xavier Défago","year":"2021","venue":"Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Okumura et al., 2022] Keisuke Okumura, Manao Machida, Xavier Défago, and Yasumasa Tamura. Priority inheri- tance with backtracking for iterative multi-agent path find- ing. Artificial Intelligence (AIJ), 2022.","title":"Priority inheritance with backtracking for iterative multi-agent path finding","authors":"Keisuke Okumura, Manao Machida, Xavier Défago, Yasumasa Tamura","year":"2022","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2019/76"},{"position":17,"raw":"[Okumura, 2023] Keisuke Okumura. Lacam: Search-based algorithm for quick multi-agent pathfinding. In Proc. AAAI Conf. on Artificial Intelligence (AAAI), 2023.","title":"Lacam: Search-based algorithm for quick multi-agent pathfinding","authors":"Keisuke Okumura","year":"2023","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Sharon et al., 2015] Guni Sharon, Roni Stern, Ariel Felner, and Nathan R Sturtevant. Conflict-based search for opti- mal multi-agent pathfinding. Artificial Intelligence (AIJ), 2015.","title":"Conflict-based search for optimal multi-agent pathfinding","authors":"Guni Sharon, Roni Stern, Ariel Felner, Nathan R Sturtevant","year":"2015","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Shome et al., 2020] Rahul Shome, Kiril Solovey, Andrew Dobson, Dan Halperin, and Kostas E Bekris. drrt * : Scal- able and informed asymptotically-optimal multi-robot mo- tion planning. Autonomous Robots (AURO), 2020.","title":"drrt * : Scalable and informed asymptotically-optimal multi-robot motion planning","authors":"Rahul Shome, Kiril Solovey, Andrew Dobson, Dan Halperin, Kostas E Bekris","year":"2020","venue":"Autonomous Robots","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Silver, 2005] David Silver. Cooperative pathfinding. In Proc. AAAI Conf. on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2005.","title":"Cooperative pathfinding","authors":"David Silver","year":"2005","venue":"Proc. AAAI Conf. on Artificial Intelligence and Interactive Digital Entertainment (AIIDE)","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Standley and Korf, 2011] Trevor Standley and Richard Korf. Complete algorithms for cooperative pathfinding problems. In Proc Int. Joint Conf. on Artificial Intelligence (IJCAI), 2011.","title":"Complete algorithms for cooperative pathfinding problems","authors":"Korf Standley, Trevor Standley, Richard Korf","year":"2011","venue":"Proc Int. Joint Conf. on Artificial Intelligence (IJCAI)","doi":null,"url":null,"internal_url":"/proceedings/2011/118"},{"position":22,"raw":"[Standley, 2010] Trevor Scott Standley. Finding optimal so- lutions to cooperative pathfinding problems. In Proc. AAAI Conf. on Artificial Intelligence (AAAI), 2010.","title":"Finding optimal solutions to cooperative pathfinding problems","authors":"Trevor Scott, Standley","year":"2010","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Stern et al., 2019] Roni Stern, Nathan Sturtevant, Ariel Fel- ner, Sven Koenig, Hang Ma, Thayne Walker, Jiaoyang Li, Dor Atzmon, Liron Cohen, TK Kumar, et al. Multi- agent pathfinding: Definitions, variants, and benchmarks. In Proc. Annu. Symp. on Combinatorial Search (SOCS), 2019.","title":"Multiagent pathfinding: Definitions, variants, and benchmarks","authors":"Roni Stern, Nathan Sturtevant, Ariel Felner, Sven Koenig, Hang Ma, Thayne Walker, Jiaoyang Li, Dor Atzmon, Liron Cohen, Kumar","year":"2019","venue":"Proc. Annu. Symp. on Combinatorial Search (SOCS)","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Surynek, 2013] Pavel Surynek. Redundancy elimination in highly parallel solutions of motion coordination prob- lems. International Journal on Artificial Intelligence Tools (IJAIT), 2013.","title":"Redundancy elimination in highly parallel solutions of motion coordination problems","authors":"Pavel Surynek, Surynek","year":"2013","venue":"International Journal on Artificial Intelligence Tools","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Vedder and Biswas, 2021] Kyle Vedder and Joydeep Biswas. X * : Anytime multi-agent path finding for sparse domains using window-based iterative repairs. Artificial Intelligence (AIJ), 2021.","title":"X * : Anytime multi-agent path finding for sparse domains using window-based iterative repairs","authors":"Kyle Vedder, Joydeep Biswas","year":"2021","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Wagner and Choset, 2015] Glenn Wagner and Howie Choset. Subdimensional expansion for multirobot path planning. Artificial Intelligence (AIJ), 2015.","title":"Subdimensional expansion for multirobot path planning","authors":"Choset ; Wagner, Glenn Wagner, Howie Choset","year":"2015","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Wurman et al., 2008] Peter R Wurman, Raffaello D'Andrea, and Mick Mountz. Coordinating hun- dreds of cooperative, autonomous vehicles in warehouses. AI magazine, 2008.","title":"Coordinating hundreds of cooperative, autonomous vehicles in warehouses","authors":"Peter R Wurman, D' Raffaello, Mick Andrea, Mountz","year":"2008","venue":"AI magazine","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Yu and LaValle, 2013] Jingjin Yu and Steven M LaValle. Structure and intractability of optimal multi-robot path planning on graphs. In Proc. AAAI Conf. on Artificial In- telligence (AAAI), 2013.","title":"Structure and intractability of optimal multi-robot path planning on graphs","authors":"Lavalle ; ] Jingjin Yu, Steven M Yu, Lavalle","year":"2013","venue":"Proc. AAAI Conf. on Artificial Intelligence (AAAI)","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}