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Generalized Longest Simple Path Problems: Speeding up Search Using SPQR Trees 广义最长简单路径问题：利用 SPQR 树加速搜索
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31539
Gal Dahan, Itay Tabib, S. E. Shimony, Yefim Dinitz
{"title":"Generalized Longest Simple Path Problems: Speeding up Search Using SPQR Trees","authors":"Gal Dahan, Itay Tabib, S. E. Shimony, Yefim Dinitz","doi":"10.1609/socs.v17i1.31539","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31539","url":null,"abstract":"The longest simple path and snake-in-a-box are combinatorial search problems of considerable research interest. Recent work has recast\u0000these problems as special cases of a generalized longest simple path (GLSP) framework, and showed how to generate improved search heuristics for them.\u0000The greatest reduction in search effort was based on SPQR tree rules,\u0000but it was\u0000posed as an open problem how to use them optimally. Unrelated to search, a theoretical paper on the existence of simple cycles that include three given edges answers such queries in linear time with SPQR trees. These theoretical results\u0000are utilized in this paper to develop advanced heuristics and search partitioning for GLSP.\u0000Empirical results on grid-based graphs show that these heuristics can result in orders of magnitude reduction in the number of expansions, as well as significantly reduced overall runtime in most cases.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"59 14","pages":"28-36"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141274904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fools Rush in Where Angels Fear to Tread in Multi-Goal CBS 多目标 CBS 中天使不敢涉足的地方，愚者贸然闯入
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31566
Grigorios Mouratidis, Bernhard Nebel, Sven Koenig
{"title":"Fools Rush in Where Angels Fear to Tread in Multi-Goal CBS","authors":"Grigorios Mouratidis, Bernhard Nebel, Sven Koenig","doi":"10.1609/socs.v17i1.31566","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31566","url":null,"abstract":"Research on multi-agent pathfinding (MAPF) has recently shifted towards problem variants that are closer to actual applications. Such variants often include the assignment of multiple goals to agents. To solve them, researchers have extended the Conflict Based Search (CBS) algorithm to multiple goals. This extension might look straightforward at first sight but it is tricky and this has already led to the development of algorithms that despite claiming to be optimal, return suboptimal solutions for some MAPF instances. In this paper, we provide a detailed analysis of the issue to raise awareness among the search community so that this mistake will not be perpetuated. Furthermore, a first evaluation against an optimal implementation is conducted which shows why this issue might have been difficult to spot. In only one of the randomly generated instances, the suboptimal behavior emerged.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"16 6","pages":"243-251"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141274280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Avoiding Node Re-Expansions Can Break Symmetry Breaking 避免节点重新扩展可打破对称性破坏
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31538
Mark Carlson, Daniel D. Harabor, P. Stuckey
{"title":"Avoiding Node Re-Expansions Can Break Symmetry Breaking","authors":"Mark Carlson, Daniel D. Harabor, P. Stuckey","doi":"10.1609/socs.v17i1.31538","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31538","url":null,"abstract":"Symmetry breaking and weighted-suboptimal search are two popular speed up techniques used in pathfinding search.\u0000It is a commonly held assumption that they are orthogonal and easily combined.\u0000In this paper we illustrate that this is not necessarily the case when combining a number of symmetry breaking methods, based on Jump Point Search, with Weighted A*, a bounded suboptimal search approach which does not require node re-expansions.\u0000Surprisingly, the combination of these two methods can cause search to fail, finding no path to a target node when clearly such paths exist.\u0000We demonstrate this phenomena and show how we can modify the combination to always succeed with low overhead.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"57 4","pages":"20-27"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ITA-ECBS: A Bounded-Suboptimal Algorithm for Combined Target-Assignment and Path-Finding Problem ITA-ECBS：目标指派和路径寻找组合问题的有界次优算法
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31551
Yimin Tang, Sven Koenig, Jiaoyang Li
{"title":"ITA-ECBS: A Bounded-Suboptimal Algorithm for Combined Target-Assignment and Path-Finding Problem","authors":"Yimin Tang, Sven Koenig, Jiaoyang Li","doi":"10.1609/socs.v17i1.31551","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31551","url":null,"abstract":"Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, plays a critical role in many applications. Sometimes, assigning a target to each agent also presents a challenge. The Combined Target-Assignment and Path-Finding (TAPF) problem, a variant of MAPF, requires one to simultaneously assign targets to agents and plan collision-free paths for agents. Several algorithms, including CBM, CBS-TA, and ITA-CBS, optimally solve the TAPF problem, with ITA-CBS being the leading algorithm for minimizing flowtime. However, the only existing bounded-suboptimal algorithm ECBS-TA is derived from CBS-TA rather than ITA-CBS. So, it faces the same issues as CBS-TA, such as searching through multiple constraint trees and spending too much time on finding the next-best target assignment. We introduce ITA-ECBS, the first bounded-suboptimal variant of ITA-CBS. Transforming ITA-CBS to its bounded-suboptimal variant is challenging because different constraint tree nodes can have different assignments of targets to agents. ITA-ECBS uses focal search to achieve efficiency and determines target assignments based on a new lower bound matrix. We show that it runs faster than ECBS-TA in 87.42% of 54,033 test cases.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"6 3","pages":"134-142"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141280875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Non-Refined Abstractions in Counterexample Guided Abstraction Refinement for Multi-Agent Path Finding (Extended Abstract) 用于多代理路径查找的反例引导抽象细化中的非定义抽象（扩展摘要）
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31584
Pavel Surynek
{"title":"Non-Refined Abstractions in Counterexample Guided Abstraction Refinement for Multi-Agent Path Finding (Extended Abstract)","authors":"Pavel Surynek","doi":"10.1609/socs.v17i1.31584","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31584","url":null,"abstract":"Counterexample guided abstraction refinement (CEGAR) represents a powerful symbolic technique for various tasks such as model checking and reachability analysis. Recently, CEGAR combined with Boolean satisfiability (SAT) has been applied for multi-agent path finding (MAPF), a problem where the task is to navigate agents from their start positions to given individual goal positions so that agents do not collide with each other. The recent CEGAR approach used the initial abstraction of the MAPF problem where collisions between agents were omitted and were eliminated in subsequent abstraction refinements. We propose in this work a novel CEGAR-style solver for MAPF based on SAT in which some abstractions are deliberately left non-refined. This adds the necessity to post-process the answers obtained from the underlying SAT solver as these answers slightly differ from the correct MAPF solutions. Non-refining however yields order-of-magnitude smaller SAT encodings than those of the previous approach and speeds up the overall solving process.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"10 4","pages":"287-288"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141281386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-agent Motion Planning through Stationary State Search (Extended Abstract) 通过静态搜索进行多代理运动规划（扩展摘要）
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31589
Jingtian Yan, Jiaoyang Li
{"title":"Multi-agent Motion Planning through Stationary State Search (Extended Abstract)","authors":"Jingtian Yan, Jiaoyang Li","doi":"10.1609/socs.v17i1.31589","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31589","url":null,"abstract":"Multi-Agent Motion Planning (MAMP) finds various real-world applications in fields such as traffic management, airport operations, and warehouse automation. This work primarily focuses on its application in large-scale automated warehouses. Recently, Multi-Agent Path-Finding (MAPF) methods have achieved great success in finding collision-free paths for hundreds of agents within automated warehouse settings. However, these methods often use a simplified assumption about the robot dynamics, which limits their practicality and realism. In this paper, we introduce a three-level MAMP framework called PSS which incorporates the kinodynamic constraints of the robots. PSS combines MAPF-based methods with Stationary Safe Interval Path Planner (SSIPP) to generate high-quality kinodynamically-feasible solutions. Our method shows significant improvements in terms of scalability and solution quality compared to existing methods.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"61 21","pages":"297-298"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Prioritised Planning with Guarantees 有保障的优先规划
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31545
Jonathan Morag, Yue Zhang, Daniel Koyfman, Zhe Chen, Ariel Felner, Daniel D. Harabor, Roni Stern
{"title":"Prioritised Planning with Guarantees","authors":"Jonathan Morag, Yue Zhang, Daniel Koyfman, Zhe Chen, Ariel Felner, Daniel D. Harabor, Roni Stern","doi":"10.1609/socs.v17i1.31545","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31545","url":null,"abstract":"Prioritised Planning (PP) is a family of incomplete and sub-optimal algorithms for multi-agent and multi-robot navigation. In PP, agents compute collision-free paths in a fixed order, one at a time. Although fast and usually effective, PP can still fail, leaving users without explanation or recourse. In this work, we give a theoretical and empirical basis for better understanding the underlying problem solved by PP, which we call Priority Constrained MAPF (PC-MAPF). We first investigate the complexity of PC-MAPF and show that the decision problem is NP-hard. We then develop Priority Constrained Search (PCS), a new algorithm that is both complete and optimal with respect to a fixed priority ordering. We experiment with PCS in a range of settings, including comparisons with existing PP baselines, and we give first-known results for optimal PC-MAPF on a popular benchmark set.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"19 11","pages":"82-90"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141279092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On Parallel External-Memory Bidirectional Search (Extended Abstract) 论并行外部内存双向搜索（扩展摘要）
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31582
Lior Siag, Shahaf S. Shperberg, Ariel Felner, Nathan R Sturtevant
{"title":"On Parallel External-Memory Bidirectional Search (Extended Abstract)","authors":"Lior Siag, Shahaf S. Shperberg, Ariel Felner, Nathan R Sturtevant","doi":"10.1609/socs.v17i1.31582","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31582","url":null,"abstract":"Parallelization and External Memory (PEM) techniques significantly enhance the capabilities of search algorithms for solving large-scale problems. While previous research on PEM has primarily centered on unidirectional algorithms, this work presents a versatile PEM framework that integrates both uni- and bi-directional best-first search algorithms.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"35 2","pages":"283-284"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lazy Evaluation of Negative Preconditions in Planning Domains (Extended Abstract) 规划域中否定先决条件的懒惰评估（扩展摘要）
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31576
Santiago Franco, Jamie O. Roberts, Sara Bernardini
{"title":"Lazy Evaluation of Negative Preconditions in Planning Domains (Extended Abstract)","authors":"Santiago Franco, Jamie O. Roberts, Sara Bernardini","doi":"10.1609/socs.v17i1.31576","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31576","url":null,"abstract":"AI planning technology faces performance issues with large-scale problems with negative preconditions. In this extended abstract, we show how to leverage the power of the Finite Domain Representation (FDR) used by the popular Fast Downward planner for such domains. FDR improves scalability thanks to its use of multi-valued state variables. However, it scales poorly when dealing with negative preconditions. We propose an alternative hybrid approach that evaluates negative preconditions on the fly during search but only when strictly needed. This is compared to the traditional use of domain-specific PDDL bookmark predicates, increasing memory usage, and automated transformations to Positive Normal Form, further escalating memory consumption.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"54 16","pages":"271-272"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141279750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bi-Criteria Diverse Plan Selection via Beam Search Approximation 通过光束搜索近似法进行双标准多样化计划选择
Symposium on Combinatorial Search Pub Date : 2024-06-01 DOI: 10.1609/socs.v17i1.31557
Shanhe Zhong, Pouya Shati, Eldan Cohen
{"title":"Bi-Criteria Diverse Plan Selection via Beam Search Approximation","authors":"Shanhe Zhong, Pouya Shati, Eldan Cohen","doi":"10.1609/socs.v17i1.31557","DOIUrl":"https://doi.org/10.1609/socs.v17i1.31557","url":null,"abstract":"Recent work on diverse planning has focused on a two-step setting where the first step consists of generating a large number of plans, and the second step consists of selecting a subset of plans that maximizes diversity. For the second step, previous work has focused on solving a combinatorial optimization problem for diverse subset selection that can be approximated using greedy search. In this work, we propose a flexible, bi-criteria framework for diverse plan selection. Our framework consists of optimizing both quality and diversity, generalizing previous work and providing flexibility to prioritize one objective over the other. We consider two quality and two diversity measures and show that greedy search guarantees an approximation with a constant ratio for certain configurations based on established results in the literature. To allow users to trade off additional computation for better solutions, we introduce a beam search approximation that generalizes the greedy search, and we provide approximation guarantees on the obtained solutions. Finally, we conduct extensive experiments that show that: (1) our flexible bi-criteria framework allows us to obtain solutions of better quality while still maintaining a high degree of diversity; (2) our beam search approximation obtains significant improvement in performance over greedy search and, for a large number of instances, is able to generate solutions that are equal to or better than those obtained by an exact MIP solver with a significantly higher runtime limit.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"23 9","pages":"188-196"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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