{"title":"Search Algorithms for Multi-Agent Teamwise Cooperative Path Finding [Extended Abstract]","authors":"Z. Ren, S. Rathinam, H. Choset","doi":"10.1609/socs.v16i1.27304","DOIUrl":null,"url":null,"abstract":"Multi-Agent Path Finding (MA-PF) finds collision-free paths for multiple agents from their respective start to goal locations. This paper investigates a generalization of MA-PF called Multi-Agent Teamwise Cooperative Path Finding (MA-TC-PF), where agents are grouped as multiple teams and each team has its own objective to minimize. In general, there is more than one team, and MA-TC-PF is thus a multi-objective planning problem with the goal of finding the entire Pareto-optimal front that represents all possible trade-offs among the objectives of the teams. We show that the existing CBS and M* for MA-PF can be modified to solve MA-TC-PF, which is verified with tests. We discuss the conditions under which the proposed algorithms are complete and are guaranteed to find the Pareto-optimal front for MA-TC-PF.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium on Combinatorial Search","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1609/socs.v16i1.27304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Multi-Agent Path Finding (MA-PF) finds collision-free paths for multiple agents from their respective start to goal locations. This paper investigates a generalization of MA-PF called Multi-Agent Teamwise Cooperative Path Finding (MA-TC-PF), where agents are grouped as multiple teams and each team has its own objective to minimize. In general, there is more than one team, and MA-TC-PF is thus a multi-objective planning problem with the goal of finding the entire Pareto-optimal front that represents all possible trade-offs among the objectives of the teams. We show that the existing CBS and M* for MA-PF can be modified to solve MA-TC-PF, which is verified with tests. We discuss the conditions under which the proposed algorithms are complete and are guaranteed to find the Pareto-optimal front for MA-TC-PF.