{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:37:26Z","timestamp":1761176246119,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Effective coordination in multi-agent systems remains challenging in dynamic and partially observable environments, where agents must reason over evolving interdependencies and limited communication bandwidth. We propose ADAPT, a unified framework for multi-agent coordination that integrates message compression, dependency estimation, and a novel auction-based dynamic prioritization mechanism. In ADAPT, agents exchange compact messages and compute dependency scores to determine how much their behavior depends on others. A distributed auction protocol then assigns priority positions, guiding autoregressive decision-making in a manner aligned with inter-agent influence. This enables flexible, influence-aware coordination without centralized control or extensive communication rounds. Experiments on SMACv2 and GRF show that ADAPT achieves higher win rates, faster convergence, and lower communication cost compared to state-of-the-art baselines. Further analyses confirm its scalability to large teams, compatibility with value decomposition, and runtime efficiency. These results show that ADAPT enables scalable, efficient, and modular multi-agent coordination.<\/jats:p>","DOI":"10.3233\/faia251227","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:55:14Z","timestamp":1761126914000},"source":"Crossref","is-referenced-by-count":0,"title":["ADAPT: Auction-Based Dynamic Prioritization for Multi-Agent Coordination"],"prefix":"10.3233","author":[{"given":"Zaipeng","family":"Xie","sequence":"first","affiliation":[{"name":"Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing, China"},{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China"}]},{"given":"Chentai","family":"Qiao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China"}]},{"given":"Nuo","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China"}]},{"given":"Yiming","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251227","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:55:14Z","timestamp":1761126914000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251227"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251227","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}