{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T05:28:27Z","timestamp":1769578107528,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819980789","type":"print"},{"value":"9789819980796","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T00:00:00Z","timestamp":1699920000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T00:00:00Z","timestamp":1699920000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-8079-6_25","type":"book-chapter","created":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T16:02:42Z","timestamp":1699891362000},"page":"319-331","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["SORA: Improving Multi-agent Cooperation with\u00a0a\u00a0Soft Role Assignment Mechanism"],"prefix":"10.1007","author":[{"given":"Guangchong","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiwei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zeren","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoliang","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,14]]},"reference":[{"key":"25_CR1","unstructured":"Berner, C., et al.: Dota 2 with large scale deep reinforcement learning. arXiv preprint arXiv:1912.06680 (2019)"},{"issue":"6","key":"25_CR2","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1177\/0278364913483345","volume":"32","author":"J Capitan","year":"2013","unstructured":"Capitan, J., Spaan, M.T., Merino, L., Ollero, A.: Decentralized multi-robot cooperation with auctioned POMDPs. Int. J. Robot. Res. 32(6), 650\u2013671 (2013)","journal-title":"Int. J. Robot. Res."},{"key":"25_CR3","unstructured":"Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)"},{"key":"25_CR4","unstructured":"Ha, D., Dai, A., Le, Q.V.: Hypernetworks. arXiv preprint arXiv:1609.09106 (2016)"},{"key":"25_CR5","unstructured":"Hausknecht, M., Stone, P.: Deep recurrent Q-learning for partially observable MDPs. In: 2015 AAAI Fall Symposium Series (2015)"},{"key":"25_CR6","unstructured":"Hu, S., Xie, C., Liang, X., Chang, X.: Policy diagnosis via measuring role diversity in cooperative multi-agent RL. In: International Conference on Machine Learning, pp. 9041\u20139071. PMLR (2022)"},{"key":"25_CR7","doi-asserted-by":"crossref","unstructured":"Kurach, K., et al.: Google research football: a novel reinforcement learning environment (2020)","DOI":"10.1609\/aaai.v34i04.5878"},{"key":"25_CR8","unstructured":"Lowe, R., et al.: Multi-agent actor-critic for mixed cooperative-competitive environments. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"25_CR9","unstructured":"Mahajan, A., Rashid, T., Samvelyan, M., Whiteson, S.: MAVEN: multi-agent variational exploration. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"25_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-28929-8","volume-title":"A Concise Introduction to Decentralized POMDPs","author":"FA Oliehoek","year":"2016","unstructured":"Oliehoek, F.A., Amato, C.: A Concise Introduction to Decentralized POMDPs. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-28929-8"},{"key":"25_CR11","unstructured":"Rashid, T., Farquhar, G., Peng, B., Whiteson, S.: Weighted QMIX: expanding monotonic value function factorisation for deep multi-agent reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 33, pp. 10199\u201310210 (2020)"},{"key":"25_CR12","unstructured":"Rashid, T., Samvelyan, M., Schroeder, C., Farquhar, G., Foerster, J., Whiteson, S.: QMIX: monotonic value function factorisation for deep multi-agent reinforcement learning. In: International Conference on Machine Learning, pp. 4295\u20134304. PMLR (2018)"},{"key":"25_CR13","unstructured":"Samvelyan, M., et al.: The StarCraft multi-agent challenge. arXiv preprint arXiv:1902.04043 (2019)"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Shamsoshoara, A., Khaledi, M., Afghah, F., Razi, A., Ashdown, J.: Distributed cooperative spectrum sharing in uav networks using multi-agent reinforcement learning. In: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC), pp. 1\u20136. IEEE (2019)","DOI":"10.1109\/CCNC.2019.8651796"},{"key":"25_CR15","unstructured":"Son, K., Kim, D., Kang, W.J., Hostallero, D., Yi, Y.: QTRAN: learning to factorize with transformation for cooperative multi-agent reinforcement learning. CoRR abs\/1905.05408 (2019). http:\/\/arxiv.org\/abs\/1905.05408"},{"key":"25_CR16","unstructured":"Sunehag, P., et al.: Value-decomposition networks for cooperative multi-agent learning. arXiv preprint arXiv:1706.05296 (2017)"},{"issue":"4","key":"25_CR17","doi-asserted-by":"publisher","first-page":"e0172395","DOI":"10.1371\/journal.pone.0172395","volume":"12","author":"A Tampuu","year":"2017","unstructured":"Tampuu, A., et al.: Multiagent cooperation and competition with deep reinforcement learning. PLOS ONE 12(4), e0172395 (2017)","journal-title":"PLOS ONE"},{"key":"25_CR18","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"25_CR19","doi-asserted-by":"crossref","unstructured":"Vinyals, O., et al.: Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature 575(7782), 350\u2013354 (2019)","DOI":"10.1038\/s41586-019-1724-z"},{"key":"25_CR20","unstructured":"Wang, J., Ren, Z., Liu, T., Yu, Y., Zhang, C.: QPLEX: duplex dueling multi-agent Q-learning. arXiv preprint arXiv:2008.01062 (2020)"},{"key":"25_CR21","unstructured":"Wang, T., Dong, H., Lesser, V., Zhang, C.: ROMA: multi-agent reinforcement learning with emergent roles. arXiv preprint arXiv:2003.08039 (2020)"},{"key":"25_CR22","unstructured":"Wang, T., Gupta, T., Mahajan, A., Peng, B., Whiteson, S., Zhang, C.: RODE: learning roles to decompose multi-agent tasks. arXiv preprint arXiv:2010.01523 (2020)"},{"key":"25_CR23","unstructured":"Yang, M., Zhao, J., Hu, X., Zhou, W., Zhu, J., Li, H.: LDSA: learning dynamic subtask assignment in cooperative multi-agent reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 35, pp. 1698\u20131710 (2022)"},{"key":"25_CR24","unstructured":"Yang, Y., et al.: Qatten: a general framework for cooperative multiagent reinforcement learning. arXiv preprint arXiv:2002.03939 (2020)"},{"key":"25_CR25","unstructured":"Ye, D., et al.: Towards playing full MOBA games with deep reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 33, pp. 621\u2013632 (2020)"},{"key":"25_CR26","doi-asserted-by":"crossref","unstructured":"Zeng, X., Peng, H., Li, A.: Effective and stable role-based multi-agent collaboration by structural information principles. arXiv preprint arXiv:2304.00755 (2023)","DOI":"10.1609\/aaai.v37i10.26390"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8079-6_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:32:53Z","timestamp":1710261173000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8079-6_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,14]]},"ISBN":["9789819980789","9789819980796"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8079-6_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,14]]},"assertion":[{"value":"14 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Changsha","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iconip2023.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1274","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"650","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"51% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4.14","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.46","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}