{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T16:40:37Z","timestamp":1783701637358,"version":"3.55.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,6]]},"DOI":"10.1109\/icassp39728.2021.9414993","type":"proceedings-article","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T15:53:45Z","timestamp":1620921225000},"page":"3480-3484","source":"Crossref","is-referenced-by-count":4,"title":["Global-Localized Agent Graph Convolution for Multi-Agent Reinforcement Learning"],"prefix":"10.1109","author":[{"given":"Yuntao","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Dou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siqi","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Multiagent bidirectionally-coordinated nets: Emergence of human-level coordination in learning to play starcraft combat games","author":"peng","year":"2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1613\/jair.2447"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.01.031"},{"key":"ref13","first-page":"2085","article-title":"Value-decomposition networks for cooperative multi-agent learning based on team re-ward","author":"sunehag","year":"2018","journal-title":"AAMAS"},{"key":"ref14","first-page":"4295","article-title":"Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning","author":"rashid","year":"2018","journal-title":"International Conference on Machine Learning"},{"key":"ref15","article-title":"Deep multi-agent reinforcement learning with relevance graphs","author":"malysheva","year":"2018"},{"key":"ref16","article-title":"Learning transferable cooperative behavior in multi-agent teams","author":"agarwal","year":"2019"},{"key":"ref17","article-title":"Graph convolutional reinforcement learning","author":"jiang","year":"2019","journal-title":"International Conference on Learning Representations"},{"key":"ref18","article-title":"Relational deep reinforcement learning","author":"zambaldi","year":"2018"},{"key":"ref19","article-title":"Relational forward models for multi-agent learning","author":"tacchetti","year":"2018"},{"key":"ref4","first-page":"2","article-title":"The dynamics of reinforcement learning in cooperative multiagent systems","volume":"1998","author":"claus","year":"1998","journal-title":"AAAI\/IAAI"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3319619.3321894"},{"key":"ref6","first-page":"7254","article-title":"Learning attentional communication for multi-agent cooperation","author":"jiang","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2007.913919"},{"key":"ref8","article-title":"A study of ai population dynamics with million-agent reinforcement learning","author":"yang","year":"2017"},{"key":"ref7","first-page":"8130","article-title":"A structured prediction approach for generalization in cooperative multi-agent reinforcement learning","author":"carion","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref2","article-title":"Dota 2 with large scale deep reinforcement learning","author":"berner","year":"2019"},{"key":"ref1","author":"sutton","year":"2018","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref9","first-page":"2244","article-title":"Learning multiagent communication with backpropagation","author":"sukhbaatar","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.entcom.2018.02.005"},{"key":"ref22","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016"},{"key":"ref21","article-title":"Starcraft ii: A new challenge for reinforcement learning","author":"vinyals","year":"2017"}],"event":{"name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Toronto, ON, Canada","start":{"date-parts":[[2021,6,6]]},"end":{"date-parts":[[2021,6,11]]}},"container-title":["ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9413349\/9413350\/09414993.pdf?arnumber=9414993","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T11:40:50Z","timestamp":1652182850000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9414993\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,6]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icassp39728.2021.9414993","relation":{},"subject":[],"published":{"date-parts":[[2021,6,6]]}}}