{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:07:50Z","timestamp":1767182870451,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":65,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFB4500703"],"award-info":[{"award-number":["2022YFB4500703"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902211 and 62202266"],"award-info":[{"award-number":["61902211 and 62202266"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004318","name":"Microsoft Research Asia","doi-asserted-by":"publisher","award":["100336949"],"award-info":[{"award-number":["100336949"]}],"id":[{"id":"10.13039\/100004318","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2022M721831"],"award-info":[{"award-number":["2022M721831"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3613764","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:30Z","timestamp":1698391650000},"page":"9093-9102","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["ParliRobo: Participant Lightweight AI Robots for Massively Multiplayer Online Games (MMOGs)"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8381-906X","authenticated-orcid":false,"given":"Jianwei","family":"Zheng","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5812-7883","authenticated-orcid":false,"given":"Changnan","family":"Xiao","sequence":"additional","affiliation":[{"name":"Bytedance Inc., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5120-8185","authenticated-orcid":false,"given":"Mingliang","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7286-122X","authenticated-orcid":false,"given":"Zhenhua","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8509-2650","authenticated-orcid":false,"given":"Feng","family":"Qian","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9104-6316","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6854-5416","authenticated-orcid":false,"given":"Xudong","family":"Wu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2743240"},{"key":"e_1_3_2_1_2_1","unstructured":"Christopher Berner Greg Brockman Brooke Chan et al. 2019. Dota 2 with Large Scale Deep Reinforcement Learning. arxiv: 1912.06680"},{"key":"e_1_3_2_1_3_1","unstructured":"Blizzard Entertainment Inc. 2022. StarCraft II Official Game Site. https:\/\/starcraft2.com\/."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.826093"},{"key":"e_1_3_2_1_5_1","volume-title":"Proc. of PMLR ICML. 793--802","author":"Brown Noam","year":"2019","unstructured":"Noam Brown, Adam Lerer, Sam Gross, and Tuomas Sandholm. 2019. Deep Counterfactual Regret Minimization. In Proc. of PMLR ICML. 793--802."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1137\/0722023"},{"key":"e_1_3_2_1_7_1","first-page":"216","article-title":"Monte-Carlo Tree Search: A New Framework for Game AI","volume":"4","author":"Chaslot Guillaume","year":"2008","unstructured":"Guillaume Chaslot, Sander Bakkes, Istvan Szita, and Pieter Spronck. 2008. Monte-Carlo Tree Search: A New Framework for Game AI. In Proc. of AAAI, Vol. 4. 216--217.","journal-title":"Proc. of AAAI"},{"key":"e_1_3_2_1_8_1","first-page":"26609","article-title":"The Elastic Lottery Ticket Hypothesis","volume":"34","author":"Chen Xiaohan","year":"2021","unstructured":"Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, and Zhangyang Wang. 2021. The Elastic Lottery Ticket Hypothesis. In Proc. of NeurIPS, Vol. 34. 26609--26621.","journal-title":"Proc. of NeurIPS"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2018.2816806"},{"key":"e_1_3_2_1_10_1","volume-title":"Proc. of ICLR.","author":"Frankle Jonathan","year":"2019","unstructured":"Jonathan Frankle and Michael Carbin. 2019. The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. In Proc. of ICLR."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2004.1365067"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Gibney Elizabeth. 2016. Google AI Algorithm Masters Ancient Game of Go. Nature News Vol. 529 7587 (2016) 445.","DOI":"10.1038\/529445a"},{"key":"e_1_3_2_1_13_1","unstructured":"Google. 2021. Official Website of Google Protocol Buffers. https:\/\/developers.google.com\/protocol-buffers."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1507149.1507178"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.2991\/iccsee.2013.391"},{"key":"e_1_3_2_1_16_1","volume-title":"Deep Reinforcement Learning from Self-Play in Imperfect-Information Games. arXiv preprint arXiv:1603.01121","author":"Heinrich Johannes","year":"2016","unstructured":"Johannes Heinrich and David Silver. 2016. Deep Reinforcement Learning from Self-Play in Imperfect-Information Games. arXiv preprint arXiv:1603.01121 (2016)."},{"key":"e_1_3_2_1_17_1","unstructured":"Henry Ewins. 2020. Like Animals Video Game AI Is Stupidly Intelligent. https:\/\/www.eurogamer.net\/articles\/2020-01-09-like-animals-video-game-ai-is-stupidly-intelligent."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2009.2032534"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITW.2010.5593336"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3206157.3206174"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301954"},{"key":"e_1_3_2_1_22_1","volume-title":"A Survey of Behavior Trees in Robotics and AI. arXiv preprint arXiv:2005.05842","author":"Iovino Matteo","year":"2020","unstructured":"Matteo Iovino, Edvards Scukins, Jonathan Styrud, Petter \u00d6gren, and Christian Smith. 2020. A Survey of Behavior Trees in Robotics and AI. arXiv preprint arXiv:2005.05842 (2020)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9562088"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.4103\/2229-516X.157168"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2002.1024752"},{"key":"e_1_3_2_1_26_1","unstructured":"KRAFTON Inc. 2022. PUBG Mobile. https:\/\/www.pubgmobile.com\/."},{"key":"e_1_3_2_1_27_1","volume-title":"Proc. of NeurIPS","volume":"25","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet Classification with Deep Convolutional Neural Networks. In Proc. of NeurIPS, Vol. 25."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2751145"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10827"},{"key":"e_1_3_2_1_30_1","volume-title":"Suphx: Mastering Mahjong with Deep Reinforcement Learning. arXiv preprint arXiv:2003.13590","author":"Li Junjie","year":"2020","unstructured":"Junjie Li, Sotetsu Koyamada, Qiwei Ye, et al. 2020. Suphx: Mastering Mahjong with Deep Reinforcement Learning. arXiv preprint arXiv:2003.13590 (2020)."},{"volume-title":"Content Distribution for Mobile Internet: A Cloud-Based Approach","author":"Li Zhenhua","key":"e_1_3_2_1_31_1","unstructured":"Zhenhua Li, Yafei Dai, Guihai Chen, and Yunhao Liu. 2023. Content Distribution for Mobile Internet: A Cloud-Based Approach, Second Edition. Springer Nature Press."},{"key":"e_1_3_2_1_32_1","volume-title":"Proc. of PMLR UAI. 215--224","author":"Lin Chiu-Chou","year":"2021","unstructured":"Chiu-Chou Lin, Wei-Chen Chiu, and I-Chen Wu. 2021. An Unsupervised Video Game Playstyle Metric via State Discretization. In Proc. of PMLR UAI. 215--224."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/631"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.232078"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3300141"},{"key":"e_1_3_2_1_36_1","unstructured":"Michael Matuschek. 2022. Using Adaptive AI to Improve the Gaming Experience. https:\/\/www.mouser.com\/blog\/using-adaptive-ai-improve-gaming-experience."},{"key":"e_1_3_2_1_37_1","volume-title":"Transform: Conformal Mapping Algorithms. https:\/\/mipav.cit.nih.gov\/pubwiki\/index.php\/Transform:_Conformal_Mapping_Algorithms.","author":"MIPAV.","year":"2020","unstructured":"MIPAV. 2020. Transform: Conformal Mapping Algorithms. https:\/\/mipav.cit.nih.gov\/pubwiki\/index.php\/Transform:_Conformal_Mapping_Algorithms."},{"key":"e_1_3_2_1_38_1","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver et al. 2013. Playing Atari with Deep Reinforcement Learning. arXiv preprint arXiv:1312.5602 (2013)."},{"key":"e_1_3_2_1_39_1","volume-title":"Nature","volume":"518","author":"Mnih Volodymyr","year":"2015","unstructured":"Volodymyr Mnih, Koray Kavukcuoglu, David Silver, et al. 2015. Human-Level Control through Deep Reinforcement Learning. Nature, Vol. 518, 7540 (2015), 529--533."},{"volume-title":"Mobile Legends: Bang Bang. https:\/\/m.mobilelegends.com\/.","year":"2022","key":"e_1_3_2_1_40_1","unstructured":"Moonton. 2022. Mobile Legends: Bang Bang. https:\/\/m.mobilelegends.com\/."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDT.2010.10"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06053-z"},{"key":"e_1_3_2_1_43_1","unstructured":"Zeev Nehari. 2012. Conformal Mapping. Courier Corporation."},{"key":"e_1_3_2_1_44_1","volume-title":"Proc. of FDG.","author":"Osborn Joseph C","year":"2014","unstructured":"Joseph C Osborn and Michael Mateas. 2014. A Game-Independent Play Trace Dissimilarity Metric. In Proc. of FDG."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2013.6633663"},{"key":"e_1_3_2_1_46_1","unstructured":"John Schulman Filip Wolski Prafulla Dhariwal et al. 2017. Proximal Policy Optimization Algorithms. arXiv preprint arXiv:1707.06347 (2017)."},{"key":"e_1_3_2_1_47_1","unstructured":"Kun Shao Zhentao Tang Yuanheng Zhu et al. 2019. A Survey of Deep Reinforcement Learning in Video Games. arXiv preprint arXiv:1912.10944 (2019)."},{"key":"e_1_3_2_1_48_1","volume-title":"Science","volume":"362","author":"Silver David","year":"2018","unstructured":"David Silver, Thomas Hubert, Julian Schrittwieser, et al. 2018. A General Reinforcement Learning Algorithm That Masters Chess, Shogi, and Go through Self-Play. Science, Vol. 362, 6419 (2018), 1140--1144."},{"key":"e_1_3_2_1_49_1","volume-title":"Very Deep Convolutional Networks for Large-scale Image Recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-scale Image Recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_1_50_1","volume-title":"Proc. of ICLR.","author":"Springenberg Jost Tobias","year":"2015","unstructured":"Jost Tobias Springenberg, Alexey Dosovitskiy, et al. 2015. Striving for Simplicity: The All Convolutional Net. In Proc. of ICLR."},{"key":"e_1_3_2_1_51_1","unstructured":"TheExpressWire. 2023. 2023-2029 Massive Multiplayer Online (MMO) Games Market Size Detailed Report with Sales and Revenue Analysis | Research by Absolute Reports. https:\/\/www.digitaljournal.com\/pr\/news\/2023-2029-massive-multiplayer-online-mmo-games-market-size-detailed-report-with-sales-and-revenue-analysis-research-by-absolute-reports."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2009.5286481"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1093\/mind\/LIX.236.433"},{"key":"e_1_3_2_1_54_1","unstructured":"Valve Corporation. 2022. Dota2 Official Game Site. https:\/\/www.dota2.com\/home."},{"key":"e_1_3_2_1_55_1","volume-title":"Proc. of AAAI. 929--930","author":"Lent Michael Van","year":"1999","unstructured":"Michael Van Lent, John Laird, Josh Buckman, et al. 1999. Intelligent Agents in Computer Games. In Proc. of AAAI. 929--930."},{"key":"e_1_3_2_1_56_1","volume-title":"Junyoung and others","author":"Babuschkin Oriol","year":"2019","unstructured":"Vinyals, Oriol and Babuschkin, Igor and Chung, Junyoung and others. 2019. Alphastar: Mastering the Real-Time Strategy Game Starcraft II. DeepMind Blog (2019), 2."},{"key":"e_1_3_2_1_57_1","first-page":"1","article-title":"Interpolation and Extrapolation","volume":"17","author":"Wahab Muhammad Abdul","year":"2017","unstructured":"Muhammad Abdul Wahab. 2017. Interpolation and Extrapolation. In Proc. Topics Syst. Eng. Winter Term, Vol. 17. 1--6.","journal-title":"Proc. Topics Syst. Eng"},{"key":"e_1_3_2_1_58_1","unstructured":"Wikipedia. 2022. Kullback Leibler divergence. https:\/\/en.wikipedia.org\/wiki\/Kullback-Leibler_divergence."},{"key":"e_1_3_2_1_59_1","first-page":"621","article-title":"Towards Playing Full MOBA Games with Deep Reinforcement Learning","volume":"33","author":"Ye Deheng","year":"2020","unstructured":"Deheng Ye, Guibin Chen, Wen Zhang, et al. 2020a. Towards Playing Full MOBA Games with Deep Reinforcement Learning. In Proc. of NeurIPS, Vol. 33. 621--632.","journal-title":"Proc. of NeurIPS"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6144"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"crossref","unstructured":"Sule Yildirim and Sindre Berg Stene. 2010. A Survey on the Need and Use of AI in Game Agents. InTech.","DOI":"10.5772\/8968"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.05.032"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11623"},{"key":"e_1_3_2_1_65_1","volume-title":"Proc. of NeurIPS","volume":"20","author":"Zinkevich Martin","year":"2007","unstructured":"Martin Zinkevich, Michael Johanson, Michael Bowling, and Carmelo Piccione. 2007. Regret Minimization in Games with Incomplete Information. In Proc. of NeurIPS, Vol. 20."}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Ottawa ON Canada","acronym":"MM '23"},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3613764","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3613764","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:05:27Z","timestamp":1755821127000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3613764"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":65,"alternative-id":["10.1145\/3581783.3613764","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3613764","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}