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Autonomous Agents and Multiagent Systems. Best and Visionary Papers : AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers / edited by Francisco S. Melo, Fei Fang
(Lecture Notes in Artificial Intelligence. ISSN:29459141 ; 13441)
| データ種別 | 電子ブック |
|---|---|
| 版 | 1st ed. 2022. |
| 出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
| 出版年 | 2022 |
| 大きさ | IX, 145 p. 34 illus., 23 illus. in color : online resource |
| 著者標目 | Melo, Francisco S editor Fang, Fei editor SpringerLink (Online service) |
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| 一般注記 | Best Papers -- TOPS: Transition-based volatility-reduced policy search -- School's out? Simulating schooling strategies during COVID-19 -- Data-driven agent-based model development to support human-centric TOD design -- Enabling negotiating agents to explore very large outcome spaces -- Purposeful failures as a form of culturally-appropriate intelligent disobedience during human-robot social interaction -- Visionary Papers -- An agent-based model of horizontal mergers -- Multi-agent traffic signal control via distributed RL with spatial and temporal feature extraction -- About digital twins, agents, and multiagent systems: A cross-fertilisation journey -- Only those who can obey can disobey: The intentional implications of artificial agent disobedience This book constitutes thoroughly refereed and revised selected best and visionary papers from the Workshops held at the International Conference on Autonomous Agents and Multiagent Systems AAMAS 2022, which took place online, during May 9–13, 2022. The 5 best papers and 4 visionary papers included in this book stem from the following workshops: - 13th Workshop on Optimization and Learning in Multi-agent Systems (OptLearnMAS); - 23rd Workshop on Multi-Agent Based Simulation (MABS); - 6th Workshop on Agent-Based Modelling of Urban Systems (ABMUS); - 10th Workshop on Engineering Multi-Agent Systems (EMAS); - 1st Workshop on Rebellion and Disobedience in AI (RaD-AI). There was a total of 59 submissions to these workshops. HTTP:URL=https://doi.org/10.1007/978-3-031-20179-0 |
|---|---|
| 件 名 | LCSH:Artificial intelligence LCSH:Computer engineering LCSH:Computer networks LCSH:Software engineering LCSH:Social sciences—Data processing LCSH:Numerical analysis FREE:Artificial Intelligence FREE:Computer Engineering and Networks FREE:Software Engineering FREE:Computer Application in Social and Behavioral Sciences FREE:Numerical Analysis |
| 分 類 | LCC:Q334-342 LCC:TA347.A78 DC23:006.3 |
| 書誌ID | EB00001044 |
| ISBN | 9783031201790 |
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※2019年3月27日以降