Neural-network-based parameter tuning for multi-agent simulation using deep reinforcement learning

IF 2.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS World Wide Web-Internet and Web Information Systems Pub Date : 2023-08-03 DOI:10.1007/s11280-023-01197-5
Masanori Hirano, K. Izumi
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基于神经网络的深度强化学习多智能体仿真参数调优
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来源期刊
World Wide Web-Internet and Web Information Systems
World Wide Web-Internet and Web Information Systems 工程技术-计算机:软件工程
CiteScore
7.30
自引率
10.80%
发文量
131
审稿时长
6 months
期刊介绍: World Wide Web: Internet and Web Information Systems (WWW) is an international, archival, peer-reviewed journal which covers all aspects of the World Wide Web, including issues related to architectures, applications, Internet and Web information systems, and communities. The purpose of this journal is to provide an international forum for researchers, professionals, and industrial practitioners to share their rapidly developing knowledge and report on new advances in Internet and web-based systems. The journal also focuses on all database- and information-system topics that relate to the Internet and the Web, particularly on ways to model, design, develop, integrate, and manage these systems. Appearing quarterly, the journal publishes (1) papers describing original ideas and new results, (2) vision papers, (3) reviews of important techniques in related areas, (4) innovative application papers, and (5) progress reports on major international research projects. Papers published in the WWW journal deal with subjects directly or indirectly related to the World Wide Web. The WWW journal provides timely, in-depth coverage of the most recent developments in the World Wide Web discipline to enable anyone involved to keep up-to-date with this dynamically changing technology.
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