On reward distribution in reinforcement learning of multi-agent surveillance systems with temporal logic specifications
IF 1.4
4区 计算机科学
Q4 ROBOTICS
引用次数: 0
Abstract
In multi-agent systems, it is important to design a reward based on the contribution of each agent for efficient learning. In this paper, we propose a reward distribution method for a surveillance ...论具有时间逻辑规范的多代理监控系统强化学习中的奖励分配
在多代理系统中，根据每个代理的贡献设计奖励对于高效学习非常重要。本文提出了一种用于监视系统的奖励分配方法。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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来源期刊
Advanced Robotics
工程技术-机器人学
CiteScore
4.10
自引率
20.00%
发文量
102
审稿时长
5.3 months
期刊介绍：
Advanced Robotics (AR) is the international journal of the Robotics Society of Japan and has a history of more than twenty years. It is an interdisciplinary journal which integrates publication of all aspects of research on robotics science and technology. Advanced Robotics publishes original research papers and survey papers from all over the world. Issues contain papers on analysis, theory, design, development, implementation and use of robots and robot technology. The journal covers both fundamental robotics and robotics related to applied fields such as service robotics, field robotics, medical robotics, rescue robotics, space robotics, underwater robotics, agriculture robotics, industrial robotics, and robots in emerging fields. It also covers aspects of social and managerial analysis and policy regarding robots.
Advanced Robotics (AR) is an international, ranked, peer-reviewed journal which publishes original research contributions to scientific knowledge.
All manuscript submissions are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees.
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