Multi-Agent Partial Observable Safe Reinforcement Learning for Counter Uncrewed Aerial Systems

Author:

Pierre Jean-Elie1ORCID,Sun Xiang1ORCID,Fierro Rafael1ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA

Funder

National Science Foundation

Air Force Research Laboratory

Sandia National Laboratories

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference38 articles.

1. Safe deep reinforcement learning for multi-agent systems with continuous action spaces;sheebaelhamd;arXiv 2108 03952,2021

2. The before, during, and after of multi-robot deadlock;grover;Int J Robot Res,2016

3. Safe exploration in continuous action spaces;dalal;arXiv 1801 08757,2018

4. High-dimensional continuous control using generalized advantage estimation;schulman;arXiv 1506 02438 [cs],2015

5. Distributed Coordination Control for Multi-Robot Networks Using Lyapunov-Like Barrier Functions

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3