Autonomous target tracking of multi-UAV: A two-stage deep reinforcement learning approach with expert experience
Authors:
- Jiahua WangJWJiahua Wang
- Ping ZhangPZPing Zhang
- Yang WangYWYang Wang
- 8 July 2023
- journal article
- research article
- Published by Elsevier in Applied Soft Computing
- Vol. 145
Abstract
No abstract availableKeywords
This publication has 24 references indexed in Scilit:
- Reinforcement Learning, Fast and SlowTrends in Cognitive Sciences, 2019
- A Multi-Objective Agent-Based Control Approach With Application in Intelligent Traffic Signal SystemIEEE Transactions on Intelligent Transportation Systems, 2019
- CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving2018
- Mastering the game of Go without human knowledgeNature, 2017
- Multi-UAVs tracking target in urban environment by model predictive control and Improved Grey Wolf OptimizerAerospace Science and Technology, 2016
- Deep Residual Learning for Image Recognition2016
- Mastering the game of Go with deep neural networks and tree searchNature, 2016
- Deep learningNature, 2015
- Human-level control through deep reinforcement learningNature, 2015
- Decentralised Standoff Tracking of Moving Targets Using Adaptive Sliding Mode Control for UAVsJournal of Intelligent & Robotic Systems, 2013