Air combat maneuver decision based on deep reinforcement learning with auxiliary reward
- 26 April 2024
- journal article
- research article
- Published by Springer Nature in Neural Computing and Applications
- Vol. 36 (21) , 13341-13356
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (62073177, 61973175, 62003351)
This publication has 46 references indexed in Scilit:
- Multi-agent air combat with two-stage graph-attention communicationNeural Computing and Applications, 2023
- Example-guided learning of stochastic human driving policies using deep reinforcement learningNeural Computing and Applications, 2022
- Autonomous decision-making for dogfights based on a tactical pursuit point approachAerospace Science and Technology, 2022
- Tactical UAV path optimization under radar threat using deep reinforcement learningNeural Computing and Applications, 2022
- Air-to-Air Combat Tactical Decision Method Based on SIRMs Fuzzy Logic and Improved Genetic Algorithm2021
- Deep reinforcement learning for wireless sensor scheduling in cyber–physical systemsAutomatica, 2020
- Influence of unmanned combat aerial vehicle agility on short-range aerial combat effectivenessAerospace Science and Technology, 2020
- An Air Combat Decision Learning System Based on a Brain-Like Cognitive MechanismCognitive Computation, 2019
- An autonomous aerial combat framework for two-on-two engagements based on basic fighter maneuversAerospace Science and Technology, 2018
- Suggestion for aircraft flying qualities requirements of a short-range air combat missionChinese Journal of Aeronautics, 2017