mlsanityData to 7 Oct 2026

A Survey on Reinforcement Learning in Aviation Applications

arXiv 2211.02147 ↗First posted 3 Nov 2022eess.SY cs.LG cs.SYcited by 19

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Abstract (arXiv)

Compared with model-based control and optimization methods, reinforcement learning (RL) provides a data-driven, learning-based framework to formulate and solve sequential decision-making problems. The RL framework has become promising due to largely improved data availability and computing power in the aviation industry. Many aviation-based applications can be formulated or treated as sequential decision-making problems. Some of them are offline planning problems, while others need to be solved online and are safety-critical. In this survey paper, we first describe standard RL formulations and solutions. Then we survey the landscape of existing RL-based applications in aviation. Finally, we summarize the paper, identify the technical gaps, and suggest future directions of RL research in aviation.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 38 of its 157 references that are in the map. First posted on arXiv 3 Nov 2022.

Builds on

38 of 157 references.

References · 38

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  3. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,416
  4. 2015Continuous control with deep reinforcement learningcited by 3,279
  5. 2015Trust Region Policy Optimizationcited by 2,503
  6. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
  7. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  8. 2018World Modelscited by 1,444
  9. 2019Mastering Atari, Go, Chess and Shogi by Planning with a Learned Modelcited by 1,327
  10. 2015Dueling Network Architectures for Deep Reinforcement Learningcited by 769
  11. 2017Counterfactual Multi-Agent Policy Gradientscited by 733
  12. 2020Deep Reinforcement Learning for Autonomous Driving: A Surveycited by 698
26 more
  1. 2019Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithmscited by 555
  2. 2016Learning to reinforcement learncited by 369
  3. 2017Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuningcited by 288
  4. 2018Mean Field Multi-Agent Reinforcement Learningcited by 202
  5. 2020Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 197
  6. 2018Model-Based Value Estimation for Efficient Model-Free Reinforcement Learningcited by 152
  7. 2016Continuous Deep Q-Learning with Model-based Accelerationcited by 149
  8. 2017Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observabilitycited by 143
  9. 2017Imagination-Augmented Agents for Deep Reinforcement Learningcited by 137
  10. 2020Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learningcited by 93
  11. 2020Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errorscited by 80
  12. 2018Reinforcement Learning for UAV Attitude Controlcited by 40
  13. 2019Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Drivingcited by 21
  14. 2019Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimizationcited by 14
  15. 2020Runtime Safety Assurance Using Reinforcement Learningcited by 8
  16. 2021Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurancecited by 8
  17. 2019Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learningcited by 6
  18. 2020A Deep Multi-Agent Reinforcement Learning Approach to Autonomous Separation Assurancecited by 6
  19. 2021Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learningcited by 6
  20. 2022Neural Network-based Flight Control Systems: Present and Futurecited by 6
  21. 2020An Autonomous Free Airspace En-route Controller using Deep Reinforcement Learning Techniquescited by 3
  22. 2022A Verification Framework for Certifying Learning-Based Safety-Critical Aviation Systemscited by 3
  23. 2019Resolving Congestions in the Air Traffic Management Domain via Multiagent Reinforcement Learning Methodscited by 2
  24. 2021Learning-to-Dispatch: Reinforcement Learning Based Flight Planning under Emergencycited by 2
  25. 2021Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learningcited by 2
  26. 2020Scalable FastMDP for Pre-departure Airspace Reservation and Strategic De-conflictcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 6; 2025: 6; 2026: 2.

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  1. 2023Risk-Aware Reinforcement Learning through Optimal Transport Theorycited by 7
  2. 2023Integrated Conflict Management for UAM with Strategic Demand Capacity Balancing and Learning-based Tactical Deconflictioncited by 6
  3. 2025Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learningcited by 4
  4. 2024Optimal Transport-Assisted Risk-Sensitive Q-Learningcited by 3
  5. 2023Joint Learning of Policy with Unknown Temporal Constraints for Safe Reinforcement Learningcited by 1
  6. 2024Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learningcited by 1
  7. 2024Deep deterministic policy gradient with symmetric data augmentation for lateral attitude tracking control of a fixed-wing aircraftcited by 1
  8. 2025Behavior Preference Regression for Offline Reinforcement Learningcited by 1
  9. 2025Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environmentscited by 1
  10. 2023Towards Theoretical Understanding of Data-Driven Policy Refinementcited by 0
  11. 2023Learning Interpretable Models of Aircraft Handling Behaviour by Reinforcement Learning from Human Feedbackcited by 0
  12. 2024Delay-Aware Reinforcement Learning for Highway On-Ramp Merging under Stochastic Communication Latencycited by 0
7 more
  1. 2024Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobilitycited by 0
  2. 2024Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learningcited by 0
  3. 2025APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional gamescited by 0
  4. 2025Reinforcement Twinning for Hybrid Control of Flapping-Wing Dronescited by 0
  5. 2025Safe and Economical UAV Trajectory Planning in Low-Altitude Airspace: A Hybrid DRL-LLM Approach with Compliance Awarenesscited by 0
  6. 2026Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimizationcited by 0
  7. 2026Flow-Corrected Thompson Sampling for Non-Stationary Contextual Banditscited by 0