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Books and Theses
- 2021
[b1]Harald Bayerlein:
Machine Learning Methods for UAV-aided Wireless Networks. (Méthodes d'apprentissage automatique pour l'utilisation des drones dans les réseaux sans-fil). Sorbonne University, France, 2021
Journal Articles
- 2021
- [j1]Harald Bayerlein
, Mirco Theile, Marco Caccamo, David Gesbert:
Multi-UAV Path Planning for Wireless Data Harvesting With Deep Reinforcement Learning. IEEE Open J. Commun. Soc. 2: 1171-1187 (2021)
Conference and Workshop Papers
- 2023
- [c9]Jichao Chen, Omid Esrafilian, Harald Bayerlein, David Gesbert, Marco Caccamo:
Model-Aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks. GLOBECOM (Workshops) 2023: 818-823 - 2022
- [c8]Raphael Trumpp, Harald Bayerlein, David Gesbert:
Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi-Agent Reinforcement Learning for Collision Avoidance. IV 2022: 331-336 - 2021
- [c7]Omid Esrafilian, Harald Bayerlein, David Gesbert:
Model-aided Deep Reinforcement Learning for Sample-efficient UAV Trajectory Design in IoT Networks. GLOBECOM 2021: 1-6 - [c6]Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert, Marco Caccamo:
UAV Path Planning using Global and Local Map Information with Deep Reinforcement Learning. ICAR 2021: 539-546 - 2020
- [c5]Harald Bayerlein, Mirco Theile, Marco Caccamo, David Gesbert:
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach. GLOBECOM 2020: 1-6 - [c4]Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert, Marco Caccamo:
UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning. IROS 2020: 1444-1449 - 2018
- [c3]Harald Bayerlein, Rajeev Gangula, David Gesbert:
Learning to Rest: A Q-Learning Approach to Flying Base Station Trajectory Design with Landing Spots. ACSSC 2018: 724-728 - [c2]Harald Bayerlein, Paul de Kerret, David Gesbert:
Trajectory Optimization for Autonomous Flying Base Station via Reinforcement Learning. SPAWC 2018: 1-5 - 2013
- [c1]Michael Schoeffler, Fabian-Robert Stöter, Harald Bayerlein, Bernd Edler, Jürgen Herre:
An Experiment about Estimating the Number of Instruments in Polyphonic Music: A Comparison Between Internet and Laboratory Results. ISMIR 2013: 389-394
Informal and Other Publications
- 2023
- [i8]Jichao Chen, Omid Esrafilian, Harald Bayerlein, David Gesbert, Marco Caccamo:
Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks. CoRR abs/2306.02029 (2023) - [i7]Mirco Theile, Harald Bayerlein, Marco Caccamo, Alberto L. Sangiovanni-Vincentelli:
Learning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning. CoRR abs/2309.03157 (2023) - 2021
- [i6]Omid Esrafilian, Harald Bayerlein, David Gesbert:
Model-aided Deep Reinforcement Learning for Sample-efficient UAV Trajectory Design in IoT Networks. CoRR abs/2104.10403 (2021) - [i5]Raphael Trumpp, Harald Bayerlein, David Gesbert:
Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi-Agent Reinforcement Learning for Collision Avoidance. CoRR abs/2109.15266 (2021) - 2020
- [i4]Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert, Marco Caccamo:
UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning. CoRR abs/2003.02609 (2020) - [i3]Harald Bayerlein, Mirco Theile, Marco Caccamo, David Gesbert:
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach. CoRR abs/2007.00544 (2020) - [i2]Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert, Marco Caccamo:
UAV Path Planning using Global and Local Map Information with Deep Reinforcement Learning. CoRR abs/2010.06917 (2020) - [i1]Harald Bayerlein, Mirco Theile, Marco Caccamo, David Gesbert:
Multi-UAV Path Planning for Wireless Data Harvesting with Deep Reinforcement Learning. CoRR abs/2010.12461 (2020)
Coauthor Index
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