The power of combined modalities in interactive robot learning
H. Beierling, R. Beierling, A.-L. Vollmer, Frontiers in Robotics and AI 12 (2025).

mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks
S.B. Schneider, S. Werner, R. Khalili, A. Hecker, H. Karl, in: IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2022.

Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding
H. Afifi, F.J. Sauer, H. Karl, in: 2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21), Hyderabad, India, 2021.

Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities
H. Afifi, M. Guenther, A. Brendel, H. Karl, W. Kellermann, in: 14. ITG Conference on Speech Communication (ITG 2021), 2021.

Learning Flow Scheduling
A. Hasnain, H. Karl, in: 2021 IEEE 18th Annual Consumer Communications &; Networking Conference (CCNC), IEEE Computer Society, n.d.

Learning Coflow Admissions
A. Hasnain, H. Karl, in: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, n.d.

A Reinforcement Learning QoI/QoS-Aware Approach in Acoustic Sensor Networks
H. Afifi, A. Ramaswamy, H. Karl, in: 2021 IEEE 18th Annual Consumer Communications \'26; Networking Conference (CCNC) (CCNC 2021), 2021.

Distributed Online Service Coordination Using Deep Reinforcement Learning
S.B. Schneider, H. Qarawlus, H. Karl, in: IEEE International Conference on Distributed Computing Systems (ICDCS), IEEE, 2021.

Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning
S.B. Schneider, R. Khalili, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, A. Hecker, Transactions on Network and Service Management (2021).

DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning
S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.

Conventional and Machine Learning Approaches for Network and Service Coordination
S.B. Schneider, Conventional and Machine Learning Approaches for Network and Service Coordination, 2021.

Self-Driving Network and Service Coordination Using Deep Reinforcement Learning
S.B. Schneider, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, R. Khalili, A. Hecker, in: IEEE International Conference on Network and Service Management (CNSM), IEEE, 2020.

Deep reinforcement learning for scheduling in large-scale networked control systems
A. Redder, A. Ramaswamy, D. Quevedo, in: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019.