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Christopher Mutschler — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Christopher Mutschler
27
papers ·
78
citations ·
25
h-index
Fraunhofer Institute for Integrated Circuits
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Deep Reinforcement Learning for Motion Planning of Mobile Robots
2019 · 13 citations
Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving
2022 · 5 citations
BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading
2023 · 3 citations
An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility
2022 · 2 citations
C-MCTS: Safe Planning with Monte Carlo Tree Search
2023 · 2 citations
Benchmarking Quantum Reinforcement Learning
2025 · 1 citations
How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies
2022 · 1 citations
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
2023 · 1 citations
Warm-Start Variational Quantum Policy Iteration
2024 · 1 citations
Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations
2026
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning
2023
Reinforcement Learning for Node Selection in Branch-and-Bound
2023
Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
2024
Top co-authors
Axel Plinge
· 7
Nico Meyer
· 4
Daniel D. Scherer
· 3
Georgios Kontes
· 3
Alexander Mattick
· 2
and Daniel D. Scherer
· 2
Bjoern M. Eskofier
· 2
Christian Ufrecht
· 2
Lukas M. Schmidt
· 2
Sebastian Rietsch
· 2
Alexander Popov
· 1
and Michael J. Hartmann
· 1
Topics
Model-Based RL
Policy Gradient
Value-Based
Meta-RL
Safe RL
Exploration
Multi-Agent
Offline RL