14 citations · 61 across the 23 of their papers we have counts for
25 papers
Architectural Influence on Variational Quantum Circuits in Multi-Agent Reinforcement Learning: Evolutionary Strategies for Optimization
Michael Kölle, Karola Schneider, Sabrina Egger +5
In recent years, Multi-Agent Reinforcement Learning (MARL) has found application in numerous areas of science and industry, such as autonomous driving, telecommunications, and glob…
MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange
Philipp Altmann, Katharina Winter, Michael Kölle +3
Recent advances in multi-agent systems (MAS) have shown that incorporating peer incentivization (PI) mechanisms vastly improves cooperation. Especially in social dilemmas, communic…
Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms
Michael Kölle, Yannick Erpelding, Fabian Ritz +3
Recent advances in Multi-Agent Reinforcement Learning have prompted the modeling of intricate interactions between agents in simulated environments. In particular, the predator-pre…
ClusterComm: Discrete Communication in Decentralized MARL using Internal Representation Clustering
Robert Müller, Hasan Turalic, Thomy Phan +3
In the realm of Multi-Agent Reinforcement Learning (MARL), prevailing approaches exhibit shortcomings in aligning with human learning, robustness, and scalability. Addressing this,…
Challenges for Reinforcement Learning in Quantum Circuit Design
Philipp Altmann, Jonas Stein, Michael Kölle +5
Quantum computing (QC) in the current NISQ era is still limited in size and precision. Hybrid applications mitigating those shortcomings are prevalent to gain early insight and adv…
Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization
Michael Kölle, Felix Topp, Thomy Phan +3
Multi-Agent Reinforcement Learning is becoming increasingly more important in times of autonomous driving and other smart industrial applications. Simultaneously a promising new ap…