3 papers
cs.MA2024
Emergence in Multi-Agent Systems: A Safety Perspective
Philipp Altmann, Julian Schönberger, Steffen Illium +5
Emergent effects can arise in multi-agent systems (MAS) where execution is decentralized and reliant on local information. These effects may range from minor deviations in behavior…
quant-ph2024
Quantum Multi-Agent Reinforcement Learning for Aerial Ad-hoc Networks
Theodora-Augustina Drăgan, Akshat Tandon, Carsten Strobel +2
Quantum machine learning (QML) as combination of quantum computing with machine learning (ML) is a promising direction to explore, in particular due to the advances in realizing qu…
cs.LG2024
Reinforcement Learning with Ensemble Model Predictive Safety Certification
Sven Gronauer, Tom Haider, Felippe Schmoeller da Roza +1
Reinforcement learning algorithms need exploration to learn. However, unsupervised exploration prevents the deployment of such algorithms on safety-critical tasks and limits real-w…