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Found 2 papers, 1 papers with code
Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning
In this work, we are particularly interested in analyzing how multi-agent reinforcement learning can bridge the gap to reality in distributed multi-robot systems where the operation of the different robots is not necessarily homogeneous.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Ubiquitous Distributed Deep Reinforcement Learning at the Edge: Analyzing Byzantine Agents in Discrete Action Spaces
The integration of edge computing in next-generation mobile networks is bringing low-latency and high-bandwidth ubiquitous connectivity to a myriad of cyber-physical systems.
