12 citations · 31 across the 11 of their papers we have counts for
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cs.LG2022
Credit-cognisant reinforcement learning for multi-agent cooperation
F. Bredell, H. A. Engelbrecht, J. C. Schoeman
Traditional multi-agent reinforcement learning (MARL) algorithms, such as independent Q-learning, struggle when presented with partially observable scenarios, and where agents are…
cs.RO2022
Bypassing the Simulation-to-reality Gap: Online Reinforcement Learning using a Supervisor
Benjamin David Evans, Johannes Betz, Hongrui Zheng +3
Deep reinforcement learning (DRL) is a promising method to learn control policies for robots only from demonstration and experience. To cover the whole dynamic behaviour of the rob…