4 citations · 9 across the 7 of their papers we have counts for
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cs.LG2023★ 4 cited
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
Matthias Gerstgrasser, Tom Danino, Sarah Keren
We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in which agents share with other agents a limited number of transitions they observe…
cs.LG2021
Collaboration Promotes Group Resilience in Multi-Agent RL
Ilai Shraga, Guy Azran, Matthias Gerstgrasser +3
To effectively operate in various dynamic scenarios, RL agents must be resilient to unexpected changes in their environment. Previous work on this form of resilience has focused on…