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cs.LG2025
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…
cs.LG2024
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…