4 citations · 10 across the 6 of their papers we have counts for
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3 papers · 1 filter
cs.MA2023★ 2 cited
AccMER: Accelerating Multi-Agent Experience Replay with Cache Locality-aware Prioritization
Kailash Gogineni, Yongsheng Mei, Peng Wei +2
Multi-Agent Experience Replay (MER) is a key component of off-policy reinforcement learning~(RL) algorithms. By remembering and reusing experiences from the past, experience replay…
cs.MA2023★ 4 cited
Towards Efficient Multi-Agent Learning Systems
Kailash Gogineni, Peng Wei, Tian Lan +1
Multi-Agent Reinforcement Learning (MARL) is an increasingly important research field that can model and control multiple large-scale autonomous systems. Despite its achievements,…
cs.MA2023★ 2 cited
Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems
Kailash Gogineni, Peng Wei, Tian Lan +1
Multi-Agent Reinforcement Learning (MARL) is a promising area of research that can model and control multiple, autonomous decision-making agents. During online training, MARL algor…