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Found 4 papers, 2 papers with code
DARL1N: Distributed multi-Agent Reinforcement Learning with One-hop Neighbors
In this paper, we address this limitation by introducing a scalable MARL method called Distributed multi-Agent Reinforcement Learning with One-hop Neighbors (DARL1N).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Multi-Agent Reinforcement Learning Based Coded Computation for Mobile Ad Hoc Computing
Mobile ad hoc computing (MAHC), which allows mobile devices to directly share their computing resources, is a promising solution to address the growing demands for computing resources required by mobile devices.
Coding for Distributed Multi-Agent Reinforcement Learning
This paper aims to mitigate straggler effects in synchronous distributed learning for multi-agent reinforcement learning (MARL) problems.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems
In recent years, coded distributed computing (CDC) has attracted significant attention, because it can efficiently facilitate many delay-sensitive computation tasks against unexpected latencies in distributed computing systems.
Distributed, Parallel, and Cluster Computing
