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cs.LG2021
Q-Mixing Network for Multi-Agent Pathfinding in Partially Observable Grid Environments
Vasilii Davydov, Alexey Skrynnik, Konstantin Yakovlev +1
In this paper, we consider the problem of multi-agent navigation in partially observable grid environments. This problem is challenging for centralized planning approaches as they,…
cs.LG2020★ 2 cited
Forgetful Experience Replay in Hierarchical Reinforcement Learning from Demonstrations
Alexey Skrynnik, Aleksey Staroverov, Ermek Aitygulov +3
Currently, deep reinforcement learning (RL) shows impressive results in complex gaming and robotic environments. Often these results are achieved at the expense of huge computation…