25 citations · 53 across the 12 of their papers we have counts for
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cs.LG2023
Measuring and Mitigating Interference in Reinforcement Learning
Vincent Liu, Han Wang, Ruo Yu Tao +3
Catastrophic interference is common in many network-based learning systems, and many proposals exist for mitigating it. Before overcoming interference we must understand it better.…
cs.LG2023★ 1 cited
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Rich Sutton +1
Constructing states from sequences of observations is an important component of reinforcement learning agents. One solution for state construction is to use recurrent neural networ…