5 citations · 6 across the 3 of their papers we have counts for
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cs.LG2023
Reinforcement Learning with Fast and Forgetful Memory
Steven Morad, Ryan Kortvelesy, Stephan Liwicki +1
Nearly all real world tasks are inherently partially observable, necessitating the use of memory in Reinforcement Learning (RL). Most model-free approaches summarize the trajectory…
cs.LG2023★ 5 cited
POPGym: Benchmarking Partially Observable Reinforcement Learning
Steven Morad, Ryan Kortvelesy, Matteo Bettini +2
Real world applications of Reinforcement Learning (RL) are often partially observable, thus requiring memory. Despite this, partial observability is still largely ignored by contem…