15 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
An Idiosyncrasy of Time-discretization in Reinforcement Learning
Kris De Asis, Richard S. Sutton
Many reinforcement learning algorithms are built on an assumption that an agent interacts with an environment over fixed-duration, discrete time steps. However, physical systems ar…
cs.AI2017★ 15 cited
Multi-step Reinforcement Learning: A Unifying Algorithm
Kristopher De Asis, J. Fernando Hernandez-Garcia, G. Zacharias Holland +1
Unifying seemingly disparate algorithmic ideas to produce better performing algorithms has been a longstanding goal in reinforcement learning. As a primary example, TD() elegant…