18 citations · 19 across the 3 of their papers we have counts for
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cs.LG2021
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems
Joel Oren, Chana Ross, Maksym Lefarov +5
We study combinatorial problems with real world applications such as machine scheduling, routing, and assignment. We propose a method that combines Reinforcement Learning (RL) and…
cs.LG2019★ 1 cited
Trajectory-Based Off-Policy Deep Reinforcement Learning
Andreas Doerr, Michael Volpp, Marc Toussaint +2
Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks. However, these methods are also data-inefficient, aff…