3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.AI2026
When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning
Yann Berthelot, Philippe Preux, Riad Akrour
Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses such controllers as queryable…
cs.LG2024★ 3 cited
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten +30
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curv…