498 citations · 934 across the 15 of their papers we have counts for
Showing 2016Show all
2 papers · 1 filter
cs.AI2016★ 322 cited
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Haoran Tang, Rein Houthooft, Davis Foote +6
Count-based exploration algorithms are known to perform near-optimally when used in conjunction with tabular reinforcement learning (RL) methods for solving small discrete Markov d…
cs.LG2016★ 498 cited
VIME: Variational Information Maximizing Exploration
Rein Houthooft, Xi Chen, Yan Duan +3
Scalable and effective exploration remains a key challenge in reinforcement learning (RL). While there are methods with optimality guarantees in the setting of discrete state and a…