521 citations · 1.2k across the 41 of their papers we have counts for
4 papers · 1 filter
SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration
Giulia Vezzani, Dhruva Tirumala, Markus Wulfmeier +13
The ability to effectively reuse prior knowledge is a key requirement when building general and flexible Reinforcement Learning (RL) agents. Skill reuse is one of the most common a…
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation
Alex X. Lee, Coline Devin, Jost Tobias Springenberg +4
Reinforcement learning (RL) has been shown to be effective at learning control from experience. However, RL typically requires a large amount of online interaction with the environ…
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach
Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan +6
Actor-critic algorithms that make use of distributional policy evaluation have frequently been shown to outperform their non-distributional counterparts on many challenging control…
Forgetting and Imbalance in Robot Lifelong Learning with Off-policy Data
Wenxuan Zhou, Steven Bohez, Jan Humplik +5
Robots will experience non-stationary environment dynamics throughout their lifetime: the robot dynamics can change due to wear and tear, or its surroundings may change over time.…