72 citations · 113 across the 5 of their papers we have counts for
5 papers
Latent-Predictive Empowerment: Measuring Empowerment without a Simulator
Andrew Levy, Alessandro Allievi, George Konidaris
Empowerment has the potential to help agents learn large skillsets, but is not yet a scalable solution for training general-purpose agents. Recent empowerment methods learn diverse…
Hierarchical Empowerment: Towards Tractable Empowerment-Based Skill Learning
Andrew Levy, Sreehari Rammohan, Alessandro Allievi +2
General purpose agents will require large repertoires of skills. Empowerment -- the maximum mutual information between skills and states -- provides a pathway for learning large co…
HAC Explore: Accelerating Exploration with Hierarchical Reinforcement Learning
Willie McClinton, Andrew Levy, George Konidaris
Sparse rewards and long time horizons remain challenging for reinforcement learning algorithms. Exploration bonuses can help in sparse reward settings by encouraging agents to expl…
Hierarchical Reinforcement Learning with Hindsight
Andrew Levy, Robert Platt, Kate Saenko
Reinforcement Learning (RL) algorithms can suffer from poor sample efficiency when rewards are delayed and sparse. We introduce a solution that enables agents to learn temporally e…
Learning Multi-Level Hierarchies with Hindsight
Andrew Levy, George Konidaris, Robert Platt +1
Hierarchical agents have the potential to solve sequential decision making tasks with greater sample efficiency than their non-hierarchical counterparts because hierarchical agents…