2 citations · 3 across the 13 of their papers we have counts for
4 papers · 1 filter
Exploiting Local Dynamics Regularity for Reusable Skills in Offline Hierarchical RL
Sarthak Dayal, Abhinav Peri, Carl Qi +4
Hierarchical Reinforcement Learning (HRL) promises to solve long-horizon Reinforcement Learning (RL) tasks more efficiently than non-hierarchical counterparts by discovering and re…
RLZero: Direct Policy Inference from Language Without In-Domain Supervision
Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo +6
The reward hypothesis states that all goals and purposes can be understood as the maximization of a received scalar reward signal. However, in practice, defining such a reward sign…
Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere +3
Reinforcement learning (RL) algorithms often struggle to learn policies that generalize to novel situations due to issues such as causal confusion, overfitting to irrelevant factor…
Granger Causal Interaction Skill Chains
Caleb Chuck, Kevin Black, Aditya Arjun +2
Reinforcement Learning (RL) has demonstrated promising results in learning policies for complex tasks, but it often suffers from low sample efficiency and limited transferability.…