9 citations · 9 across the 3 of their papers we have counts for
4 papers · 1 filter
Behavior Preference Regression for Offline Reinforcement Learning
Padmanaba Srinivasan, William Knottenbelt
Offline reinforcement learning (RL) methods aim to learn optimal policies with access only to trajectories in a fixed dataset. Policy constraint methods formulate policy learning a…
Offline Model-Based Reinforcement Learning with Anti-Exploration
Padmanaba Srinivasan, William Knottenbelt
Model-based reinforcement learning (MBRL) algorithms learn a dynamics model from collected data and apply it to generate synthetic trajectories to enable faster learning. This is a…
Offline Reinforcement Learning with Behavioral Supervisor Tuning
Padmanaba Srinivasan, William Knottenbelt
Offline reinforcement learning (RL) algorithms are applied to learn performant, well-generalizing policies when provided with a static dataset of interactions. Many recent approach…
Time-series Transformer Generative Adversarial Networks
Padmanaba Srinivasan, William J. Knottenbelt
Many real-world tasks are plagued by limitations on data: in some instances very little data is available and in others, data is protected by privacy enforcing regulations (e.g. GD…