82 citations · 426 across the 67 of their papers we have counts for
20 papers · 1 filter
Hierarchical Policy Blending As Optimal Transport
An T. Le, Kay Hansel, Jan Peters +1
We present hierarchical policy blending as optimal transport (HiPBOT). HiPBOT hierarchically adjusts the weights of low-level reactive expert policies of different agents by adding…
How Crucial is Transformer in Decision Transformer?
Max Siebenborn, Boris Belousov, Junning Huang +1
Decision Transformer (DT) is a recently proposed architecture for Reinforcement Learning that frames the decision-making process as an auto-regressive sequence modeling problem and…
Active Exploration for Robotic Manipulation
Tim Schneider, Boris Belousov, Georgia Chalvatzaki +3
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in recent years. One of the key challenges in manipulation i…
MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction
Vignesh Prasad, Dorothea Koert, Ruth Stock-Homburg +2
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human's actions and intentions is critical for efficient and effective coll…
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes
Joe Watson, Jan Peters
Monte Carlo methods have become increasingly relevant for control of non-differentiable systems, approximate dynamics models and learning from data. These methods scale to high-dim…
Hierarchical Policy Blending as Inference for Reactive Robot Control
Kay Hansel, Julen Urain, Jan Peters +1
Motion generation in cluttered, dense, and dynamic environments is a central topic in robotics, rendered as a multi-objective decision-making problem. Current approaches trade-off…