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Found 6 papers, 1 papers with code
Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
Exploration in sparse-reward reinforcement learning is difficult due to the requirement of long, coordinated sequences of actions in order to achieve any reward.
To the Noise and Back: Diffusion for Shared Autonomy
Traditional approaches to shared autonomy rely on knowledge of the environment dynamics, a discrete space of user goals that is known a priori, or knowledge of the user's policy -- assumptions that are unrealistic in many domains.
Depth Field Networks for Generalizable Multi-view Scene Representation
Modern 3D computer vision leverages learning to boost geometric reasoning, mapping image data to classical structures such as cost volumes or epipolar constraints to improve matching.
Grasp and Motion Planning for Dexterous Manipulation for the Real Robot Challenge
This report describes our winning submission to the Real Robot Challenge (https://real-robot-challenge. com/).
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
By analyzing the change in the maximum expected hitting cost, this work presents a formal understanding of the effect of potential-based reward shaping on regret (and sample complexity) in the undiscounted average reward setting.
Generalized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands
Symbolic models capture linguistic structure but have not scaled successfully to handle the diverse language produced by untrained users.
