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cs.LG2024
WARPD: World model Assisted Reactive Policy Diffusion
Shashank Hegde, Satyajeet Das, Gautam Salhotra +1
With the increasing availability of open-source robotic data, imitation learning has become a promising approach for both manipulation and locomotion. Diffusion models are now wide…
cs.LG2023
Generating Behaviorally Diverse Policies with Latent Diffusion Models
Shashank Hegde, Sumeet Batra, K. R. Zentner +1
Recent progress in Quality Diversity Reinforcement Learning (QD-RL) has enabled learning a collection of behaviorally diverse, high performing policies. However, these methods typi…
cs.LG2021
Agents that Listen: High-Throughput Reinforcement Learning with Multiple Sensory Systems
Shashank Hegde, Anssi Kanervisto, Aleksei Petrenko
Humans and other intelligent animals evolved highly sophisticated perception systems that combine multiple sensory modalities. On the other hand, state-of-the-art artificial agents…