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On Multi-objective Policy Optimization as a Tool for Reinforcement Learning
Many advances that have improved the robustness and efficiency of deep r...
06/15/2021 ∙ by Abbas Abdolmaleki, et al. ∙
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Representation Matters: Improving Perception and Exploration for Robotics
Projecting high-dimensional environment observations into lower-dimensio...
11/03/2020 ∙ by Markus Wulfmeier, et al. ∙
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Local Search for Policy Iteration in Continuous Control
We present an algorithm for local, regularized, policy improvement in re...
10/12/2020 ∙ by Jost Tobias Springenberg, et al. ∙
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Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB
In this work, we bridge the gap between recent pose estimation and track...
10/30/2019 ∙ by Felix Leeb, et al. ∙
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Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
Humans are masters at quickly learning many complex tasks, relying on an...
10/09/2019 ∙ by Arunkumar Byravan, et al. ∙
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Prospection: Interpretable Plans From Language By Predicting the Future
High-level human instructions often correspond to behaviors with multipl...
03/20/2019 ∙ by Chris Paxton, et al. ∙
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SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control
In this work, we present an approach to deep visuomotor control using st...
10/02/2017 ∙ by Arunkumar Byravan, et al. ∙
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SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks
We introduce SE3-Nets, which are deep neural networks designed to model ...
06/08/2016 ∙ by Arunkumar Byravan, et al. ∙
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