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Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions
Trajectory optimization and model predictive control are essential techn...
03/29/2021 ∙ by Hany Abdulsamad, et al. ∙
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A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning
Across machine learning, the use of curricula has shown strong empirical...
02/25/2021 ∙ by Pascal Klink, et al. ∙
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A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning
Probabilistic regression techniques in control and robotics applications...
11/10/2020 ∙ by Hany Abdulsamad, et al. ∙
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Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation
The control of nonlinear dynamical systems remains a major challenge for...
05/04/2020 ∙ by Hany Abdulsamad, et al. ∙
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A Nonparametric Offpolicy Policy Gradient
Reinforcement learning (RL) algorithms still suffer from high sample com...
01/08/2020 ∙ by Samuele Tosatto, et al. ∙
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Receding Horizon Curiosity
Sample-efficient exploration is crucial not only for discovering rewardi...
10/08/2019 ∙ by Matthias Schultheis, et al. ∙
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Stochastic Optimal Control as Approximate Input Inference
Optimal control of stochastic nonlinear dynamical systems is a major cha...
10/07/2019 ∙ by Joe Watson, et al. ∙
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Self-Paced Contextual Reinforcement Learning
Generalization and adaptation of learned skills to novel situations is a...
10/07/2019 ∙ by Pascal Klink, et al. ∙
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