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Differentiable Trust Region Layers for Deep Reinforcement Learning
Trust region methods are a popular tool in reinforcement learning as the...
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Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning
Estimating accurate forward and inverse dynamics models is a crucial com...
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Imitation Learning for Autonomous Trajectory Learning of Robot Arms in Space
This work adds on to the on-going efforts to provide more autonomy to sp...
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Non-Adversarial Imitation Learning and its Connections to Adversarial Methods
Many modern methods for imitation learning and inverse reinforcement lea...
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Probabilistic approach to physical object disentangling
Physically disentangling entangled objects from each other is a problem ...
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Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
Modelling highly multi-modal data is a challenging problem in machine le...
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Trust-Region Variational Inference with Gaussian Mixture Models
Many methods for machine learning rely on approximate inference from int...
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Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
In order to integrate uncertainty estimates into deep time-series modell...
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Compatible Natural Gradient Policy Search
Trust-region methods have yielded state-of-the-art results in policy sea...
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An Algorithmic Perspective on Imitation Learning
As robots and other intelligent agents move from simple environments and...
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Adaptation and Robust Learning of Probabilistic Movement Primitives
Probabilistic representations of movement primitives open important new ...
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Towards Fine Grained Network Flow Prediction
One main challenge for the design of networks is that traffic load is no...
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Deep Reinforcement Learning for Swarm Systems
Recently, deep reinforcement learning (RL) methods have been applied suc...
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Learning Complex Swarm Behaviors by Exploiting Local Communication Protocols with Deep Reinforcement Learning
Swarm systems constitute a challenging problem for reinforcement learnin...
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Guided Deep Reinforcement Learning for Swarm Systems
In this paper, we investigate how to learn to control a group of coopera...
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Policy Search with High-Dimensional Context Variables
Direct contextual policy search methods learn to improve policy paramete...
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