Corpus ID: 6085454

Efficient reinforcement learning using Gaussian processes

@inproceedings{Deisenroth2010EfficientRL,
  title={Efficient reinforcement learning using Gaussian processes},
  author={M. Deisenroth},
  year={2010}
}
This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems. [...] Key Method PILCO takes model uncertainties consistently into account during long-term planning to reduce model bias. Second, we propose principled algorithms for robust filtering and smoothing in GP dynamic systems.Expand
Off-policy reinforcement learning with Gaussian processes
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Online reinforcement learning by Bayesian inference
Model-Based Bayesian Sparse Sampling for Data Efficient Control
Multi-Fidelity Reinforcement Learning with Gaussian Processes
Gaussian Processes for Data-Efficient Learning in Robotics and Control
Online Constrained Model-based Reinforcement Learning
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Gaussian Processes in Reinforcement Learning
A Bayesian Framework for Reinforcement Learning
Gaussian process dynamic programming
Adaptive, Cautious, Predictive control with Gaussian Process Priors
State-Space Inference and Learning with Gaussian Processes
Reinforcement learning with Gaussian processes
A Bayesian Sampling Approach to Exploration in Reinforcement Learning
Model-free off-policy reinforcement learning in continuous environment
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