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Found 2 papers, 1 papers with code
Learning Robust Controllers Via Probabilistic Model-Based Policy Search
Model-based Reinforcement Learning estimates the true environment through a world model in order to approximate the optimal policy.
Model-based Reinforcement Learning
reinforcement-learning
+1
Probabilistic selection of inducing points in sparse Gaussian processes
Sparse Gaussian processes and various extensions thereof are enabled through inducing points, that simultaneously bottleneck the predictive capacity and act as the main contributor towards model complexity.
