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Found 3 papers, 1 papers with code
Constrained Reinforcement Learning with Smoothed Log Barrier Function
However, for many real-world problems, it is often more convenient to formulate optimization problems in terms of rewards and constraints simultaneously.
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
The combination of Reinforcement Learning (RL) with deep learning has led to a series of impressive feats, with many believing (deep) RL provides a path towards generally capable agents.
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
We demonstrate that this problem can be tackled effectively with automated HPO, which we demonstrate to yield significantly improved performance compared to human experts.
Hyperparameter Optimization
Model-based Reinforcement Learning
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