Safe Policy Search with Gaussian Process Models
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Abstract (arXiv)
We propose a method to optimise the parameters of a policy which will be used to safely perform a given task in a data-efficient manner. We train a Gaussian process model to capture the system dynamics, based on the PILCO framework. Our model has useful analytic properties, which allow closed form computation of error gradients and estimating the probability of violating given state space constraints. During training, as well as operation, only policies that are deemed safe are implemented on the real system, minimising the risk of failure.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Dec 2017.
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Citing papers per year: 2020: 1; 2021: 2; 2022: 2; 2023: 1; 2024: 3.
9 papers.
- 2022A Review of Safe Reinforcement Learning: Methods, Theory and Applicationscited by 169
- 2024Enhancing LLM Safety via Constrained Direct Preference Optimizationcited by 47
- 2022Lexicographic Multi-Objective Reinforcement Learningcited by 17
- 2024Constrained Reinforcement Learning with Smoothed Log Barrier Functioncited by 12
- 2021Certification of Iterative Predictions in Bayesian Neural Networkscited by 8
- 2023Probabilistic Reach-Avoid for Bayesian Neural Networkscited by 4
- 2021Learning Robust Controllers Via Probabilistic Model-Based Policy Searchcited by 1
- 2024Constrained Reinforcement Learning for Safe Heat Pump Controlcited by 1
- 2020MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreascited by 0
- 2024Constrained Reinforcement Learning for Safe Heat Pump Control29 Sep 2024
- 2024Constrained Reinforcement Learning with Smoothed Log Barrier Function21 Mar 2024
- 2024Enhancing LLM Safety via Constrained Direct Preference Optimization4 Mar 2024
- 2023Probabilistic Reach-Avoid for Bayesian Neural Networks3 Oct 2023
- 2022Lexicographic Multi-Objective Reinforcement Learning28 Dec 2022
- 2022A Review of Safe Reinforcement Learning: Methods, Theory and Applications20 May 2022
- 2021Learning Robust Controllers Via Probabilistic Model-Based Policy Search26 Oct 2021
- 2021Certification of Iterative Predictions in Bayesian Neural Networks21 May 2021
- 2020MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas3 Mar 2020