no code implementations • 2 Apr 2024 • Ya-Chien Chang, Sicun Gao
Reinforcement learning for control over continuous spaces typically uses high-entropy stochastic policies, such as Gaussian distributions, for local exploration and estimating policy gradient to optimize performance.
1 code implementation • NeurIPS 2019 • Ya-Chien Chang, Nima Roohi, Sicun Gao
We propose new methods for learning control policies and neural network Lyapunov functions for nonlinear control problems, with provable guarantee of stability.
