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GitHub3y
walkacross/optimal-control-and-reinforcement-learning - GitHub
Dynamic programming, Hamilton-Jacobi reachability, and direct and indirect methods for trajectory optimization. Introduction to model predictive control. Adaptive control, model-based and model-free ...
www.cs.cmu.edu1mon
16-745: Optimal Control and Reinforcement Learning - CMU School of Computer Science
16-745: Optimal Control and Reinforcement Learning Spring 2020, TT 4:30-5:50 GHC 4303 Instructor: Chris Atkeson, [email protected] TA: Ramkumar Natarajan [email protected], Office hours Thursdays 6-7 ...
IEEE1y
Safe Reinforcement Learning and Adaptive Optimal Control With Applications to Obstacle Avoidance Problem
Next, a safe reinforcement learning framework is proposed by combining model-based policy iteration and state-following-based approximation. Upon real-time data and extrapolated experience data, this ...
IEEE4y
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference | part of Robotics: Science and Systems VIII | MIT Press books - IEEE Xplore
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference Abstract: We present a reformulation of the stochastic optimal control problem in terms of KL divergence minimisation, ...
Scientific Research Publishing15y
Control Task for Reinforcement Learning with Known Optimal Solution for Discrete and Continuous Actions - Scientific Research Publishing
Discover optimal solutions for reinforcement learning in both discrete and continuous action sets. Compare RL solution methods based on value functions. Learn how to solve control tasks with ...
University of Waterloo2y
Reinforcement Learning for Robotic Control | Scholar - University of Waterloo
When I began to study Reinforcement Learning (RL) in robotics, I noted that there was no literature available that reviewed the varying methods of RL for complex, multistep tasks. To solve this issue, ...
GitHub1y
optimal-control-and-reinforcement-learning/README.md at main · walkacross/optimal-control-and-reinforcement-learning - GitHub
The purpose of the book is to consider large and challenging multistage decision problems, which can be solved in principle by dynamic programming and optimal control, but their exact solution is ...
www.cs.cmu.edu10mon
16-745: Optimal Control and Reinforcement Learning - CMU School of Computer Science
16-745: Optimal Control and Reinforcement Learning Spring 2019, TT 3-4:20 NSH 3002 Instructor: Chris Atkeson, cga at cmu TA: Preeti Sar, psar1 at andrew, Office hours Tuesday 7 NSH 4508. Events of ...