Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles

By Draguna L. Vrabie, Kyriakos G. Vamvoudakis, Frank L. Lewis. 2012

270 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Jan Muzík
2. Fred Godtliebsen
3. Phuong D. Ngo
4. Anna Holubová
5. Susan Wei

Citations in the corpus

• A Reinforcement Learning–Based Method for Management of Type 1 Diabetes: Exploratory Study (2019, positive): “Vrabie et al (2018) and 2 studies by Ngo et al (2018) applied a model-based RL algorithm for controlling blood glucose for type 1 Diabetes [22-24].”
• Control of Blood Glucose for Type-1 Diabetes by Using Reinforcement Learning with Feedforward Algorithm (2018, methodology): “Comparisons were made between the proposed reinforcement learning with the feedforward (RLFF) controller, the optimal RL (ORL) controller [15], and the proportional-integral-derivative (PID) controller.”
• Reinforcement-learning optimal control for type-1 diabetes (2018, methodology): “[6] provide techniques to obtain optimal adaptive control algorithms for dynamical systems with unknown mathematical models by using reinforcement learning.”
• Nonlinear control systems - A brief overview of historical and recent advances (2017, background): “10: Actor-Critic Structure for reinforcement learning scheme [88]”