Integral \(Q\)-learning and explorized policy iteration for adaptive optimal control of continuous-time linear systems
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Publication:694822
DOI10.1016/j.automatica.2012.06.008zbMath1254.49019OpenAlexW2087063454MaRDI QIDQ694822
Jin Bae Park, Yoon Ho Choi, Jae Young Lee
Publication date: 13 December 2012
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2012.06.008
Learning and adaptive systems in artificial intelligence (68T05) Linear-quadratic optimal control problems (49N10)
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Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Model-free \(Q\)-learning designs for linear discrete-time zero-sum games with application to \(H^\infty\) control
- Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem
- Adaptive optimal control for continuous-time linear systems based on policy iteration
- \({\mathcal Q}\)-learning
- A note on persistency of excitation
- Dynamic programming and suboptimal control: a survey from ADP to MPC
- Approximate Dynamic Programming
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