Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems

By Derong Liu, Qinglai Wei. IEEE Transactions on Neural Networks and Learning Systems, 2014

679 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/66d9de49635c8db4931a903228caa744b972d871

How researchers see this paper

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

In Artificial Intelligence

1. Derong Liu
2. Qinglai Wei
3. Yanhong Luo
4. Huaguang Zhang
5. He Jiang
6. Geyang Xiao
7. Hanquan Lin
8. Biao Luo

In Biomedical Engineering

1. Derong Liu
2. Qinglai Wei
3. Hanquan Lin
4. Huaguang Zhang
5. Yanhong Luo
6. He Jiang
7. Geyang Xiao
8. Bo Zhao

In Computational Theory and Mathematics

1. Derong Liu
2. Qinglai Wei
3. Huaguang Zhang
4. Yanhong Luo
5. Hanquan Lin
6. Biao Luo
7. He Jiang
8. Geyang Xiao

Citations in the corpus

• Data-Driven Optimal Consensus Control for Discrete-Time Multi-Agent Systems With Unknown Dynamics Using Reinforcement Learning Method (2017, methodology): “The proposed online algorithm in this paper is motivated by the idea of PI algorithm [47]–[49].”
• Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems (2016, methodology): “Policy iteration algorithm [68] is a basic iterative ADP algorithm.”
• Adaptive Dynamic Programming for Control: A Survey and Recent Advances (2021, background): “Later, Liu and Wei [72] first described the stability and convergence”