Adaptive Dynamic Programming Control

Adaptive Dynamic Programming Control is a research topic within Computational Theory and Mathematics. Science Explorer counts 8k research works in it since 1965. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of Adaptive Dynamic Programming and Reinforcement Learning techniques to solve optimal control problems in continuous-time nonlinear systems. It explores the use of neural networks, policy iteration, actor-critic algorithms, and $H_{infty}$ control for online learning and feedback control in various domains such as robotics, energy management, and multi-agent systems.

• Adaptive Dynamic Programming
• Reinforcement Learning
• Optimal Control
• Neural Networks
• Continuous-Time Systems
• Nonlinear Systems
• Policy Iteration
• Actor-Critic Algorithm
• $H_{infty}$ Control
• Online Learning