Adaptive Feedback Control by Constrained Approximate Dynamic Programming

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || A Constrained Backpropagation Approach to Function Approximation and Approximate Dynamic Programming

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 334 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Stable Adaptive Neural Control of Partially Observable Dynamic Systems

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 335 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Frontmatter

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 215 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Learning and Optimization in Hierarchical Adaptive Critic Design

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 749 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Linearly Solvable Optimal Control

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 307 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single

Reinforcement Learning and Approximate D

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Single Network Adaptive Critics Networks-Development, Analysis, and Applications

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 343 KB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single