Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Optimal Control of Unknown Nonlinear Discrete-Time Systems Using the Iterative Globalized Dual Heuristic Programming Algorithm

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) || 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) || Bounds for Markov Decision Processes

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 137 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) || Reinforcement Learning and Approximate Dynamic Programming (RLADP)-Foundations, Common Misconceptions, and the Challenges Ahead

✍ Lewis, Frank L.; Liu, Derong 📂 Article 📅 2013 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 147 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) || 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 Dynamic Programming for Feedback Control (Lewis/Reinforcement Learning and Approximate Dynamic Programming for Feedback Control) || Optimal Control of Unknown Nonlinear Discrete-Time Systems Using the Iterative Globalized Dual Heuristic Programming Algorithm

✦ Synopsis