Reinforcement learning and approximate dynamic programming for feedback control
by Lewis, Frank L. Liu, Derong
"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 player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely gu…
Read More ↓Title Statements
- Full title :Reinforcement learning and approximate dynamic programming for feedback control / edited by Frank L. Lewis, U TA Automation and Robotics Research Insitute, Derong Liu, University of Illinois, Chicago, IL.
Summary
"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 player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making"--
"Reinforcement learning and adaptive control can be useful for controlling a wide variety of systems including robots, industrial processes, and economical decision making"--
Edition Statements
- Publication Date:2013.
Publication Statements
- Publisher(s):IEEE Press, John Wiley and Sons, Inc
- Place of Publication:Piscataway, NJ
- Language:eng
- Publication Date:2013.
The Physical Object
- Description:1 online resource (xxvi, 613 pages :) : illustrations.
Edition Identifiers
- ISBN:9781118104200, 111810420X
- oclc:on1340070974
- LC Classification:Q325.6
- Dewey Decimal:003/.5
Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Related Works
more →
Reinforcement learning and stochastic optimization: a unified framework for sequential deci…
Powell, Warren B.
Human-robot interaction control using reinforcement learning
Yu, Wen, (Robotics engineer)
Multi-Agent Machine Learning
Reinforcement learning algorithms: analysis and applications
Reinforcement learning for cyber-physical systems with cybersecurity case studi…
Li, Chong
Reinforcement learning for cyber-physical systems with cybersecurity case studi…
Li, Chong
Reinforcement learning for cyber-physical systems with cybersecurity case studi…
Li, Chong
Hands-on reinforcement learning for games: implementing self-learning agents in ga…
Lanham, Micheal
Hands-on reinforcement learning for games: implementing self-learning agents in ga…
Lanham, Micheal
Files & Downloads
-
Reinforcement Learning and Approximate Dynamic Pr…
PDF · 44.5 MB · updated -
Reinforcement Learning and Approximate Dynamic Pr…
EPUB · 7.2 MB · updated
Rate & Review