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Handbook of learning and approximate dynamic programming /

. A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code. Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book. Includes ideas, directions, and recent results on current research issues and addresses appl...

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Bibliographic Details
Other Authors: Si, Jennie
Format: eBook
Language:English
Language Notes:English.
Published: Hoboken, NJ : IEEE Press : Wiley-Interscience, ©2004.
Series:IEEE series on computational intelligence ; 2.
Subjects:
Dynamic programming.
Automatic programming (Computer science)
Machine learning.
Control theory.
Systems engineering.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Matter
  • Foreword / Shankar Sastry
  • ADP: Goals, Opportunities and Principles / Paul Werbos
  • Overview. Reinforcement Learning and Its Relationship to Supervised Learning / Andrew G Barto, Thomas G Dietterich
  • Model-Based Adaptive Critic Designs / Silvia Ferrari, Robert F Stengel
  • Guidance in the Use of Adaptive Critics for Control / George G Lendaris, James C Neidhoefer
  • Direct Neural Dynamic Programming / Jennie Si, Lei Yang, Derong Liu
  • The Linear Programming Approach to Approximate Dynamic Programming / Daniela Pucci de Farias
  • Reinforcement Learning in Large, High-Dimensional State Spaces / Greg Grudic, Lyle Ungar
  • Hierarchical Decision Making / Malcolm Ryan
  • Technical Advances. Improved Temporal Difference Methods with Linear Function Approximation / Dimitri P Bertsekas, Vivek S Borkar, Angelia Nedich
  • Approximate Dynamic Programming for High-Dimensional Resource Allocation Problems / Warren B Powell, Benjamin Van Roy
  • Hierarchical Approaches to Concurrency, Multiagency, and Partial Observability / Sridhar Mahadevan, Mohammad Ghavamzadeh, Khashayar Rohanimanesh, Georgias Theocharous
  • Learning and Optimization
  • From a System Theoretic Perspective / Xi-Ren Cao
  • Robust Reinforcement Learning Using Integral-Quadratic Constraints / Charles W Anderson, Matt Kretchmar, Peter Young, Douglas Hittle
  • Supervised Actor-Critic Reinforcement Learning / Michael T Rosenstein, Andrew G Barto
  • BPTT and DAC
  • A Common Framework for Comparison / Danil V Prokhorov
  • Applications. Near-Optimal Control Via Reinforcement Learning and Hybridization / Augustine O Esogbue, Warren E Hearnes
  • Multiobjective Control Problems by Reinforcement Learning / Dong-Oh Kang, Zeungnam Bien
  • Adaptive Critic Based Neural Network for Control-Constrained Agile Missile / S N Balakrishnan, Dongchen Han
  • Applications of Approximate Dynamic Programming in Power Systems Control / Ganesh K Venayagamoorthy, Donald C Wunsch, Ronald G Harley
  • Robust Reinforcement Learning for Heating, Ventilation, and Air Conditioning Control of Buildings / Charles W Anderson, Douglas Hittle, Matt Kretchmar, Peter Young
  • Helicopter Flight Control Using Direct Neural Dynamic Programming / Russell Enns, Jennie Si
  • Toward Dynamic Stochastic Optimal Power Flow / James A Momoh
  • Control, Optimization, Security, and Self-healing of Benchmark Power Systems / James A Momoh, Edwin Zivi
  • Bibliography
  • Index.