Open access peer-reviewed Edited Volume

Reinforcement Learning

Edited by Cornelius Weber

University of Hamburg, Germany


Mark Elshaw

University of Sunderland

N. Michael Mayer

National Chung Cheng University, Taiwan

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field.

Read more >Order hardcopy
Reinforcement LearningEdited by Cornelius Weber

Published: January 1st 2008

DOI: 10.5772/54

ISBN: 978-3-902613-14-1

eBook (PDF) ISBN: 978-953-51-5821-9

Copyright year: 2008

Books open for chapter submissions

95461 Total Chapter Downloads

25 Crossref Citations

68 Web of Science Citations

68 Dimensions Citations


Open access peer-reviewed

1. Neural Forecasting Systems

By Takashi Kuremoto, Masanao Obayashi and Kunikazu Kobayashi


Open access peer-reviewed

2. Reinforcement Learning in System Identification

By Mariela Cerrada and Jose Aguilar


Open access peer-reviewed

3. Reinforcement Evolutionary Learning for Neuro-Fuzzy Controller Design

By Cheng-Jian Lin


Open access peer-reviewed

4. Superposition-Inspired Reinforcement Learning and Quantum Reinforcement Learning

By Chun-Lin Chen and Dao-Yi Dong


Open access peer-reviewed

5. An Extension of Finite-state Markov Decision Process and an Application of Grammatical Inference

By Takeshi Shibata and Ryo Yoshinaka


Open access peer-reviewed

6. Interaction Between the Spatio-Temporal Learning Rule (Non Hebbian) and Hebbian in Single Cells: A Cellular Mechanism of Reinforcement Learning

By Minoru Tsukada


Open access peer-reviewed

7. Reinforcement Learning Embedded in Brains and Robots

By Cornelius Weber, Mark Elshaw, Stefan Wermter, Jochen Triesch and Christopher Willmot


Open access peer-reviewed

8. Decentralized Reinforcement Learning for the Online Optimization of Distributed Systems

By Jim Dowling and Seif Haridi


Open access peer-reviewed

9. Multi-Automata Learning

By Verbeeck Katja, Nowe Ann, Vrancx Peter and Peeters Maarten


Open access peer-reviewed

10. Abstraction for Genetics-Based Reinforcement Learning

By Will Browne, Dan Scott and Charalambos Ioannides


Open access peer-reviewed

11. Dynamics of the Bush-Mosteller Learning Algorithm in 2x2 Games

By Luis R. Izquierdo and Segismundo S. Izquierdo


Open access peer-reviewed

12. Modular Learning Systems for Behavior Acquisition in Multi-Agent Environment

By Yasutake Takahashi and Minoru Asada


Open access peer-reviewed

13. Optimising Spoken Dialogue Strategies within the Reinforcement Learning Paradigm

By Olivier Pietquin


Open access peer-reviewed

14. Water Allocation Improvement in River Basin Using Adaptive Neural Fuzzy Reinforcement Learning Approach

By Abolpour B., Javan M. and Karamouz M.


Open access peer-reviewed

15. Reinforcement Learning for Building Environmental Control

By Konstantinos Dalamagkidis and Dionysia Kolokotsa


Open access peer-reviewed

16. Model-Free Learning Control of Chemical Processes

By S. Syafiie, F. Tadeo and E. Martinez


Open access peer-reviewed

17. Reinforcement Learning-Based Supervisory Control Strategy for a Rotary Kiln Process

By Xiaojie Zhou, Heng Yue and Tianyou Chai


Open access peer-reviewed

18. Inductive Approaches Based on Trial/Error Paradigm for Communications Network

By Abdelhamid Mellouk


Open access peer-reviewed

19. The Allocation of Time and Location Information to Activity-Travel Sequence Data by Means of Reinforcement Learning

By Wets Janssens


Open access peer-reviewed

20. Application on Reinforcement Learning for Diagnosis Based on Medical Image

By Stelmo Magalhaes Barros Netto, Vanessa Rodrigues Coelho Leite, Aristofanes Correa Silva, Anselmo Cardoso de Paiva and Areolino de Almeida Neto


Open access peer-reviewed

21. RL Based Decision Support System for u-Healthcare Environment

By Devinder Thapa, In-Sung Jung and Gi-Nam Wang


Open access peer-reviewed

22. Reinforcement Learning to Support Meta-Level Control in Air Traffic Management

By Daniela P. Alves, Li Weigang and Bueno B. Souza


Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

Order a hardcopy of the Edited Volume

Free shipping with DHL Express

Hardcover (ex. VAT)£139

Order now

Residents of European Union countries need to add a Book Value-Added Tax Rate based on their country of residence. Institutions and companies, registered as VAT taxable entities in their own EU member state, will not pay VAT by providing IntechOpen with their VAT registration number. This is made possible by the EU reverse charge method.

Special discount for IntechOpen contributors

All IntechOpen contributors are offered special discounts starting at 40% OFF available through your personal dashboard

Login and purchase