Skip to main content
SpringerLink
Log in

Learning Systems and Intelligent Robots

  • Book
  • © 1974

Overview

Editors:
  1. K. S. Fu

    1. School of Electrical Engineering, Purdue University, West Lafayette, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Julius T. Tou

    1. Center for Information Research, University of Florida, Gainesville, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (22 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. The Concept of a Linguistic Variable and its Application to Approximate Reasoning

    • L. A. Zadeh
    Pages 1-10

  3. Fundamental Concepts and Social Consequences of Artificial Intelligence

    • Shuhei Aida
    Pages 11-31

  4. Biorobots for Simulation Studies of Learning and Intelligent Controls

    • Tosio Kitagawa
    Pages 33-46

  5. A Mathematical Neuron Model which has a Staircaselike Response Characteristic

    • Jin-ichi Nagumo
    Pages 47-91

  6. Performance Aspects of Stochastic Nonlinear System Classification by Pattern Recognition Methods

    • R. F. Hofstadter, G. N. Saridis
    Pages 93-113

  7. Algorithmic Techniques for Modeling Nonlinear Functions

    • Lester A. Gerhardt, Takatoshi Miura
    Pages 115-144

  8. A Survey of Heuristic Search Method of Multimodal Optimum Point

    • Moriya Oda, Kahei Nakamura, B. F. Womack
    Pages 145-169

  9. Basic Search Patterns in Heuristic Search

    • Baxter F. Womack
    Pages 171-190

  10. Multi-Modal System Identifications by a Learning Procedure

    • Setsuzo Tsuji, Kousuke Kumamaru, Naotoshi Maeda, Katsuji Tsuruda
    Pages 191-210

  11. Learning Dual Control under Complete State Information

    • Kahei Nakamura, Yoshimasa Yoshida
    Pages 211-231

  12. On a Class of Variable-Structure Systems

    • Surender K. Gupta, Kuduvally N. Swamy, Tzyh-Jong Tarn, John Zaborszky
    Pages 233-248

  13. A Method of Learning Control Varying Search Domain by Fuzzy Automata

    • Seizo Kitajima, Kiyoji Asai
    Pages 249-262

  14. Adaptive Computer Aiding in Dynamic Decision Processes

    • Amos Freedy, Gershon Weltman
    Pages 263-271

  15. Optimal Learning Recognizer for Unknown Signal Sets in a Channel with Feedback Link

    • Kokichi Tanaka, Shinichi Tamura
    Pages 273-294

  16. Computational Algorithms for Interactive Pattern Recognition

    • Y. T. Chien
    Pages 295-316

  17. A Methodology for Interactive Systems

    • K. Hanakata
    Pages 317-324

  18. Automatic Recognition of Complex Three-Dimensional Objects from Optical Images

    • Robert B. McGhee
    Pages 325-341

  19. Eyes of the Wabot

    • S. Ohteru, H. Kobayashi, T. Kato
    Pages 343-364

  20. The “Rubber-Mask” Technique-I, Pattern Measurement and Analysis

    • Bernard Widrow
    Pages 365-400
Back to top

Keywords

About this book

This book contains the Proceedings of the S~cond U. S. -Japan Seminar on Learning Control and Intelligent Control. The seminar, held at Gainesville, Florida, from October 22 to 26, 1973, was sponsored by the U. S. -Japan Cooperative Science Program, jointly supported by the National Science Foundation and the Japan Society for the Promotion of Science. The full texts of the twenty-one presented papers are included. The papers cover a variety of topics related to learning control and intelligent control, ranging from pattern recognition to system identification, from learning control to intelligent robots. During the past decade, there has been a considerable increase of interest in problems of machine learning, systems which exhibit learning behavior. In designing a system, if the a priori infor­ mation required is unknown or incompletely known, one approach is to design a system which is capable of learning the unknown infor­ mation during its operation. The learned information will then be used to improve the system's performance. This approach has been used in the design of pattern recognition systems, automatic control systems and system identification algorithms. If we naturally extend our goal to the design of systems which will behave more and more intelligently, learning systems research is only a preliminary step towards a general concept of integrated intelligent systems. One example of this class of systems is the intelligent robot, which integrates pattern recognition. learning and problem-solving into one intelligent system.

Editors and Affiliations

  • School of Electrical Engineering, Purdue University, West Lafayette, USA

    K. S. Fu

  • Center for Information Research, University of Florida, Gainesville, USA

    Julius T. Tou

Bibliographic Information

  • Book Title: Learning Systems and Intelligent Robots

  • Editors: K. S. Fu, Julius T. Tou

  • DOI: https://doi.org/10.1007/978-1-4684-2106-4

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Plenum Press, New York 1974

  • Softcover ISBN: 978-1-4684-2108-8Published: 14 March 2012

  • eBook ISBN: 978-1-4684-2106-4Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: X, 452

  • Topics: Science, Humanities and Social Sciences, multidisciplinary

Publish with us

Policies and ethics

Back to top

Search

Navigation