Learning Systems and Intelligent Robots

  • K. S. Fu
  • Julius T. Tou

Table of contents

  1. Front Matter
    Pages i-ix
  2. Lester A. Gerhardt, Takatoshi Miura
    Pages 115-144
  3. Moriya Oda, Kahei Nakamura, B. F. Womack
    Pages 145-169
  4. Baxter F. Womack
    Pages 171-190
  5. Setsuzo Tsuji, Kousuke Kumamaru, Naotoshi Maeda, Katsuji Tsuruda
    Pages 191-210
  6. Kahei Nakamura, Yoshimasa Yoshida
    Pages 211-231
  7. Surender K. Gupta, Kuduvally N. Swamy, Tzyh-Jong Tarn, John Zaborszky
    Pages 233-248
  8. Amos Freedy, Gershon Weltman
    Pages 263-271
  9. K. Hanakata
    Pages 317-324
  10. S. Ohteru, H. Kobayashi, T. Kato
    Pages 343-364

About this book

Introduction

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.

Keywords

Pattern Matching algorithms artificial intelligence automata behavior cognition control intelligence learning machine learning modeling pattern recognition robot simulation

Editors and affiliations

  • K. S. Fu
    • 1
  • Julius T. Tou
    • 2
  1. 1.School of Electrical EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.Center for Information ResearchUniversity of FloridaGainesvilleUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4684-2106-4
  • Copyright Information Springer-Verlag US 1974
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4684-2108-8
  • Online ISBN 978-1-4684-2106-4
  • About this book