Adaptive Information Processing

An Introductory Survey

  • Jeffrey R. Sampson

Part of the Texts and Monographs in Computer Science book series (MCS)

Table of contents

  1. Front Matter
    Pages i-x
  2. Introduction

    1. Jeffrey R. Sampson
      Pages 1-3
  3. Information and automata

    1. Front Matter
      Pages 5-6
    2. Jeffrey R. Sampson
      Pages 7-15
    3. Jeffrey R. Sampson
      Pages 16-24
    4. Jeffrey R. Sampson
      Pages 25-39
    5. Jeffrey R. Sampson
      Pages 40-55
    6. Jeffrey R. Sampson
      Pages 56-66
  4. Biological Information Processing

    1. Front Matter
      Pages 67-68
    2. Jeffrey R. Sampson
      Pages 69-84
    3. Jeffrey R. Sampson
      Pages 85-95
    4. Jeffrey R. Sampson
      Pages 96-106
    5. Jeffrey R. Sampson
      Pages 107-117
    6. Jeffrey R. Sampson
      Pages 118-126
  5. Artificial intelligence

    1. Front Matter
      Pages 127-128
    2. Jeffrey R. Sampson
      Pages 129-145
    3. Jeffrey R. Sampson
      Pages 146-159
    4. Jeffrey R. Sampson
      Pages 160-174
    5. Jeffrey R. Sampson
      Pages 175-189
    6. Jeffrey R. Sampson
      Pages 190-207
  6. Back Matter
    Pages 208-214

About this book


This book began as a series of lecture notes for a course called Introduc­ tion to Adaptive Systems which I developed for undergraduate Computing Science majors at the University of Alberta and first taught in 1973. The objective of the course has been threefold: (l) to expose undergraduate computer scientists to a variety of subjects in the theory and application of computation, subjects which are too often postponed to the graduate level or never taught at all; (2) to provide undergraduates with a background sufficient to make them effective participants in graduate level courses in Automata Theory, Biological Information Processing, and Artificial Intelligence; and (3) to present a personal viewpoint which unifies the apparently diverse aspects of the subject matter covered. All of these goals apply equally to this book, which is primarily designed for use in a one semester undergraduate computer science course. I assume the reader has a general knowledge of computers and programming, though not of particular machines or languages. His mathematical background should include basic concepts of number systems, set theory, elementary discrete probability, and logic.


Information Processing artificial intelligence automata computer computer science probability programming

Authors and affiliations

  • Jeffrey R. Sampson
    • 1
  1. 1.Department of Computing ScienceThe University of AlbertaEdmontonCanada

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1976
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-85503-0
  • Online ISBN 978-3-642-85501-6
  • Series Print ISSN 0172-603X
  • Buy this book on publisher's site