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Response Models for Detection of Change

  • Amnon Rapoport
  • William E. Stein
  • Graham J. Burkheimer

Part of the Theory and Decision Library book series (TDLU, volume 18)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 1-15
  3. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 16-31
  4. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 32-63
  5. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 64-80
  6. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 81-102
  7. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 103-118
  8. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 119-147
  9. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 147-167
  10. Amnon Rapoport, William E. Stein, Graham J. Burkheimer
    Pages 168-179
  11. Back Matter
    Pages 180-201

About this book

Introduction

This book reports our research on detection of change processes that underlie psychophysical, learning, medical diagnosis, military, and pro­ duction control situations, and share three major features. First, the states of the process are not directly observable but become gradually known with the sequential acquisition of fallible information over time. Second, the mechanism that generates the fallible information is not stationary; rather, it is subjected to a sudden and irrevocable change. Thirdly, in­ complete, probabilistic information about the time of change is available when the process commences. The purpose of the book is to characterize this class of detection of change processes, to derive the optimal policy that minimizes total expected loss, and, most importantly, to develop testable response models, based on simple decision rules, for describing detection of change behavior. The book is theoretical in the sense that it offers mathematical models of multi-stage decision behavior and solutions to optimization problems. However, it is not anti-empirical, as it aims to stimulate new experimental research and to generate applications. Throughout the book, questions of experimental verification are briefly considered, and existing data from two studies are brought to bear on the validity of the models. The work is not complete; it only provides a starting point for investigating how people detect a change in an uncertain environment, balancing between the cost of delay in detecting the change and the cost of making an incor­ rect terminal decision.

Keywords

decision theory evaluation experiment information nature research state statistics

Authors and affiliations

  • Amnon Rapoport
    • 1
  • William E. Stein
    • 2
  • Graham J. Burkheimer
    • 3
  1. 1.University of North CarolinaChapel HillUSA
  2. 2.Texas Christian UniversityUSA
  3. 3.Research Triangle InstituteUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-009-9386-0
  • Copyright Information Springer Science+Business Media B.V. 1979
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-009-9388-4
  • Online ISBN 978-94-009-9386-0
  • Buy this book on publisher's site
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