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Plan Prediction

Which Policy is Preferred by Which People?

  • Ray Wyatt

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Common Sense Plan Prediction

    1. Front Matter
      Pages 1-1
    2. Ray Wyatt
      Pages 3-29
    3. Ray Wyatt
      Pages 31-64
    4. Ray Wyatt
      Pages 65-96
  3. Plan-Prediction Parameters

    1. Front Matter
      Pages 97-97
    2. Ray Wyatt
      Pages 99-126
    3. Ray Wyatt
      Pages 127-159
    4. Ray Wyatt
      Pages 161-184
  4. A Plan-Prediction System

    1. Front Matter
      Pages 185-185
    2. Ray Wyatt
      Pages 187-211
    3. Ray Wyatt
      Pages 213-242
    4. Ray Wyatt
      Pages 243-266
  5. Back Matter
    Pages 267-276

About this book

Introduction

This book develops an innovative system, in the form of an "app", that harnesses the power of the internet to predict which sorts of people will prefer which policy in ANY planning situation.

It chronicles the accumulated research wisdom behind the system’s reasoning, along with several less successful approaches to policy making that have been found wanting in the past – including the myth, usually peddled by strategic planners, that it is possible to find a "best" plan which optimally satisfies everybody.

The book lays out an entirely new kind of Planning Support System (PSS). It will facilitate decision-making that is far more community-sensitive than previously, and it will drastically improve the performance of anyone who needs to plan within socially-sensitive contexts – which is all of us.

A standout feature of the system is its commitment to “scientific rigour”, as shown by its predicted plan scores always being graphically presented within error margins so that true statistical significance is instantly observable. Moreover, the probabilities that its predictions are correct are always shown  – a refreshing change from most, if not all other Decision Support Systems (DSS) that simply expect users to accept their outputs on faith alone.

Keywords

Plan Evaluation Planning Support Systems Machine Learning Plan Prediction Plans

Authors and affiliations

  • Ray Wyatt
    • 1
  1. 1.School of GeographyThe University of MelbourneMelbourneAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-46430-5
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-46429-9
  • Online ISBN 978-3-319-46430-5
  • Buy this book on publisher's site