Computing Possible Futures

William B Rouse author

Format:Hardback

Publisher:Oxford University Press

Published:12th Sep '19

Currently unavailable, and unfortunately no date known when it will be back

Computing Possible Futures cover

Mathematical modelling and simulation is an increasingly powerful area of mathematics and computer science, which in recent years has been fuelled by the unprecedented access to larger than ever stores of data. These techniques have an increasing number of applications in the professional and political spheres, and people try to predict the results of certain courses of action as accurately as possible. Computing Possible Futures explores the use of models on everyday phenomena such as waiting in lines and driving a car, before expanding the model's complexity to look at how large-scale computational models can help imagine big scale "what-if" scenarios like the effect self-driving cars on the US economy. The successes and failures of complex real world problems are examined, and it is shown how few, if any, failures are due to model errors or computational difficulties. It is also shown how real life decision makers have addressed important problems and used their model-based understanding of possible futures to inform these decisions. Written in an entertaining and accessible way, Computing Possible Futures will help those concerned about the futurity of their decisions to understand what fundamentally needs to be done, why it needs to be done, and how to do it.

A must read for everyone who has ever wondered 'What If?' and felt unprepared to rigorously generate possible answers ... The chapter on intelligent systems is especially timely, and covers artificial intelligence and machine learning from a fresh perspective. * Jim Spohrer, Director, Cognitive OpenTech at IBM *
Computing Possible Futures provides a compelling approach to systems thinking, as well as an array of tools for exploring what might happen and leading indicators of likely futures. * Denis A. Cortese MD, Foundation Professor, Arizona State University *
The hope is that readers will discuss this book and develop a 'shared mental model' of computational modeling in the process, which will greatly enhance their chances of success. * MathSciNet *

ISBN: 9780198846420

Dimensions: 238mm x 161mm x 18mm

Weight: 502g

202 pages