Bibliograph

Algorithms to live by, the computer science of human decisions, Brian Christian and Tom Griffiths

Type

Label

Algorithms to live by, the computer science of human decisions, Brian Christian and Tom Griffiths

Language

eng

Bibliography note

Includes bibliographical references and index

Index

index present

Literary Form

non fiction

Main title

Algorithms to live by

Nature of contents

bibliography

Oclc number

908628787

Responsibility statement

Brian Christian and Tom Griffiths

Sub title

the computer science of human decisions

Summary

A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind. All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.--From dust jacket

Table Of Contents

Optimal stopping : when to stop looking -- Explore/exploit : the latest vs. the greatest -- Sorting : making order -- Caching : forget about it -- Scheduling : first things first -- Bayes's Rule : predicting the future -- Overfitting : when to think less -- Relaxation : let it slide -- Randomness : when to leave it to chance -- Networking : how we connect -- Game theory : the minds of others -- Conclusion : computational kindness

Classification

Contributor