Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian - Book Summary - Readtrepreneur (Disclaimer: This is NOT the original book, but an unofficial summary.)
Have you ever thought how can we incorporate computer algorithms into our day-to-day problem solving? Could it bring good results? Algorithms to Live By offers us a peculiar but effective way of seeing the world. Everyday we encounter a different set of problems that need solving, Brian Christian claims that we should try to ponder about our daily issues as a computer would when solving problems. With a simpler and more organized way of tackling situations that we face everyday, you can manage to solve them easily and obtain better results.
(Note: This summary is wholly written and published by Readtrepreneur. It is not affiliated with the original author in any way)
"We say 'brain fart' when we should really say 'cache miss'." - Brian Christian.
Algorithms to live by possesses the two qualities that are key for a good book; an amusing factor and meaning. It truly is an entertaining read because of Brian Christian's funny ways of phrasing his analogies and how practical his teachings are. The book manages to keep you entertained while he walks you through a more efficient method of thinking. Brian Christian stresses that thinking in algorithms is using your brain in the best possible way.
P.S. Algorithms to Live By is a brilliant book that will completely change the way you solve problems. With a simpler and more elegant train of thought, your odds of obtaining the best result possible when problem solving is significantly higher.
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Chapter 1. Optimal Stopping – When to Stop Looking
One thing that makes life difficult is not knowing when to stop – this has been labeled as the Optimal Stopping Problem. There is a danger of quitting too early and missing out on something good, or quitting too late and exhausting the little energy and time that we have.
Thankfully, there is an algorithm that will make decisions much easier. It’s not entirely foolproof, but it will produce better outcomes than doing things randomly.
The Optimal Stopping Problem deals not with what option to select but how many choices to consider. Based on statistical data, the ideal percentage is 37%.
The Secretary Problem explores the idea of Optimal Stopping. Someone tasked to hire a secretary has to choose among applicants, but he must know when to stop so that he will not miss someone who is good for the job.
In looking for the secretary, stopping late means prolonging the choice unnecessarily, while stopping too early lets the best applicant go unhired. The strategy is to find a reasonable balance between the two conditions.
