About the Author
Brian Christian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and a New Yorker favorite book of the year. His writing has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, and The Paris Review, as well as in scientific journals such as Cognitive Science, and has been translated into eleven languages. He lives in San Francisco.
Tom Griffiths is a professor of psychology and cognitive science at UC Berkeley, where he directs the Computational Cognitive Science Lab. He has published more than 150 scientific papers on topics ranging from cognitive psychology to cultural evolution, and has received awards from the National Science Foundation, the Sloan Foundation, the American Psychological Association, and the Psychonomic Society, among others. He lives in Berkeley.
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.
画说那些被豆瓣低估了的好书之Algorithms to Live By - 算法优化生活 一本在豆瓣被严重低估的小书,Algorithms to Live By ,中文译名“算法之美”,如何用计算机算法优化生活。虽然书名看起来很深奥,实际上可读性很强,也不需要任何算法基础——应该说,反而更加适合对计算机...
评分一、停车场和麦田 此刻你正在电影院的地下停车场,身边坐着你今天的约会对象。你想把车停得尽量靠近电梯间,但那里的好车位可能已经被别的车占了。这时约会对象示意你旁边就有一个空车位,这里离电梯已经不算远了,但也不太近。你应该停这儿么?还是应该继续往前开?选择前者,...
评分1.从37%法则说起 苏格拉底带领几个弟子来到一块麦地边。他对弟子们说:“你们去麦地里摘一个最大的麦穗,只许前行不能回头,我在麦地的尽头等你们。” 《最大的麦穗》其实就是数学界的“最优停止问题”,要取得最理想的结果,显然需要在两者之间找到最合适的平衡点,在甄选时既...
评分这本书,算法科普得并不清楚,结合生活的部分又很啰嗦。不过这个思路是值得肯定的。有时候编程的时候知道用算法,一到生活中就忘了用。比如第3章“排序”,就提到让东西乱糟糟的有时反而是最高效的。编程的时候都知道,如果以后不搜索或极少搜索,那就没必要排序。但生活中有时...
37%規則:以買房為例,目標一年內,前 37% 的時間只看不買,在預算內了解一下市場上哪些房子你喜歡,哪些不喜歡,記住這個階段內你看到過的最滿意的那個,等到過了 37% 這個時間點,一旦遇到比前一階段那個最好的房子好,或者類似的房子,就毫不猶豫地買下來。數學家的時間管理思維:1. 最近截止日期優先 2. 如果最近截止日期優先法還是做不完,優先放棄佔用時間最長的任務 3. 如果牽涉到別人的等待時間,則完成時間短的任務優先 4. 小事與要事的衡量公式,任務密度 = 重要程度 / 完成時間,然後按照任務的密度由高到低的順序去做。
评分看之前就比较担心是不是太trivial都是已经知道的东西,结果不幸料中。不过也好,打消了我写类似书的想法
评分"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",确实如此,希望我本科时就读过 (不过16年才出来呀...)
评分看到地老天荒,终于在早晨的船上看完了。。
评分37%規則:以買房為例,目標一年內,前 37% 的時間只看不買,在預算內了解一下市場上哪些房子你喜歡,哪些不喜歡,記住這個階段內你看到過的最滿意的那個,等到過了 37% 這個時間點,一旦遇到比前一階段那個最好的房子好,或者類似的房子,就毫不猶豫地買下來。數學家的時間管理思維:1. 最近截止日期優先 2. 如果最近截止日期優先法還是做不完,優先放棄佔用時間最長的任務 3. 如果牽涉到別人的等待時間,則完成時間短的任務優先 4. 小事與要事的衡量公式,任務密度 = 重要程度 / 完成時間,然後按照任務的密度由高到低的順序去做。
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