作者:
Brian Christian
/
Tom Griffiths 出版社: Henry Holt and Co. 副标题: The Computer Science of Human Decisions 出版年: 2016-4-19 页数: 368 定价: USD 30.00 装帧: Hardcover ISBN: 9781627790369
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...
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.
作者简介
· · · · · ·
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 bee...
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.
目录
· · · · · ·
Introduction 1
Algorithms to Live By
1 Optimal Stopping 9
When to Stop Looking
2 Explore/Exploit 31
The Latest vs. the Greatest
· · · · · ·
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Introduction 1
Algorithms to Live By
1 Optimal Stopping 9
When to Stop Looking
2 Explore/Exploit 31
The Latest vs. the Greatest
3 Sorting 59
Making Order
4 Caching 84
Forget About It
5 Scheduling 105
First Things First
6 Bayes’s Rule 128
Predicting the Future
7 Overfitting 149
When to Think Less
8 Relaxation 169
Let It Slide
9 Randomness 182
When to Leave It to Chance
10 Networking 205
How We Connect
11 Game Theory 229
The Minds of Others
Conclusion 256
Computational Kindness
Notes 263
Bibliography 315
Acknowledgments 335
Index 339
· · · · · · (收起)
Algorithm is just a finite sequence of steps used to solve a problem.
Look-then-leap rule: you set a predetermined amount of time for "looking"- that is , exploring your options, gathering data - in which your categorically don't choose anyone, no matter how impressive. After that point, you enter the " leap" phase, prepared to instantly commit to anyone who outshines the best applicant you saw in the look phase. (查看原文)
听NPR的采访知道的这本书，印象是如何用算法帮助你找对象和收拾家。真读了以后感觉那些生活小窍门都是表层，这书的本质是用CS的角度去思考，从解决计算问题延伸到哲学。感触最深的是贝叶斯那章，人们都对prior有很好的直觉，但是这个直觉不停的在被追求吸引眼球的新闻扭曲。尤其现在这个一开电脑一摸手机，简直是一个人一个泡泡的世界里，protect your prior太艰辛了
Sometimes if you feel like you cannot come up with the perfect algorithm, maybe you should relax some constraints and just forget about optimizing for the perfect solution that can only be found in a ...Sometimes if you feel like you cannot come up with the perfect algorithm, maybe you should relax some constraints and just forget about optimizing for the perfect solution that can only be found in a million years (展开)
这本书英文原版的标题是Algorithms to Live By，翻译成中文变成《算法之美》，乍眼一看似乎有点离题，但读完后我觉得英文书名本身有点夸张。理由如下： 1. 人不是机器，没有什么黄金算法可以让你“to live by”而获得完全的确定性和好生活。不能说你遵从了optimal stopping在约...
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很久以前就知道这本书了，不过看着"算法"两字实在没兴趣。直到某天翻Google Talks, 发现作者的讲座很受欢迎，看了看才发现确实很有意思 放在国内的语境下，这本书叫"心智模型"，或model thinker可能好一点 介绍里写 "A fascinating exploration of how insights from computer ...
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从运动联盟排对阵表的角度看几种排序算法的角度倒是新颖。从第六章贝叶斯之后开始起飞了。从 overfitting 飞跃到了进化中的滞后，第七章 randomness 提到的 Monte Carlo 原来是被正经在研究原子弹的时候发明出来的，我当初还觉得自己用它省去了一些数学证明是作弊，turns out s...
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Algorithms to live by: 1. Optimal stopping problem: 37% for apartment hunting: grab the first after that threshold. 2. People don't need therapist, they need an algorithm. 3. Algorithm is not confined to mathematics. It stems from the Stone Age. 4. Science...
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17 有用 滕子京 2016-09-23 13:47:59
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
6 有用 Inari 2018-01-05 04:57:41
听NPR的采访知道的这本书，印象是如何用算法帮助你找对象和收拾家。真读了以后感觉那些生活小窍门都是表层，这书的本质是用CS的角度去思考，从解决计算问题延伸到哲学。感触最深的是贝叶斯那章，人们都对prior有很好的直觉，但是这个直觉不停的在被追求吸引眼球的新闻扭曲。尤其现在这个一开电脑一摸手机，简直是一个人一个泡泡的世界里，protect your prior太艰辛了
1 有用 綦 2019-03-17 10:01:32
Have you updated your OS today yet? #wethebots
7 有用 Lily 2017-05-18 03:47:18
《指导生活的算法》 生活中的很多复杂决策，看上去没有规律可循，实际上是可以用算法来解决的。e.g.找对象用到的37%法则 很多时候我们会沉迷在细节里，看不清大方向，其实是犯了数学上的过度拟合错误。 时间问题本质上是个数学问题，用数学家的办法管理时间，才能活得更有效率。
2 有用 Amo Wu 2018-02-09 22:11:53
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，... 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。 (展开)
0 有用 瓦屋瓦屋鸦一夜 2024-04-14 19:38:18 北京
既不深入，也不浅出。读后除了了解知道一些名字概念，什么也没有剩下。
0 有用 momo 2024-03-21 00:27:05 上海
只讲结论不讲证明
0 有用 uss enterprise 2024-03-13 15:22:43 美国
写的太好了，很多之前感觉有点陈词滥调的问题（比如exploit/explore)读了这本书之后都觉得耳目一新! Tom Griffith太强了还有啥是你不会的吗！
0 有用 喜乐 2024-03-05 01:48:36 美国
因为公司内网CTO的推荐而读的，结果比想象中要有趣，读起来煞有兴味。是很容易理解和运用的数据和模型，但就和bezos的那个例子一样，人生遗憾无限，但是可以以自己的模型降到最少。
0 有用 Sandy'Y 2024-02-28 11:17:59 美国
Sometimes if you feel like you cannot come up with the perfect algorithm, maybe you should relax some constraints and just forget about optimizing for the perfect solution that can only be found in a ... Sometimes if you feel like you cannot come up with the perfect algorithm, maybe you should relax some constraints and just forget about optimizing for the perfect solution that can only be found in a million years (展开)