Algorithms to Live By: The Computer Science of Human Decisions
A fascinating exploration of how 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 s...more
- Martin Erwig: Once Upon an Algorithm (if you're more into examples on how to apply algorithms in everyday life)
- Paul Curzon, Peter W. McOwan: The Power Of Computational Thinking (works mostly with examples, puzzles and games)
- Karl Beecher: Computational Thinking (somewhat more technical)
This book spoke volumes to me. I have studied math, and I love math especially applying it to scientific problems. But I have never looked into algorithms, nor have I been taught algorithms. What a shame! I took to the ideas instantly and it all made complete sense - ...more
The book starts out describing the "optimal stopping problem." It is also sometimes called the "secretary hiring problem", and I have seen it applied to dating to find a romantic partner, an ...more
The big picture
We encounter many problems in our daily life, for instance, should I park my car here or proceed with the hope of finding a free spot a bit further? Should I try new restaurants or just stick to good old ones I know? How can I find my life's purpose? What is the fastest way I can sort out my books, hmmm, should I even try sorting out my shelves? How can I best schedule my tasks for maximum productivity and many more routine problems/>The ...more
But, perhaps out of train-wreck curiousity, I picked it up and took a look. The first thing I noticed is that Alison Gopnik gave it a dust jacket endorsement. Ok, you have my full attention n ...more
Brian & Tom enlists findings from computer science to guide us through these. Algorithms here are the shortcuts or even the intuitions that guide us through problems that are intractable at first glance. We, apparently, use them everyday. Brian & Tom are here to document this and to show how exactly we can make th ...more
Some of my favorite principles/concepts:
* 37% rule of "optimal stoppi ...more
Stop on Tinder at 37%.
Use thick markers in brainstorming.
All things being equal, it'll last as long as it's lasted.
But lest you think this is another fluffy brain book, it's actually hard computer programming with the occasional laugh-out-loud line. The team behind it are serious academics who have thought deeply about how computers think and how we can use those algorithms to make our lives easier. Which, when ...more
Wow. I did not expect this book to be this good.
Algorithms to live by is aptly named. The authors use computer science problems to tackle everyday problems that every one of us encounters on a daily basis. How should I schedule my day? How should I organize my files? When I found a parking spot, should I park or should I search a bit more?
All of these problems have a right answer, and people mostly don't know the answer. This book h ...more
I think the following two lines matter:
neighbor <---a highest valued successor of the current.
if value(neighbor)> value(current) then replace current with neighbor.
Now, whether people would execute these two lines or not depends on many things. Sometim ...more
These algorithms are very theoretical. It's impossible to apply them without making all kinds of assumptions that don't seem generally valid in the real world. And the proponents don't test them to see if they work. For example, they've got one on how to find a parking spot. They ask the guy who came up with it how it works for him. He answers "Oh me, I ride a bike." [rimshot]
Also, the ...more
Presenting common algorithms as a way of making decisions in ordinary human affairs seems a lot like the computer-science v ...more
My notes from this book -
(1) Optimal Stopping
(2) Old people don't lose memory - they have so much of it that it slows their system.
(3) Procrastination can be seen as an efficient scheduling problem with wrong priority.
(4) Predictive Models - Gaussian, Power Law, Erlang
(5) Over-fitting - "It really is true that a company will build whatever the CEO decides to measure".
(6) Penalize complexity - ...more
Very interesting and readable book that goes through algorithms that are common in computer science and tech fields, gives a bit of history about them, and then shows ways that they could be applied to every day scenarios.
Since I’ve worked in tech on products up and down the OSI stack, I was familiar with a lot of them though I certainly hadn’t sat down in ...more
This book uses some major algorithms that has been used in computer science and mathematics, and showed their implications for daily decisions.
I enjoyed this book, though I would've loved it, if it had more of a structure, and maybe even exercises, for eager audience.
I tend to not implement algorithms just for the sake of learning a new one and this is not a good thing. When you read these kinds of books you understand why it's so important to know which kinds of algorithms already exists and which problems they solve.
Real hackers (Read Hackers: Heroes of the Computer Revolution) implement their own code just for the sake of learning something new or for the ...more
Writing and storytelling wasn’t perhaps quite as gladwellesque as it could have been, but the content was very illuminating.
I'd highly recommend this book to anyone who starts (or continues) to study computer science. It provides an important connection or grounding, between somewhat dry science and real life and shows how our everyday actions and decisions are described or affected by core CS algorithms.
I listened to it as an audiobook and I'd say that's the only book with the word "algorithm" in its title so far, that is perfectly suitable for the audiobook format. It doesn't have formulas or sour ...more
Griffiths uses various facets of algorithmic problem-solving like sorting, caching, and optimal stopping to convince the reader that step-by-step methods that seem very mechanical in nature are actually extremely useful (or at least “good enough”) for making decisions amid uncertainty.
This is a really great dive into intelligent ...more
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His writing has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, The Paris Review, and in scientific journals such as Cognitive Science. Christian has been featur ...more