Highlights from Algorithms to Live By: The Computer Science of Human Decisions (Christian, Brian)

The highlights bellow are just a short list of the total I collected. This post will be updated over time with more highlights.

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finding an apartment belongs to a class of mathematical problems known as “optimal stopping” problems. The 37% rule defines a simple series of steps—what computer scientists call an “algorithm”—for solving these problems. And as it turns out, apartment hunting is just one of the ways that optimal stopping rears its head in daily life. Committing to or forgoing a succession of options is a structure that appears in life again and again, in slightly different incarnations. How many times to circle the block before pulling into a parking space? How far to push your luck with a risky business venture before cashing out? How long to hold out for a better offer on that house or car?

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They don’t need a therapist; they need an algorithm. The therapist tells them to find the right, comfortable balance between impulsivity and overthinking. The algorithm tells them the balance is thirty-seven percent.

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Optimal stopping tells us when to look and when to leap. The explore/exploit tradeoff tells us how to find the balance between trying new things and enjoying our favorites. Sorting theory tells us how (and whether) to arrange our offices. Caching theory tells us how to fill our closets. Scheduling theory tells us how to fill our time.

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exploration is gathering information, and exploitation is using the information you have to get a known good result.

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When balancing favorite experiences and new ones, nothing matters as much as the interval over which we plan to enjoy them. “I’m more likely to try a new restaurant when I move to a city than when I’m leaving it,”

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sobering property of trying new things is that the value of exploration, of finding a new favorite, can only go down over time, as the remaining opportunities to savor it dwindle. Discovering an enchanting café on your last night in town doesn’t give you the opportunity to return.

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The flip side is that the value of exploitation can only go up over time. The loveliest café that you know about today is, by definition, at least as lovely as the loveliest café you knew about last month. (And if you’ve found another favorite since then, it might just be more so.) So explore when you will have time to use the resulting knowledge, exploit when you’re ready to cash in. The interval makes the strategy.