
Algorithms to Live By: The Computer Science of Human Decisions

The untested rookie is worth more (early in the season, anyway) than the veteran of seemingly equal ability, precisely because we know less about him. Exploration in itself has value, since trying new things increases our chances of finding the best. So taking the future into account, rather than focusing just on the present, drives us toward novel
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We know this because 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 dail
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Because for people there’s always a time cost. It doesn’t come from the design of the experiment. It comes from people’s lives.
Griffiths • Algorithms to Live By: The Computer Science of Human Decisions
“I mostly go to restaurants I know and love now, because I know I’m going to be leaving New York fairly soon. Whereas a couple years ago I moved to Pune, India, and I just would eat friggin’ everywhere that didn’t look like it was gonna kill me. And as I was leaving the city I went back to all my old favorites, rather than trying out new stuff.… Ev
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“After searching for a while, we humans just tend to get bored. It’s not irrational to get bored, but it’s hard to model that rigorously.”
Griffiths • Algorithms to Live By: The Computer Science of Human Decisions
Nonetheless, the present has a higher priority: a cured patient today is taken to be more valuable than one cured a week or a year from now, and certainly the same holds true of profits. Economists refer to this idea, of valuing the present more highly than the future, as “discounting.”
Griffiths • Algorithms to Live By: The Computer Science of Human Decisions
(“Wait, I can resolve this argument. That restaurant was good 29 times out of 35, but this other one has been good 13 times out of 16, so the Gittins indices are … Hey, where did everybody go?”)
Griffiths • Algorithms to Live By: The Computer Science of Human Decisions
First, assuming you’re not omniscient, your total amount of regret will probably never stop increasing, even if you pick the best possible strategy—because even the best strategy isn’t perfect every time. Second, regret will increase at a slower rate if you pick the best strategy than if you pick others; what’s more, with a good strategy regret’s r
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But the reality is not so simple. Remembering that every “best” song and restaurant among your favorites began humbly as something merely “new” to you is a reminder that there may be yet-unknown bests still out there—and thus that the new is indeed worthy of at least some of our attention.