Algorithms to Live By: The Computer Science of Human Decisions

science, the tension between exploration and exploitation takes its most concrete form in a scenario called the “multi-armed bandit problem.”

When balancing favorite experiences and new ones, nothing matters as much as the interval over which we plan to enjoy them.

“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

If waiting costs $2,000 an offer, we should hold out for an even $480,000. In a slow market where waiting costs $10,000 an offer, we should take anything over $455,279. Finally, if waiting costs half or more of our expected range of offers—in this case, $50,000—then there’s no advantage whatsoever to holding out; we’ll do best by taking the very fi

The chance of ending up with the single best applicant in this full-information version of the secretary problem comes to 58%—still far from a guarantee, but considerably better than the 37% success rate offered by the 37% Rule in the no-information game.

Most people acted in a way that was consistent with the Look-Then-Leap Rule, but they leapt sooner than they should have more than four-fifths of the time.

As we have seen, this Catch-22, this angsty freshman cri de coeur, is what mathematicians call an “optimal stopping” problem, and it may actually have an answer: 37%.

A 63% failure rate, when following the best possible strategy, is a sobering fact. Even when we act optimally in the secretary problem, we will still fail most of the time—that is, we won’t end up with the single best applicant in the pool. This is bad news for those of us who would frame romance as a search for “the one.” But here’s the silver lin

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.