According to Feynman’s approach, in this context, people should try a different restaurant each night until they find one that exceeds a particular threshold that reflects a desired quality.

In Feynman’s equations this threshold is not fixed. Instead it declines more and more rapidly as the number of days left in the city reduces. In other words, as the days go by there is increasingly less motivation to hunt for an amazing dining spot, because the time you will have to enjoy it has decreased.

“The thresholds are being guided by the best thing you might be able to find if you kept looking,” said Griffiths. “If you have a long time to look, finding something amazing has a lot of value because you can go back many times.”

Feynman’s approach assumed there is equal possibility of finding any restaurant within a fixed range of quality. However the researchers also explored other scenarios.

“We showed that if the distribution of restaurants varies, then the strategy you should follow will change too,” said Griffiths.

Here is the full story, and here is the PNAS article.  I think of that as a pretty pessimistic approach to the problem.  In most locales you should be able to find lots of very good restaurants, so if you find a quality place early on you do not return to it, rather you keep looking for more, in fact feeling emboldened by your early success.  Maybe this algorithm applies to Cuba?

Via both Adam K. and Mike Doherty.