How math can help you decide what to order for dinner

An experiment with 2,520 participants backs Richard Feynman’s answer to every diner’s dilemma: do I want to try something new?

Nobel Prize winning physicist Richard Feynman stands in front of a blackboard strewn with notation in his lab in Los Angeles, Californina.

Richard Feynman was awarded the 1965 Nobel Prize in Physics.

Kevin Fleming/Corbis via Getty Images

In a scene that could have easily featured in an episode of the US television sitcom The Big Bang Theory, the late US physicist Richard Feynman once turned a visit to a Thai restaurant he often dined at into a mathematical riddle: how adventurous should we be in trying new dishes? Feynman promptly solved this on a sheet of paper.

Now, behavioural scientists have revisited Feynman’s solution — some of which had been obscured by his inscrutable handwriting — and found that his was indeed the optimal strategy.

Feynman’s dilemma is one that will be familiar to any restaurant-goer. Do we keep ordering the best dish we’ve had so far, or do we explore the menu in the hope of finding something better? A study published in the Proceedings of the National Academy of Sciences on 1 June probes this question, and includes experimental findings that participants adopt meal-choosing strategies that closely approximate Feynman’s mathematical solution.


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Behavioural scientist Shoham Choshen-Hillel at the Hebrew University of Jerusalem says that the authors wrote a “super creative article.” “The restaurant example stands in for decisions in many settings,” she adds. Real-life examples include choosing a home to buy, deciding whom to partner up with and selecting a parking spot.

Are you ready to order?

The story begins with a regular visit by Feynman, a Nobel prizewinning physicist at the California Institute of Technology in Pasadena, and his friend Ralph Leighton, to a Thai restaurant in nearby Glendale in the late 1970s. (Leighton helped Feynman to write his popular 1985 memoir Surely You’re Joking, Mr. Feynman! and was the son of the late physicist Robert Leighton, the co-author of the influential 1964 The Feynman Lectures on Physics, together with Feynman and Matthew Sands.) Leighton wondered whether he should order ginger chicken — his favourite dish — or explore the rest of the menu. Feynman began scribbling and promptly claimed he had found a mathematical solution: in his simplified model of the situation, he calculated a threshold — a number of visits beyond which Leighton’s rational decision would be to always settle on his favourite dish.

What Feynman had done was turn the restaurant dilemma into a question in decision theory — a field at the intersection of economics and psychology that analyses strategies in one-person games. In particular, it was an original contribution to a larger family of problems in decision theory called stopping problems. These include real-life problems in which someone has to decide whether the possibility they have in front of them is good enough, or whether to keep searching.

Leighton saved the notes, and years later he partially transcribed Feynman’s spidery cursive handwriting to the best of his ability. Leighton described his interpretation in an article he posted online in the early 2000s. A decade later, in 2013, Tom Griffiths, a cognitive scientist at Princeton University in New Jersey, became interested in the question while he was researching a book with his collaborator Brian Christian, a computer scientist and cognitive scientist. Griffiths then transcribed Feynman’s notes in full for the first time.

Christian, who is now at the University of California, Berkeley, says the question then lay dormant for nearly another decade, until the two researchers decided to revisit it in 2021. “We’d understood the meaning of Feynman’s notes, but there was all this work to be done,” he says. The researchers then went on to confirm that Feynman had indeed come up with the best solution, and also solved a generalized version of the problem.

Behaviour matches maths

Together with a third co-author, cognitive psychologist Evan Russek at the City University of New York, the team decided to test whether people’s choices would resemble anything close to the mathematical solution. They translated the restaurant question into an online game, recruiting 2,520 participants to answer it. Participants were instructed to imagine visiting a new city for a period of between one and four weeks, and having to choose which restaurant to eat at each night. Players could earn points for the quality of the restaurant they picked (a number between 1 and 100), and were told to try to maximize their total number of points. Participants became less willing to risk trying new restaurants as the end of their visit approached, which followed logic similar to Feynman’s optimal formula.

Although the participants did not work out the mathematical solution — which involves a formula with square roots — their behaviour was a very close approximation of it.

“The fact that, even in this simplified setting, they still find that people behave in a quite consistent — and pretty effective — way is quite impressive,” says Choshen-Hillel.

Although Feynman’s problem could have applications in economics and marketing, it does not fully model people’s behaviour at a restaurant, Choshen-Hillel says. In particular, it does not take boredom into account, Christian says, because players’ optimal option is to settle on one dish once and for all. In real life, someone might want to continue to choose the same dish every other time, say, and keep exploring the menu on the other visits. But the problem “does distil to its essential form this fundamental tension very familiar in every day: the decision between doing your favourite thing and trying something new,” he says.

This article is reproduced with permission and was first published on June 1, 2026.

Davide Castelvecchi is a staff reporter at Nature who has been obsessed with quantum spin for essentially his entire life. Follow him on X @dcastelvecchi

More by Davide Castelvecchi

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