Algorithms in Life: Find the perfect partner, apartment and job | Hacker News Reader

Algorithms in Life: Find the perfect partner, apartment and job

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69 pointsdhara0413 comments

In the secretary problem, we assume that your ability to distinguish a good secretary from a bad one is fully developed from the beginning. In the examples given, you spent a significant amount of time (maybe even your whole life) figuring out what makes a good partner, apartment, or job. It's a neat problem, but I would be concerned for anyone who uses it as a life guide.

My favorite math problem that offers a realistic solution to a practical problem is Sperner's Lemma (implemented here [1])

[1] https://www.nytimes.com/interactive/2014/science/rent-divisi...

This sounds like an interesting idea, thanks for sharing info about Sperner's lemma.

The 37% solution to the Secretary Problem is derived by letting n (number of candidates) tend to infinity (https://en.wikipedia.org/wiki/Secretary_problem#Deriving_the...). Most of us are not that lucky in love affairs.

I've been on 300 first dates, Ive been with about 1/3rd of that many women. I still fucked up horribly.

I agree we aren't that lucky.I didn't know about derivation using n tends to infinity. Thanks for that.

As always, the applicability of the assumptions is key.

If you can go back to an earlier partner, that changes things quite a lot, right? Hey, what if you can date multiple people at once?

Also, is your judgement of a given date atomic? You meet, you immediately know how good this one is, you hit or stay?

Not sure that's how it works.

Also, what about the chance they don't want you? Does the secretary game solution allow for the other part applying the same rules?

Yes, the Algorithm changes if you can go back to an earlier partner. You can keep looking further beyond 37% and defer decision making.

I wouldn't recommend dating multiple people at once.

Say your goal is to find your soulmate in next 2 years, let's define n =24 months. Then you keep looking for the next 9 months without committing to any one. Let's say the name of your perfect partner in the first 37% is Max. Then you start looking beyond the first 37%, the first person better than Max is your soulmate. Considering there is chance of refusal or rejection, you can start earlier (follow the above algorithm at 33% )

https://www.amazon.com/Algorithms-Live-Computer-Science-Deci...

This is an excellent read, even if you're familiar with most of the material.

Thanks, glad you enjoyed reading it

Although this result sets up in some way a baseline, n (the number of choices) should be a random variable N in order to make things a bit more realistic.

Edit: A brief comment on this case is mentioned here: https://en.wikipedia.org/wiki/Secretary_problem#Unknown_numb...

The `1/e-law of best choice` mentioned on there was interesting, and helped me accept the conclusion regarding finding love. With the previous examples, love and similar concepts didn't seem like they would work well when N could theoretically be infinite. Though, after some help understanding the wiki explanation [1], applying the rule over the finite _period of time_ during which you see options, rather than the total number of options, makes much more sense and seems more agreeable.

[1]: http://math.stackexchange.com/questions/840196/how-to-use-th...

That's intriguing!

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