
Algorithms in Life: Find the perfect partner, apartment and job - dhara04
https://medium.com/techbasics/find-the-perfect-spouse-job-and-apartment-949bb447b0c9
======
qntty
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...](https://www.nytimes.com/interactive/2014/science/rent-division-
calculator.html)

~~~
dhara04
This sounds like an interesting idea, thanks for sharing info about Sperner's
lemma.

------
Jun8
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...](https://en.wikipedia.org/wiki/Secretary_problem#Deriving_the_optimal_policy)).
Most of us are not that lucky in love affairs.

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

------
lordnacho
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?

~~~
dhara04
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% )

------
anirudhgarg
[https://www.amazon.com/Algorithms-Live-Computer-Science-
Deci...](https://www.amazon.com/Algorithms-Live-Computer-Science-
Decisions/dp/1627790365/ref=mt_hardcover?_encoding=UTF8&me=)

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

~~~
dhara04
Thanks, glad you enjoyed reading it

------
kmundnic
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...](https://en.wikipedia.org/wiki/Secretary_problem#Unknown_number_of_applicants)

~~~
Psilidae
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...](http://math.stackexchange.com/questions/840196/how-to-use-the-1-e-law-
of-best-choice)

