I can answer with an example, the famous book Algorithms to live by. It’s amazing how so many of everyday things can be explained with mathematics.

https://www.amazon.com/-/es/Brian-Christian/dp/1627790365

A great general one that HN folks should enjoy:

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian & Tom Griffiths

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

I came across an interesting take on this in the book Algorithms to live by [1]. They argue that old age is a time of exploitation (as in explore/exploit strategy) where we tend to prioritize relations/experiences that we know to be rewarding. At a younger age, we are more accommodating to explore new experiences. That is why a teenager entering a dorm in a new environment full of strangers can get excited while for old people entering a retirement home it can be a harrowing experience.

1 - https://www.amazon.com/gp/product/1627790365

I guess I'm the foolish one, but I thought the title implied that the book was about algorithms you can use to make decisions, not decision making algorithms.

If the former sounds interesting, here is a similar book I read a long time ago: https://www.amazon.com/Algorithms-Live-Computer-Science-Deci...

Tons, the book "Algorithms to live by" go head first into this - https://www.amazon.com/Algorithms-Live-Computer-Science-Deci...

It can sound a bit simple at first, but the human - algo stories are terrific.

As you get older, you should read fewer new books, and revisit the ones that have you the most joy. Vacation sounds like a great place for that!

Edit: why? Because you believe in the leverage algorithms can provide https://www.amazon.com/Algorithms-Live-Computer-Science-Deci...

There are probably a lot of single people here that would benefit from that book as well (the stopping problem)

We all "know" the algos. But reading/hearing how they can be applied and what effect they can have on your life can be enlightening.

I can also recommend "Algorithms to Live By", by Brian Christian & Tom Griffiths. https://www.amazon.com/Algorithms-Live-Computer-Science-Deci...

Super accessible.

The Nash equilibrium for an unlimited vacation policy is no vacation for anyone.

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

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

>So is there an ideally sized choice set when it comes to dating—one large enough to include variety and depth, yet small enough that you can fairly weigh each prospect’s potential without tripping your brain’s overload switch? [...] Fisher puts people somewhere in the middle of that range. “Once you’ve met nine people who are vaguely in the ballpark, choose one and get to know that person better. If nothing works in that nine, go for another nine,” she says.

The article talks about simultaneous choices (choice overload). A related concept is serial choices and the "when to stop looking for The One" dilemma. That's been modeled as The Secretary Problem[1] which calculates a 37% stopping point. It also has been discussed by several authors: [2] [3] [4] [5]

[1]https://en.wikipedia.org/wiki/Secretary_problem

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

[3]https://youtu.be/OwKj-wgXteo?t=10m12s

[4]https://www.amazon.com/Mathematics-Love-Patterns-Ultimate-Eq...

[5]https://www.ted.com/talks/hannah_fry_the_mathematics_of_love...

By the way, that article is an advertisement for "Algorithms to Live By: The Computer Science of Human Decisions" [1] in case you're triggered by native advertising. That out of the way ...

As the article states, caching is useful when you have memory stores with different access speeds. This is (frequently, in my experience, caveat caveat etc.) not the case in reality, where you only have the one storage area that has a fixed, fairly low access speed. People are mostly bottlenecked by scanning rate, so it'd make more sense to use an indexing mechanism. Maybe b-trees for closets? B-trees, perhaps, if you store things in boxes?

[1]: http://www.amazon.com/dp/1627790365/