There is a chapter in Algorithms to Live By which claims the effect is beyond silly and annoying.
> If you want to be a good intuitive Bayesian--if you want to naturally make good predictions, without having to think about what kind of prediction rule is appropriate--you need to protect your priors. Counterintuitively, that might mean turning off the news.
p. 148 Algorithms to Live By, Brian Christian and Tom Griffiths
Algorithms to Live By című könyv való neked OP.
A könyv szerint, hogy megtaláld az ideális párod, a párkereséssel töltött évek 37%-át fordítsd arra, hogy csak randizz minél többet, teszteld a kapcsolatotkat. Ezután után vedd ez az első nőt aki jobb mint bármelyik akivel a 37% eléréséig összejöttél. Statisztikailag így van a legjobb esélyed arra, hogy megtaláld a számodra lehetséges legjobb csajt. De ugyanez a szabály alkalmazható pl. házvásarlásra, álláskeresésre is.
A visszautasítás kicsit bonyolítja a dolgokat de majd kiszámolod, hogy mennyivel csökkenti ez azt a bűvös 37 százalékot.
I don't have any links about it but it's a pretty well known thing: the stopping problem. A quick google will give you lots of resources!
The book is on amazon! book link
Algoriths to Live By by Brian Christian and Tom Griffiths. Written for the lay person so very accessible, by a brilliant cognitive scientist at Princeton (though at Berkeley when the book was written).
Vision by David Marr. One of the first and most important books that anyone interested in cognition and computation will ever read. Absolute must if you want to understand why the field began looking at the mind more or less like a computer.
"Algorithms to Live By: The Computer Science of Human Decisions" by Brian Christian and Tom Griffiths.
Check out the book Algorithms To Live By. It's an interesting read about how we can apply common computing algorithms to our day to day lives'
You might like Algorithms to live by.
Puoi fare il contrario, puoi prendere degli algoritmi e vivere la tua vita seguendo quelli
I really liked the algorithms to live by book. Not heavy on the math, very approachable. I personally think it should be required reading for any CS50.
https://www.amazon.com/Algorithms-Live-Computer-Science-Decisions/dp/1627790365
You have discovered the explore/exploit dilemma, also known as the multi-armed bandit problem. Should you search for new things you on the chance you will like them, or continue to listen to the things you know you like?
I do the same thing with Spotify. I have a large list of "saved" music on there that I often come back to and shuffle when I need something familiar. But every so often I like to branch out and find something new, either with the weekly discover playlists, or by going to a song I like and playing the rest of that artist's songs or switching to radio mode so it will suggest more. With this method I gradually build up more songs for my list. Also every so often I remember a song I like and search for it, and then I can explore that artist's other songs. But the vast majority of the time I want the sure thing, so I go to my saved songs list and hit shuffle.
Btw, I learned about the multi-armed bandit problem from the book Algorithms to Live By.
You guys want to try out Algorithms to Live By?
You may want to check out Algorithms to Live by.
It goes into practical examples of complex problems that mathematicians and programmers have solved. It reads somewhat like a philosophy book if that will help you.