ohwellhere
Joined 5 years ago
Joined 5 years ago
It is not necessarily true that an O(1) algorithm will outperform an O(n^2) alternative on a particular set of data. But it is true that an O(1) algorithm will outperform an O(n^2) alternative as the size of the input data increases.
I know very many people who would refuse to work for certain companies and in certain industries — and have rejected certain projects — but would happily contribute to something MIT licensed that would end up in those systems anyway!
[0]: https://www.amazon.com/Alien-Information-Theory-Psychedelic-...
This sounds like exactly the kind of definition that would get appropriated to belittle slaves. See also simply, “boy.”
GPT4 (lyrics) Suno (music) Resemble (voice) SyncLabs (performance) Runway (film) Fable (edit) Midjourney (image) Katalist (storyboard) Topaz (up-res)
“Red-headed lady, gonna eat an apple. She breathes on it first, wipes it on her bloooouuuuse…”
So if the probability of finding a mine at any given spot is given by p, then the probability of finding a mine in the top left during gameplay for cases where one does not click it first (in which case it is 0?) is 1 for the case where you clicked on a mine first with probability p, and then p for the remainder.
So the total probability p' is p * 1 + (1 - p) * p, or 2p - p^2.
Wikipedia says
> Beginner is usually on an 8x8 or 9x9 board containing 10 mines, Intermediate is usually on a 16x16 board with 40 mines and expert is usually on a 30x16 board with 99 mines; however, there is usually an option to customise board size and mine count.
I was curious to see the concrete effects for no reason other than to procrastinate.