Oh sorry to hear that. RIP

is it because of Corona?

So sad hearing that, true jem of a teacher. RIP

@@ThePaypay88 His McDonald's belly

,,🙏🏻🙏🏻🙏🏻 respect from India Rest in peace 🕊️🕊️🕊️ A great professor....

thx

@@ahmedmamdouhkhaled8750 welcome, good luck ^^

thank you for saving my ass. also, Christopher impressed me at the end lol

same boat here mate

This was 3 year ago... this isn't 2021!

Viral Villager I came from the future

Nafolchan O.o

Are u serious? The class and professor disappointed me. The small dwarf guy explains very well. But this professor...Not even close.

@@Atknss can you tell me where i can find this mestirious dwarf that can help me understand AI, would be much appreciated, thank you in advance :)

I dont know where u study or what u study but this is an amazing lecture abt AI. If u cant follow thats allows seriously conclusions about you tho

@@MrEvilFreakout I think he plays in Game of Thrones. Ask George R.R. Martin. LOL no seriously I would like to know too. Although I think this lecture was pretty good.

+Mares Fillies Thanks , World needs more people like you.

bless you

fuck you. it starts around min 16.

thats alpha-beta part, not the original min-max.

no such thing as savex about it, doesnt matter, schoolx, scox, these gamex etc. meaningless, cepit, do, be can do,be any nmw and any be perfx. also buyer not seller, always test profx not for test

He’s only off by 10^10. While still being right. See my other comment.

Perhaps it can be organized by branch: one process takes a branch, then when it splits it also splits the process in two. Of course when b=15 that can become cumbersome I guess.

How'd you do on it?

What does it mean?

@@axelkennedal5656 Euphemism for an exam?

yes

Whenever u get a fixed value of a node (here 27 at the top) , you compare that fixed value to the next deepest first node(here 1) and then again the usual way of checking nodes... I was also confused for a while there..

If the computer is the superior player, then it doesn't matter when the human makes a poor move. The computer, when doing the initial search, decided that the branch in question was "too good to be true." Thus when the human makes that move, the computer can re-discover the path that was originally "too good to be true" with less effort than it took to find it the first time (because we are one level deeper in the tree). Bottom line: Computers (when properly programmed) spend the bulk of their time analyzing the game under the assumption that the opponent is just as good as the computer. Whenever the opponent makes a poor move, the computer can recognize and capitalize on that gain relatively quickly, making the time wasted earlier irrelevant.

@@richardwalker3760 Probably caching values or entire trees can be of value? Otherwise you are recalculating things you've seen before.

Yes, of course. Then you simply have a single deterministic program.

Not necessarily. The algorithms can use random numbers if there are moves with the same value.

@@marmathic9874 But they don't. And combining two deterministic algorithms always results in a new deterministic algorithm, and thus a deterministic result.