Great explanation! Some important notes as well: 1) only in a Max node can update the corresponding alpha, so does Min for beta. 2) v can only be returned up to its parent 3) alpha and beta can only be passed down from its parent 4) cut the current node from the tree whenever alpha >= beta In the graph on the right whiteboard, shouldn't all the alpha, beta are initialized as -infinity and infinity, respectively? At 13:07, for the completeness of the logic flow, I think we should set the beta to be 2 in the node(v=2, alpha=8, beta= ), then because alpha(8) > beta(2), we prune the right subtree.
Great teacher, got a B on my AI exam with your videos about tree search algorithms 👌 explained it way better in a couple of minutes than my teacher in an hour
I want to thank you sir, you have done what my teacher was unable to do, a good explanation, it took me three days to understand this, and finally I understood thanks to this video
the best explanation about minimax. You are a great professor. I watched a lot of videos about minimax algorithm, but only your video I understood clearly
Wow, this lecture helps me understand the alpha-beta algorithm, the pseudo code is very helpful to understand. Quite intuitive. Where is the link for the assignment?
Wonderful video. This helped a lot! Working through the example in real time and explaining your thought process as you went really helped make this click.
I must be missing something because the following scenario seems like a possible scenario where alpha beta pruning can discount a superior position down the road. In chess, isn't it possible to have a move sequence where moves 6 ply out may show an inferior score for white but if the line was analyzed further, we'd see that white might be able to force a mate by taking a material loss. Wouldn't alpha beta pruning possibly discount such a line by abandoning further computational depth for that line such that it would never be able to see that a temporary drop in maximization of white's score actually sets up for a win for white? I guess my question can be reduced to this: Is it possible for alpha beta pruning to discount a line that is temporarily inferior (low score) but a few moves further out we discover a forced mate? Could alpha beta pruning throw out the analysis for such lines? Also, the entire principle of the minimax algo (in my opinion) is the scoring we give specific positions based on what information has been learned about chess over the centuries. We rank certain material with specific scores and also certain positions with specific scores. If the methodology of scoring the current state of the chess game is imperfect, then the minimax algo may not always be 100% optimal in the search tree it explores based on those scores. Let me give a quick counter example to (hopefully) better illustrate my argument. In the game of chess, there is really only one ultimate score -- is there a sequence of moves from the current game position where white (or black if playing black) can force a checkmate of the opposing king. Every other analysis within the game is of no consequence if it doesn't lead to a line where the opposing king is checkmated (or if checkmating is not possible, the only other analysis of consequence is trying to draw the current game). A new chess engine called Oracle is created using hardware from thousands of years into the future. Oracle is able to analyze 100 ply within the game in a matter of microseconds. Oracle discovers a line where white sacrifices four pieces (let's say a pawn, a knight, a bishop and a rook) in order to force a mate on the opposing king approximately 20 moves out. Now in this example, wouldn't current engines stop processing this line after the first or second piece was lost because the minimax score / alpha beta pruning? The current engine might discount the sequence of moves and call the first sacrifice a blunder because it never processed this particular line deeper. I could be way off here because my knowledge of minimax with A/B pruning is incomplete -- that's why I'm throwing this out there for others with more experience. Is this a disadvantage of minimax with AB pruning?
Every single time I see that you have uploaded a video about a topic, I lose all fear, that I'm not going to be able to understand it. This is not an exaggeration, you've helped me avoid so much confusion and desperation. Thank you so much John!
What would be a real life example ?. For example, when robo vacuum is trying to clean a house, what would be the example of pruning here ?. Is pruning happening when robo vacuum for example when it says task finish although it's not like skipping task because there are an obstacles blocking its way?
pruning can miss the best value returning. In the example, the best value should be 9 not 8. Pruning can accelerate the performance, but it not always give the best result (or best move).
Thank you sir! I was wondering if there is a formula that can calculate the maximum number of nodes that can be pruned in a tree with a depth of d and a branching factor of b.
It would be cool if you pointed more often to the algorithm. Instead, it seems as if you were doing an interpretation and that is not true. You are following exactly as it is.
Is it at all possible to see the slides you mention in the video? I've spent the past couple of days trying to figure out how to apply MiniMax with Alpha-Beta Pruning to my A-Level Chess AI, and I always seem to get bugs that shouldn't exist (I literally mean they shouldn't exist, not I don't know why they exist), Thanks
The best explanation of alpha beta pruning. "If the value is greater than beta that means min is going to prefer the branch that lead to beta." That line made it click for me.
Great explanation! Some important notes as well:
1) only in a Max node can update the corresponding alpha, so does Min for beta.
2) v can only be returned up to its parent
3) alpha and beta can only be passed down from its parent
4) cut the current node from the tree whenever alpha >= beta
In the graph on the right whiteboard, shouldn't all the alpha, beta are initialized as -infinity and infinity, respectively?
At 13:07, for the completeness of the logic flow, I think we should set the beta to be 2 in the node(v=2, alpha=8, beta= ), then because alpha(8) > beta(2), we prune the right subtree.
all solid things to point out, thanks
It works like a charm, Thanks!
Yeah, this algorithm is total shit
beta would never assigned the value of two; the function would return before that variable assignment.
Thanks this helped me so much, you have no idea
One of the best explanation, Thank you John Levine.
Thank you, sir. You are a great teacher!
Excellent explanation! The video is clear, concise, and precise. We want more videos from you. Please teach us more about AI.
You are a great lecturer, not many people can do this.
Thanks! :)
Great teacher, got a B on my AI exam with your videos about tree search algorithms 👌 explained it way better in a couple of minutes than my teacher in an hour
Great work! Well done
Thanks. That was my nth video on that topic and this time it clicked. Thanks for taking the time to go through it so deliberately. :)
You're very welcome!
Can you do a video on nonlinear planning with Goal Stack...
THANK YOU SIR! I finally know alpha beta pruning!!! Your explanation was crystal clear. If you taught my AI course, I would never ditch class!!
Kindly sir make videos on graph and tree searching algorithms i.e. by bfs,dfs,uniform cost search in python.
This definitely has to be the most thorough explanation I found on the topic. Thank you! :D
I want to thank you sir,
you have done what my teacher was unable to do, a good explanation,
it took me three days to understand this, and finally I understood thanks to this video
One of the best video on youtube to understand Alpha Beta pruning.
Want more video like this to get more understanding of AI.
the best explanation about minimax. You are a great professor. I watched a lot of videos about minimax algorithm, but only your video I understood clearly
This is the best video about this topic
He saved my exam. Thnxx sir for such a great explanation.
Alpha-beta pruning using {v, α, β}: 4:33
love you best videos sir
He is god. He explained everything in just 13 minutes. I wish if I came across this video earlier it could have saved my time. Great teacher!!
Wow, this lecture helps me understand the alpha-beta algorithm, the pseudo code is very helpful to understand. Quite intuitive. Where is the link for the assignment?
Do more videos for fuck sake please
Wonderful video. This helped a lot! Working through the example in real time and explaining your thought process as you went really helped make this click.
As a self-learner, this video is by far the best explanation I've ever seen. Clean, concise, and to the point.
I must be missing something because the following scenario seems like a possible scenario where alpha beta pruning can discount a superior position down the road.
In chess, isn't it possible to have a move sequence where moves 6 ply out may show an inferior score for white but if the line was analyzed further, we'd see that white might be able to force a mate by taking a material loss. Wouldn't alpha beta pruning possibly discount such a line by abandoning further computational depth for that line such that it would never be able to see that a temporary drop in maximization of white's score actually sets up for a win for white?
I guess my question can be reduced to this:
Is it possible for alpha beta pruning to discount a line that is temporarily inferior (low score) but a few moves further out we discover a forced mate? Could alpha beta pruning throw out the analysis for such lines?
Also, the entire principle of the minimax algo (in my opinion) is the scoring we give specific positions based on what information has been learned about chess over the centuries. We rank certain material with specific scores and also certain positions with specific scores. If the methodology of scoring the current state of the chess game is imperfect, then the minimax algo may not always be 100% optimal in the search tree it explores based on those scores.
Let me give a quick counter example to (hopefully) better illustrate my argument. In the game of chess, there is really only one ultimate score -- is there a sequence of moves from the current game position where white (or black if playing black) can force a checkmate of the opposing king. Every other analysis within the game is of no consequence if it doesn't lead to a line where the opposing king is checkmated (or if checkmating is not possible, the only other analysis of consequence is trying to draw the current game). A new chess engine called Oracle is created using hardware from thousands of years into the future. Oracle is able to analyze 100 ply within the game in a matter of microseconds. Oracle discovers a line where white sacrifices four pieces (let's say a pawn, a knight, a bishop and a rook) in order to force a mate on the opposing king approximately 20 moves out.
Now in this example, wouldn't current engines stop processing this line after the first or second piece was lost because the minimax score / alpha beta pruning? The current engine might discount the sequence of moves and call the first sacrifice a blunder because it never processed this particular line deeper.
I could be way off here because my knowledge of minimax with A/B pruning is incomplete -- that's why I'm throwing this out there for others with more experience. Is this a disadvantage of minimax with AB pruning?
Fantastic explanation. No one on RUclips has ever explained this algorithm so nicely using it's pseudo code . Very nice Sir, Respect
Great explanation 👌
Every single time I see that you have uploaded a video about a topic, I lose all fear, that I'm not going to be able to understand it. This is not an exaggeration, you've helped me avoid so much confusion and desperation. Thank you so much John!
5 year later and still best video on alpha-beta pruning. Thank you sir.
Thanks for making me feel old! Very glad it's useful 😀
Your videos are so concise and helpful. They're the only thing keeping my grade decent in my Intelligent Systems class.
Glad you like them!
Respect to you sir. You explained it so well! I'm very grateful!
this is amazingly helpful for me! thank you sir for this explanation!
Great presentation of work. would it be possible to link the supplementary material associated with this lecture?
What would be a real life example ?. For example, when robo vacuum is trying to clean a house, what would be the example of pruning here ?. Is pruning happening when robo vacuum for example when it says task finish although it's not like skipping task because there are an obstacles blocking its way?
an excellent teacher , thank's a lot. we'r waiting for more courses about AI :) Good luck
pruning can miss the best value returning. In the example, the best value should be 9 not 8. Pruning can accelerate the performance, but it not always give the best result (or best move).
Great explanation! I already knew what steps to take, but it wasn't really clear why I should take those steps. It is clear to me now.
Thank you sir! I was wondering if there is a formula that can calculate the maximum number of nodes that can be pruned in a tree with a depth of d and a branching factor of b.
Thanks teacher...I watch your videos in Azerbaijan✨
it's just amazing. all your videos are the definition of crystal clear explanation. perfect. I wish you'll do more videos
Your videos help me so much with my course, thanks!
It would be cool if you pointed more often to the algorithm. Instead, it seems as if you were doing an interpretation and that is not true. You are following exactly as it is.
Sir, would you mind making a series video for Artificial Intelligence... It will be more helpful...
thank you for saving me from my lecturer....
very good Explanation Sir! :)
Damn, you are good. Thanks for helping
Awesome explanation sir thanks from india
this video was so helpful.
thank you.
This is so helpful!! Thank you so much!
excellente!!! mi amo probes !!
Just wanted to thank you for your great videos! Watching them pre-exam to refresh and they're all very clear and informative
Obrigado. IA já está no bolso
why you not prune -2 ? 8>2 ?
can min come at the top and be followed by max?
Thank you so much! You're the best!!
great explanation!!! Thank you!!!
Great Explanation! Thanks alot.
bunch of thanks (y)
this is life-saving sir thanks a lot ^-^
this guy makes me wanna go back to school
Many thanks for explanation!
Love from Pakistan!!!!
katlu.........ahh ahhhh ahhhh.....ahhhh
Thank you so much sir. !!!!
Goated Explanation Sir!
thanks man, you gave me a great favor
Sirrr love your vids
loved the way you explaine
easy example, make a harder one🤭
This is the hotest content online about this chapter!
So concise and precise!🎉
Thank you!
Is it at all possible to see the slides you mention in the video? I've spent the past couple of days trying to figure out how to apply MiniMax with Alpha-Beta Pruning to my A-Level Chess AI, and I always seem to get bugs that shouldn't exist (I literally mean they shouldn't exist, not I don't know why they exist), Thanks
Amazing. Stick to the Lego though.
Great explanation!
The best explanation of alpha beta pruning. "If the value is greater than beta that means min is going to prefer the branch that lead to beta." That line made it click for me.
Is it just me or is he the actor who played Benjamin Linus from LOST (Michael Emerson)? He both looks and speaks exactly like Ben.
I have to admit you are the only one who could explain and impart knowledge to even the dumbest person like me. You are the great great teacher.
Awesome explanation. Upvote. Please make videos explain, all alogrithms Thanks!
You did not define the term "pruning". What do you mean "that will show you where the search can be pruned"?
It means the search will never explore that path. Pruned nodes and their child nodes will be ignored by the minimax algorithm to save computing time.
Would the -2 value not be pruned as we have a deep cut off situation ? We can see that Max will be = 8? Is there point in exploring -2?
Thank you so much!
Thank you for this amazing video and explaination, not many have the ability to do this 🌸🖤
Watching this once saves me so much time that might've gone into reading through a textbook section on this particular algorithm
Tnx you are so amazing
Thank you sir ！
Good work right there!!!
Thank you!!! :)
Don't expect to instantly understand this topic, but your video did it. Thanks. :D
OMG! Very very clear! I came from CS188 step by step.
This is the best video I have seen which explains the algorithm along with the graph.
Very good video. I will now attempt to code my own tic-tac-toe solver :)
Thank you so much for your video. It's really clear.
Thank you very very much! It takes a long time for me to understand the alpha-beta pruning .Luckly ,I find this vedio.
Thank you. I've seen many videos and could not understand until I saw this video. Many thanks for your clear explanation!!
Thank you
Thanks. your explain is quit clear😊
bsdk english to theek se bol le 6th pass ma ki chut
Please make a video on Negamax as well, would be perfect if includes Transposition in the algorithm either. And thanks for the lesson, thank you.
error 404
this mans single handedly getting me through AI
Thank You so much sir!
God Bless you!
Great
Thank you Dr
why does 8 get placed as alpha in the level 2 right node ?
wow so clear