6. Search: Games, Minimax, and Alpha-Beta

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MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: ocw.mit.edu/6-034F10
Instructor: Patrick Winston
In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures that some answer is always available.
License: Creative Commons BY-NC-SA
More information at ocw.mit.edu/terms
More courses at ocw.mit.edu

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9 янв 2014

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Комментарии : 262

@66javi66 4 года назад

Patrick Winston, the professor of this lecture, pass away this July... Thank you Patrick.

@joefagan9335 3 года назад

Oh sorry to hear that. RIP

@ThePaypay88 3 года назад

is it because of Corona?

@dipmodi844 3 года назад

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

@BabbyCat3008 3 года назад

@@ThePaypay88 His McDonald's belly

@piyushsingh6462 2 года назад

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

@yassinehani 5 лет назад

Minimax : 16:17 alpha beta simple example : 21:51 alpha beta big example : 24:54

@ahmedmamdouhkhaled8750 10 месяцев назад

thx

@yassinehani 10 месяцев назад

@@ahmedmamdouhkhaled8750 welcome, good luck ^^

@kardsh 7 лет назад

didn't pay attention in my classes, now here i am at 4 am watching a lecture from 7 years ago......

@kardsh 7 лет назад

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

@darkweiss1234 7 лет назад

same boat here mate

@JNSStudios 7 лет назад

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

@kardsh 7 лет назад

Viral Villager I came from the future

@JNSStudios 7 лет назад

Nafolchan O.o

@BrunoAlmeidaSilveira 8 лет назад

One of the best lectures in the series, fantastic professor and amazing didactic. Many thanks to MIT for this contribution.

@Atknss 6 лет назад

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

@MrEvilFreakout 5 лет назад

@@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 :)

@nesco3836 3 года назад

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

@MichielvanderBlonk 2 года назад

@@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.

@johnnybegood8669 4 года назад

R.I.P. Patrick Winston, your work will last forever

@sixpooltube 6 лет назад

This is the Breaking Bad of AI lectures. Epic beyond comparison. I've watched it more than once and I've learned something new every time.

@RyanCarmellini 8 лет назад

Great lecture. Very clearly explained alpha beta pruning. I liked the greater than and less than comparisons on each level. This was much clearer then just defining alpha and beta at each level.

@Apollys 7 лет назад

Wowwww I've never seen anyone evaluate the time cost of brute forcing chess the way he did! Amazing! This guy is just amazing.

@tcveatch 6 месяцев назад

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

@codykala7014 6 лет назад

This was an excellent lecture. The explanation of alpha-beta pruning was so clear and easy to follow, and Prof. Winston is excellent at presenting the material in an engaging fashion. And I loved how Prof. Winston goes the extra mile to tie in these concepts to real life situations such as Deep Blue. Thank you so much!

@moosesnWoop 4 года назад

Love these lectures - think about them throughout my day. Well seasoned Lecture. Sad to hear about his passing.

@mass13982 8 лет назад

Amazing professor. My hat off to you sir

@yyk900820 7 лет назад

Love this professor. Calm clear explanation. Smooth voice. And humour.

@JenniferLaura92 9 лет назад

what a great explanation. Elaborated very well! thank you

@maresfillies6041 9 лет назад

For those who want to know where he talks about Min Max go to 25:00. It saved my ass.

@KulbhushanChand 8 лет назад

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

@mekaseymour1784 7 лет назад

bless you

@chg_m 6 лет назад

fuck you. it starts around min 16.

@flavillus 6 лет назад

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

@zes7215 5 лет назад

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

@cameronmoore7675 6 лет назад

Came here for a good explanation of alpha-beta pruning, and got what I came for. Fantastic lecture! ...but what really blew me away was how *absurdly clean* that blackboard is. Just look at it!

@ishratrhidita9393 5 лет назад

He is an amazing professor. I would have considered myself lucky to be in his class.

@DusanResin 5 лет назад

Great explanation! It's basically everything you need to build any game with AI opponent in one lecture. And you can easily determinate the level of difficulty by limiting the depth level of calculating.

@alakamyok1261 4 года назад

Amazing teacher, thanks to engineers of yesterday, and MIT, we have access to these gems.

@insidioso4304 7 лет назад

Greetings from the Politecnico di Milano; thank you for these beautiful lectures!

@adityavardhanjain Год назад

This lecture is so good. It clears the concept on a theoretical and practical aspects both.

@avinkon 5 месяцев назад

Patrick Winston has a great teaching style with a subtle humor , childlike playfulness, enthusiasm , energetic and engaging lecture, enjoyed thoroughly :)

@bhargavaramudu3242 4 года назад

This lecture is awesome...such a great professor he is...I absolutely love him

@jaceks6338 6 лет назад

This prof explains stuff so well. Respect.

@narobot 7 лет назад

This is such a great video, I am pretty amazed at how anyone could have came up with this. Great lecture.

@EliusMaximus 3 года назад

Amazing lecture, I am very grateful that this has been recorded, thank you for spreading knowledge for free

@shiningyrlife 9 лет назад

best minimax and alpha beta pruning explanation i ever see!

@hslyu 2 года назад

You gave me a great inspiration. Rest in peace my teacher.

@ohserra 10 лет назад

Thank you Professor Patrick! I wish I have had some professors like you!

@dagual4473 8 лет назад

Thanks to the guy who wrote the subtitles. It clearly made me understand beter.

@GoogleUser-ee8ro 5 лет назад

Prof Winston is quite a genius in giving funny Memorable names for algorithms - British Museum, dead horse, Marshall Art etc. Also the way he explained how Deep Blue applied minimax + alphabet prune + Progressive Deepening etc immediate relate the material to real-life applications. Good Job! But I hope he could explain more on how paralleled computing helped alpha beta punning in DB.

@MichielvanderBlonk 2 года назад

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.

@-_Nuke_- 7 месяцев назад

I wanted to say a huge thank you, this was an amazing lecture! I can only imagine the elegance of modern chess engines like StockFish and LC0... StockFish being a brute force and neural network hybrid and LC0 being a pure neural netword powerhouse... The amount of knowledge someone could get from studying them would be extraordinary! If only I could had the pleasure...

@sagarpanwar2724 4 года назад

The most clear explanation of Alpha Beta Pruning and Minimax

@OlivierNayraguet 4 года назад

I am into AI and Game Theory now with Columbia Engineering, I really enjoyed this presentation. So long professor.

@celialiang1485 3 года назад

Thank you for this great speech. RIP professor.

@myj313 5 лет назад

Seems like a really nice professor. My AI professor also nice and good teacher but leaves out some details which I learn it from here. Thanks for great courses!

@themathaces8370 3 года назад

Beautiful lecture. Thanks very much.

@FreshEkie 7 лет назад

Excellent, very helpful for my Artificial Intelligence exam. Greetings from Germany.

@AlexandrSudakov 2 года назад

I wish I had such a lecturer in my university :) Especially I liked the moment about cloud computing at 11:07

@richardwalker3760 10 лет назад

Phenomenal lecture. Thank you.

@mofakah5906 4 года назад

Came for just the minimax but I stayed for the whole lecture. Thanks MIT

@shubhamsawant5609 2 года назад

Cleared the outlook for Games search

@junweima 5 лет назад

I pray every day for more lectures

@zfranklyn 6 лет назад

Such a great, clear lecturer!

@stevenstefano8778 3 года назад

Great video and lecture! Required viewing from my AI professor at Pace University. Worth every second!

@ahgiynq 4 года назад

Thank you for these great lectures

@debangan 3 года назад

The dude with leg up just reinvented a whole damn idea in a class. No wonder he is in MIT and I am not.

@IsaacBhasme 10 лет назад

Good lecture. Elaborated very well.

@behind-the-scenes420 Год назад

Excellent instructor ever. Love from Comsats Islamabad

@__-to3hq 5 лет назад

I'm glad I never went to a university, someone like me needs to hear or see something done a few times, this is better for me video lectures from MIT xD

@AChannelFrom2006 8 лет назад

Thank you very much for these.

@garimamandal98 Год назад

Very well explained. All my doubts got cleared

@sondredyvik5815 9 лет назад

Great lecture!

@EngenhariadeSoftwareLuciana 8 лет назад

perfect lecture!

@chemicalfiend101 5 лет назад

I didn't think anyone would call a bulldozer sophisticated, but they are! This course is quite eye-opening.

@dalest.hillaire5542 6 лет назад

Very clear and concise.

@rohitdas475 2 года назад

Pruning explained in the perfect way !!

@berke-ozgen 2 года назад

Great and impressive lecture.

@QueenGraceFace 10 лет назад

This is really helpful! Great lecture :)

@perseusgeorgiadis7821 Год назад

Finally. Someone explained this stuff in a way I could understand

@keyboard_toucher Год назад

Human chess players do use the alpha-beta approach (even if we don't recognize it by name), we just have a lot of additional tricks like heuristics about which moves to explore and the order in which to do so.

@nadianyc9262 5 лет назад

you saved my life , thank youu

@maliknaveedphotography 7 лет назад

Sir u R Great ! Really This is Excellent Lecture :) Thanks

@brianbaker1124 6 лет назад

wonderful lecture

@charlesrodriguez6276 3 года назад

Since school is online anyways and the whole course is project-based for me. I'm going to MIT online for my Fall semester.

@HenriqueLuisSchmidt 9 лет назад

great lecture!

@wolftribe66 4 года назад

24:59 man had a tree prepared like a G

@amrmoneer5881 4 года назад

This is beautiful. he explained it in simple terms very vell

@35sherminator 8 лет назад

Great lecture

@davidiswhat 5 лет назад

Damn, this was good. I ended up skipping the proof like stuff and could only really understood the actual algorithm. Might watch more of these.

@nXqd 9 лет назад

thanks mr winston. This is so good :)

@robertjurjevic6580 8 лет назад

thanks for this lecture :)

@shawntsai3277 7 лет назад

This professor is perfect. It is waste of time to attend the same classes in other school.

@Conor.Mcnuggets 7 лет назад

@ 29:34, for the deep cut, did he compare two Max nodes? or compared the bottom Min node with the root Max node?

@JITCompilation 2 года назад

Lectures like this make me wish I didn't screw around so much in high school :C should've gone to MIT instead of my crappy uni

@maresfillies6041 9 лет назад

Awesome lecture, I have a test on these topics today. :D

@larry_the 2 года назад

How'd you do on it?

@alm5966 3 года назад

Slightly shocking that MIT students couldn't offer up the generally perceived age of the Universe. I would have thought some of them had at least watched Big Bang Theory.

@ShivangiSingh-wc3gk 6 лет назад

I got thrown off a little on the alpha beta part. So at each level we when we make comparisons do we look at the values from both the min and max perspective?

@livb4139 Год назад

39:02 "unfortunate choice of variable names" lmfao

@EchoVids2u 5 лет назад

30:29 Shouldn't the root then be = 8 ?

@EtzEchad 6 месяцев назад

The game tree depth is just one factor. I bigger problem is the evaluation of the board at each level. That is what makes current chess engines winners.

@vasugupta1 6 лет назад

very nicely explained the concepts my ai lecturer couldnt teach

@khairolhazeeq5426 4 года назад

I have a few questions. The first one is, is Minimax considered as a state space search? If it is is there a Goal state/node?

@MrChanyw 9 лет назад

Great explanation minimax saved my ass! thankssss

@xinxingyang4477 4 года назад

A problem I can not understand about the minimax algorithm is about the other player. Do we consider the other player can make the same calculation of the tree to a similar depth? What if they can not and made some decisions to different branches... Will that be a problem? Or not a problem?

@XTrumpet63X 7 лет назад

I feel proud that I've been watching MIT lectures enough to have gotten the "celebration of learning" reference. xD

@axelkennedal5656 5 лет назад

What does it mean?

@jamesbalajan3850 4 года назад

@@axelkennedal5656 Euphemism for an exam?

@myrsinivak6993 6 лет назад

When exactly does A-B prune the most nodes?

@rahulaollove 6 лет назад

what software is he using for it ?

@Griff10poldi 7 лет назад

Finally I understand this :O

@majusumanto9016 5 лет назад

I find something here about alpha & betha, what if we're changing the position between 3 and 9 on the left tree...then the first cut off wouldn't happen... so the interesting thing is the alpha betha depended on the evaluation method... For example if you're doing evaluation from the right position so the cut-off will be different :D ... anyway thank you for the explanation... it's really clear

@rj-nj3uk 5 лет назад

When the intro didn't said "This content is provided under MIT open course ware...." I thought my earphone broke.

@WepixGames 4 года назад

R.I.P Patrick Winston

@haoyangy7026 6 лет назад

Jeez this prof is so cool in the way he talks about things wish I have a teacher like that so I don't have to watch this in a class with a super bad teacher lol

@nicoscarpa 5 лет назад

In the alpha-beta example, the branch that doesn't actually get created is just the right-most one that leads to the terminal node (not computed, because of the "cut"). Is that right? If it's right, than the statement "it's as if that branch doesn't exist" (24:00) must be interpreted such that the algorithm will never choose the action that leads to the right-hand node (the one

@spectator5144 Год назад

yes

@alpotato6531 5 месяцев назад

rip. great explanations!

@tcveatch 6 месяцев назад

On full depth search (13:44 ish) he says 10*(80+10+9+7) = 10^106 but it’s actually 10^116. Sure his point holds but he’s just off by a factor of 10^10=10 billion.

@GettoFeng 9 лет назад

anybody got what the student said at 42:00 ?

@cagmz 7 лет назад

Can anyone explain how the deep cut off works at 28:13? Is the maximizer making a comparison from the root to the minimizer value just above the leaf?

@amitrokade1140 7 лет назад

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..

@rnmisrahi 2 года назад

Small error: to convert seconds to nanoseconds you need to add 6 to the exponential factor, not 3. Still, this would not impact the point made by this brilliant professor

@AZZEDDINE2801 9 лет назад

thanks

@BertVerhelst 9 лет назад

I wonder how much you save by using the tree of the last move as a basis for the next one, since the min player can be a human, and he might not take the branch you predicted. So the alpha beta algorithm assumes the min player will always take the option that is most in the min player's own interest, which is not always the case in computationally "flawed" humans.

@richardwalker3760 9 лет назад

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.

@MichielvanderBlonk 2 года назад

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