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Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

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Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#31

Post by irascible »

forgot-my-pw wrote: post #15

I don't think we can learn much from how an engine learns, but we certainly can learn from its results. For example, there's this interesting discussion: https://www.reddit.com/r/chess/comments/7ibzq4/stockfish_vs_... Because Alphazero did not learn from human games, it looks at the different pieces without attaching values like we do. It has no problems sacrificing a higher "valued" piece for the sake of its strateg…

Yeah. Our human chess heuristics are biased toward strategies that fit within a human working memory. Alphagos working memory is orders of magnitude larger.

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#32

Post by infinity0 »

ansible wrote: post #27
infinity0 wrote: post #19

Earlier quoted context omitted.

What are the winning conditions for math?

A smaller proof using fewer axioms or other proofs than the current state-of-the-art. Discovering new and "interesting" proofs. Don't ask me to define "interesting" in this context.

It's exactly my original point that these goals are not well-defined in early 21st century maths.

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#33

Post by seanwilson »

ansible wrote: post #27
infinity0 wrote: post #19

Earlier quoted context omitted.

What are the winning conditions for math?

A smaller proof using fewer axioms or other proofs than the current state-of-the-art. Discovering new and "interesting" proofs. Don't ask me to define "interesting" in this context.

In the field of formal/machine proofs, nobody really cares about the length of the proofs because part of the point is the proofs are checked by the computer back to the basic axioms so you can trust the proofs are correct. Being able to discover long and ugly proofs to difficult theorems or coming up with new theorems would have endless applications.

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#34

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Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#35

Post by pixl97 »

eutropia wrote: post #18

Remember that AlphaZero played 44 million games of chess, whereas your average professional chess player has played somewhere on the order of 10,000-100,000. Self-play works, but rather slowly.

How many years did it take the professional to play 100,000 games? How many minutes did it take AGZ to play 44M? It sounds like self play is rather fast to me.

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#36

Post by ararar »

jdoliner wrote: post #26
markussss wrote: post #24

Earlier quoted context omitted.

>unfortunately I'm blanking on his name John Nash (supposedly) had this mindset? Is that who you're thinking about?

That wasn't who I had in mind, but thanks for sharing that example. I think the guy I'm thinking of is at Cornell and still alive. He also might actually be in CS instead of Math. I tried googling it but, unfortunately, "math professor who doesn't read papers" didn't come up with any results.

You might be thinking of R.L. Moore and his "Moore Method" except it was only used in a teaching context, not in day to day work. See https://en.wikipedia.org/wiki/Moore_method

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#37

Post by ararar »

I think there is a possibility of applying machine learning to teaching humans in the sense of continuous, algorithmic tuning/personalization of lesson plans/teaching strategies to accelerate human learning ... as a teacher's aide in other words.

Re: Ask HN: Can we adapt AlphaZero's self-play technique for better human learning?

#38

Post by SamReidHughes »

jdoliner wrote: post #26
markussss wrote: post #24

Earlier quoted context omitted.

>unfortunately I'm blanking on his name John Nash (supposedly) had this mindset? Is that who you're thinking about?

That wasn't who I had in mind, but thanks for sharing that example. I think the guy I'm thinking of is at Cornell and still alive. He also might actually be in CS instead of Math. I tried googling it but, unfortunately, "math professor who doesn't read papers" didn't come up with any results.

Maybe it was a physics professor.
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