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Player of Games

arxiv.org

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Re: Player of Games

#61

Post by _0ffh »

OneTimePetes wrote: post #46
doctor_eval wrote: post #9

Earlier quoted context omitted.

I suppose it's better than "Use of Weapons".

Why not have a seat, take that chair over there.

One of the best, and executed to perfection! You can sort-of-see the point coming for a long, long time in the book, as he gradually builds the suspicion by dropping the occasional hint here and there, but it's always so that it must remain a highly uncertain speculation until he drops the reveal. Just the right balance between "How should I have suspected that?" and "Those hints were too much on the nose!".

Re: Player of Games

#62

Post by [deleted] »

sdenton4 wrote: post #3

This is clearly part of DeepMind's long-game plan to achieve world domination through board game mastery. Naming the new algorithm after the book is a real tip of their hand... https://en.wikipedia.org/wiki/The_Player_of_Games

[deleted]

Re: Player of Games

#64

Post by WithinReason »

sdenton4 wrote: post #3

This is clearly part of DeepMind's long-game plan to achieve world domination through board game mastery. Naming the new algorithm after the book is a real tip of their hand... https://en.wikipedia.org/wiki/The_Player_of_Games

"In 2015, two SpaceX autonomous spaceport drone ships—Just Read the Instructions and Of Course I Still Love You—were named after ships in the book, as a posthumous tribute to Banks by Elon Musk"

Re: Player of Games

#65

Post by _0ffh »

JanneVee wrote: post #34
_tkii wrote: post #23

Earlier quoted context omitted.

Why?

I don't know how go changed. But as for chess the tournament play at the master level have insane deep opening preparation done before with computers. They play preparation game where they try to guess what lines the opponent checked and memorized before the games. They aren't actually playing until their computer backed preparation ends more than the few moves that they have fed in to come up with something differen…

Yeah, I guess half the opening is hoping to kick the opponent out of his preparations while staying within your own. Or maybe all.

Re: Player of Games

#67

Post by fho »

nicolodavis wrote: post #55
fho wrote: post #43

Earlier quoted context omitted.

I tried my hand once or twice at (re-)implementing board games [0], so that I could run some common "AI" algorithms on the game trees. What tripped me up every time is that most board games have a lot of "if this happens, there is this specific rule that applies". Even relatively simple games (like Homeworlds) are pretty hard to nail down perfectly due to all the special cases. Do you, or somebody else, have any reco…

You could consider using a library like boardgame.io for this.

I'll look into that.

Re: Player of Games

#68

Post by loxias »

sillysaurusx wrote: post #40
fxtentacle wrote: post #39

This is a great result, but you can see that it's more of a theoretical case because of this: "converging to perfect play as available computation time and approximation capacity increases." That is true for pretty much all current deep reinforcement learning algorithms. The practical question is: How much computation do you need to get useful results? Alpha Go Zero is impressive mathematics, but who is willing to sp…

You often don't need anywhere near the amount of compute in these papers to get similar performance. Suppose you're a business that needs to play games. Most people seem to think that it's a matter of plugging in the settings from the paper, buying the same hardware, then clicking a button and waiting. It's not. The specific settings matter a lot. But my main point is that you'll get most of your performance pretty r…

My thoughts, not being in the field, are parallel to the parent post. "It's nice and all that we're achieving better and better computer performance at things that used to require the human brain, but it seems we're doing so by building larger and larger computers."Not to detract from that achievement, I love large computers in their own right!

I'm a dabbler in Go, and "somewhere below professional" at the game of poker. I've followed the advances in the latter for more than a decade, eagerly reading every paper the CPRG publishes. They use a LOT of compute power!

I know from experience that "The specific settings matter a lot.". For several years, I made my living "implementing papers for hire". It's real work, no argument there. Sometimes the settings are the solution, and heck, sometimes the published algorithm is outright wrong, and you only discover so when trying to implement it.

But the second part of your point, that it's not simply achieving more performance by throwing more transistors at it, I don't have experience with, and I sorta don't believe you. :)

Your comment is quite well written, making me (irrationally?) predisposed to suspect you're correct on factual matters, or at least more of a domain expert than I. Can you cite sources, or simply elaborate more?

Re: Player of Games

#70

Post by loxias »

wetpaws wrote: post #17
wly_cdgr wrote: post #14

The future is so depressing

Fun fact: The consensus between professional go and chess players is that all new AI systems (alphago, etc) have really revitalised the game and introduced incredible amount of new strategies and depth.

I wish alphago was more "democratized" -- that is to say, I have many questions and experiments I'd love to run on it (a friend of mine and I have frequently pondered Go played in various different topological spaces, and I'd love to see an AI's result, for example).
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