[Computer-go] AlphaZero tensorflow implementation/tutorial

cody2007 cody2007 at protonmail.com
Sun Dec 9 17:07:41 PST 2018


Thanks for your comments.

>looks you made it work on a 7x7 19x19 would probably give better result especially against yourself if you are a complete novice
I'd expect that'd make me win even more against the algorithm since it would explore a far smaller amount of the search space, right?
Certainly something I'd be interested in testing though--I just would expect it'd take many months more months of training however, but would be interesting to see how much performance falls apart, if at all.

>for not cheating against gnugo, use --play-out-aftermath of gnugo parameter
Yep, I evaluate with that parameter. The problem is more that I only play 20 turns per player per game. And the network seems to like placing stones in terrotories "owned" by the other player. My scoring system then no longer counts that area as owned by the player. Probably playing more turns out and/or using a more sophisticated scoring system would fix this.

>If I don't mistake a competitive ai would need a lot more training such what does leela zero https://github.com/gcp/leela-zero
Yeah, I agree more training is probably the key here. I'll take a look at leela-zero.

‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐
On Sunday, December 9, 2018 7:41 PM, Xavier Combelle <xavier.combelle at gmail.com> wrote:

> looks you made it work on a 7x7 19x19 would probably give better result especially against yourself if you are a complete novice
>
> for not cheating against gnugo, use --play-out-aftermath of gnugo parameter
>
> If I don't mistake a competitive ai would need a lot more training such what does leela zero https://github.com/gcp/leela-zero
>
> Le 10/12/2018 à 01:25, cody2007 via Computer-go a écrit :
>
>> Hi all,
>>
>> I've posted an implementation of the AlphaZero algorithm and brief tutorial. The code runs on a single GPU. While performance is not that great, I suspect its mostly been limited by hardware limitations (my training and evaluation has been on a single Titan X). The network can beat GNU go about 50% of the time, although it "abuses" the scoring a little bit--which I talk a little more about in the article:
>>
>> https://medium.com/@cody2007.2/alphazero-implementation-and-tutorial-f4324d65fdfc
>>
>> -Cody
>>
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>>
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