[Computer-go] action-value Q for unexpanded nodes
andy.olsen.tx at gmail.com
Wed Dec 6 05:31:32 PST 2017
Thanks for letting us know the situation Aja. It must be hard for an
engineer to not be able to discuss the details of his work!
As for the first-play-urgency value, if we indulge in some reading between
the lines: It's possible to interpret the paper as saying
first-play-urgency is zero. After rereading it myself that's the way I read
it now. But if that is true maybe Aja would have said "guys the paper
already says it is zero." That would imply it's actually some other value.
That is probably reading far too much into Aja's reply, but it's something
to think about.
2017-12-06 4:47 GMT-06:00 Aja Huang <ajahuang at gmail.com>:
> 2017-12-06 9:23 GMT+00:00 Gian-Carlo Pascutto <gcp at sjeng.org>:
>> On 03-12-17 17:57, Rémi Coulom wrote:
>> > They have a Q(s,a) term in their node-selection formula, but they
>> > don't tell what value they give to an action that has not yet been
>> > visited. Maybe Aja can tell us.
>> FWIW I already asked Aja this exact question a bit after the paper came
>> out and he told me he cannot answer questions about unpublished details.
> Yes, I did ask my manager if I could answer your question but he
> specifically said no. All I can say is that first-play-urgency is not a
> significant technical detail, and what's why we didn't specify it in the
>> This is not very promising regarding reproducibility considering the AZ
>> paper is even lighter on them.
>> Another issue which is up in the air is whether the choice of the number
>> of playouts for the MCTS part represents an implicit balancing between
>> self-play and training speed. This is particularly relevant if the
>> evaluation step is removed. But it's possible even DeepMind doesn't know
>> the answer for sure. They had a setup, and they optimized it. It's not
>> clear which parts generalize.
>> (Usually one wonders about such things in terms of algorithms, but here
>> one wonders about it in terms of hardware!)
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