[Computer-go] alarming UCT behavior

[Gonçalo Mendes Ferreira]

That doesn't seem very realistic. I'd guess your prior values are 
accurate but the simulations are biased or not representative. Or you 
miss precision in your transition quality floating points. Or there's a 
bug related to being an adversarial problem and you didn't have the 
robots swap colors? :)

Do tell what it was when you discover the problem.

Gonçalo F.

On 06/11/2015 18:48, Dave Dyer wrote:
> Developing a UCT robot for a new game, I have encountered a
> surprising and alarming behavior:  the longer think time the
> robot is given, the worse the results.  That is, the same robot
> given 5 seconds per move defeats one give 30 seconds, or 180 seconds.
>
> I'm still investigating, but the proximate cause seems to be
> my limit on the size of the UCT tree.   As a memory conservation
> measure, I have a hard limit on the size of the stored tree. After
> the limit is reached, the robot continues running simulations, refining
> the outcomes based on the existing tree and random playouts below
> the leaf nodes.
>
> My intuition would be that the search would be less effective in this
> mode, but producing worse results (as measured by self-play) is
> strongly counter intuitive.
>
> Does it apply to Go?  Maybe not, but it's at least an indicator
> that arbitrary decisions that "ought to" be ok can be very bad in
> practice.
>