Comments (5)
You are right.
Win: Ray plays the biggest Count move. For example, by only 1 search, Win 100% or 0%. Playing that 100% winning move doesn't make sense.
At first ray tends to select bigger policy moves. After thinking more and more, ray selects bigger Win moves.
from ray.
Thanks for your prompt reply.
Sometime, I get not data for Win:
|Move|Count|Simulation|Policy |Value |Win |Best Sequence
| F17| 409| 50.3667| 69.7768|||w C10
| P17| 157| 52.8662| 25.1722|||w C6
| C6| 104| 51.9231| 0.2533| 55.9466| 55.1419|w F4
| O17| 11| 36.3636| 2.5871|||
| F3| 9| 22.2222| 0.2220| 53.7620| 47.4540|
| P16| 6| 50.0000| 1.0271|||
| C14| 4| 75.0000| 0.2098|||
Is that an indication that my computer is not fast enought? That I should give more thinking time to Ray?
from ray.
Do you use ray without GPU and with multi thread e.g. --thread 4
?
Current Rn's network is too heavy for CPU, so NN evaluation didn't complete in time.
from ray.
My computer is old and slow (no GPU) that's why.
But for my application, it is not a problem. The important thing is that when I got missing values for Win I can issue a warning to the user to tell him to increase the thinking time.
Thanks!
from ray.
@pnprog Perhaps --reuse-subtree
is useful for goreviewpartner.
from ray.
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from ray.