cma6:
There is a link in the first post of the thread.
We've already said N is the number of visits.
Lc0 Evaluation Explanation
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Re: Lc0 Evaluation Explanation
Last edited by jp on Fri Aug 30, 2019 11:47 pm, edited 1 time in total.
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Re: Lc0 Evaluation Explanation
I'm actually a newcomer to NN engines, so I'm still learning. I believe P is the probability that the move is the right one to play in this position, based solely on the output of the net, with no additional searching/roll outs. So the P values give an initial suggestion of which moves are likely good ones, and so worthy of further analysis. There is a discussion of these various variables here:cma6 wrote: ↑Fri Aug 30, 2019 11:13 pm Zulli:
Do you know the meaning of these terms: "P", "Q", "Q+U", & "V"?
I am guessing that V = visits. But, as pointed out, Be2 does not have the highest V value of all the moves shown. Or does the lc0 site have an explanation of the parameters, since when I searched here for "visits", it gave me no new information.
https://github.com/LeelaChessZero/lc0/w ... Chess-Zero
Love to find something better, but not as technical as reading a research article!
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Re: Lc0 Evaluation Explanation
Zullil:
Thanks for the excellent link.
Thanks for the excellent link.
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Re: Lc0 Evaluation Explanation
I found the meaning of the "(+7)", etc. It's "how many visits are processed by other threads when this is printed".
I still don't know what the "(712)", etc. mean.
By useful interpretation, I guess you mean from the chess point of view. Many of these outputted variables may be mainly useful from the computing point of view.
If it just chooses Q, it'll run into the standard MCTS problem where an engine "may favor a losing move with only one or a few forced refutations, due to the vast majority of other moves providing a better random playout score than other, better moves".
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Re: Lc0 Evaluation Explanation
Code: Select all
e2e4 (123) N: 329 (+ 4) (V: -12.34%) (P:38.12%) (Q: -0.2325) (U: 0.2394) (Q+U: 0.0069)
^ ^ ^ ^ ^ ^ ^ ^ ^
| | | | | | | | Q+U, see below
| | | | | | | U from PUCT formula,
| | | | | | | see below.
| | | | | | Average value of V in a subtree
| | | | | Probability of this move, from NN, 0%..100%
| | | | Expected outcome for this position, directly from NN, -100%..100%
| | | How many visits are processed by other threads when this is printed.
| | Number of visits. The move with maximum visits is chosen for play.
Move |
Internal move id (for debugging)
* U = P * Cpuct * sqrt(sum of N of all moves) / (N + 1)
CPuct is a search parameter, can be changed with a command line flag.
* The move with largest Q+U will be visited next
* The move with the highest N is played when search is stopped
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Re: Lc0 Evaluation Explanation
Nice that the most useful explanation came right on my birthday
Yes, useful was meant from a chess point of view. More specifically I am looking for ideas on how to decide between
different moves for correspondence chess (CC) but also for an OTB opening repertoire. In CC often times one prefers
complex positions to simple ones and one tries to avoid drawing lines and I am hoping to get such info from the lc0
output. Exciting would be to see the draw-percentage from the playouts.
Yes, useful was meant from a chess point of view. More specifically I am looking for ideas on how to decide between
different moves for correspondence chess (CC) but also for an OTB opening repertoire. In CC often times one prefers
complex positions to simple ones and one tries to avoid drawing lines and I am hoping to get such info from the lc0
output. Exciting would be to see the draw-percentage from the playouts.