Komodo 13 released

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Ovyron
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Re: Komodo 13 released

Post by Ovyron » Mon May 20, 2019 6:39 pm

Gabor Szots wrote:
Thu May 09, 2019 7:58 am
Ovyron wrote:
Wed May 08, 2019 8:48 pm
Gabor Szots wrote:
Tue May 07, 2019 6:32 am
Where do I set MultiPV under the Shredder GUI?
It seems that you can't set MutiPV under the Shredder GUI (it hides the setting in engine options, and doesn't allow to set it directly; I had to make my own compile of McCain that calls it "MultiPW" just to fix this.)

The best you can do is using the F6 Key to increase MutiPV lines by one, and the F5 Key to decrease them by one, but it's impossible to play MultiPV games in the Shredder GUI (as it defaults to 1 in play mode.)
Thank you for your reply. I edited my Komodo eng file to include a line MultiPV=6, only I don't know whether it has an effect.
Haha! Whoa, yes, it does! And it works for any engine! :D This is a clever solution, and I was having to edit engine code and make my own compile to achieve what adding this line on option does :)

So here's the thing, Shredder GUI doesn't know this is Multi-PV output, so it treats it like normal output. If you're using an older version of Shredder Classic, right-click the analysis panel and tick the "Continuous Display" option so you don't mix anything.

The difference is that on normal output the best move is always shown at the very bottom of the analysis, while with a setting like MultiPV=6, the 6th best move is shown at the very bottom, with the 5th best in the previous line, and the 4th best in the previous line and so on.

I believe this was the reason engines like McCain's Tactical Setting or ShashChess's Deep Analysis Mode just switch MultiPV like this (no different than setting MultiPV in engine options), except they hide the scores of non-best moves so the score of the best one still appears at the bottom (even though for analysis knowing the scores of all those moves for free is very useful, not just finding the best move unattended.)

Thanks for this concept, now all engines that support MultiPV are able to use McCain's Tactical Setting by setting it in engine options :mrgreen:
Great spirits have always encountered violent opposition from mediocre minds.

schack
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Re: Komodo 13 released

Post by schack » Tue May 21, 2019 8:26 pm

How many rollouts per second does one core of K13.01 achieve? I know this will differ greatly based on processor and processor speed, but is there a rough way to know?

lkaufman
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Re: Komodo 13 released

Post by lkaufman » Tue May 21, 2019 9:30 pm

schack wrote:
Tue May 21, 2019 8:26 pm
How many rollouts per second does one core of K13.01 achieve? I know this will differ greatly based on processor and processor speed, but is there a rough way to know?
\

On my fast laptop, using one core only, it reports 1000 nodes after 12 seconds in opening position, so 83 nps. It doesn't sound like enough to even play chess, but each of these nodes is based on thousands of regular nodes searched, so if we counted nodes that way it might be in the ballpark of a million or so nps on one core.
Komodo rules!

collins1982
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Re: Komodo 13 released

Post by collins1982 » Wed May 22, 2019 6:31 am

i need this engine

schack
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Re: Komodo 13 released

Post by schack » Wed May 22, 2019 2:15 pm

@larry - Can you explain what the search tree looks like in layman's terms? I'm curious as to how this operates.

mjlef
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Re: Komodo 13 released

Post by mjlef » Wed May 22, 2019 5:23 pm

schack wrote:
Wed May 22, 2019 2:15 pm
@larry - Can you explain what the search tree looks like in layman's terms? I'm curious as to how this operates.
With standard alpha-beta search, the programs just explore alone one line at a time, only saving/remembering the best line. With MCTS search, the whole game tree is stored in memory as a linked list of nodes. A node is a position. So the root node is simply the position on the board being searched. Its child nodes are the positions made after making a move from the root. The game tree is expanded a by formula with two parts. One part is simple the average win probability for that position and is the Exploit part of the formula. The other part is an Explore part which helps ensure the program looks at positions with a lower win probability, just in case a deeper search of them leads to something better. You select the best mode and repeat, deeper and deeper in the tree. When you hit a leaf node (with no children) you expand them and return a win probability up the line in the tree you traversed, addin in the win probability of the new node, adjusted for the side to move.

Each node has a bunch of numbers like a count how often this nodes has been selected, The sum of the win probabilities, a number called policy to help select the nodes, perhaps node locking stuff so only one processor works on updating that node at a time and so on.

Mark

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