Komodo 13 released

[lkaufman]

I have a question. If I purchase chessbase Komodo 12 (or latest chessbase version)
then can I get the newest version of the engine?

Basically I want the newest Komodo with the latest chessbase GUI.

Then just wait a few days until Komodo 13 goes on sale on the chessbase website. They haven't announced anything yet, but in the past they always release within a couple weeks of any new integer version of Komodo on our website.

Ok thanks. And if I get Komodo 13 then do I get a year of engine updates? Or just all updates from 13 and prior to version 14 ?

No, ChessBase only gives free updates for the first two months.

[Nordlandia]

No recent fritz update in quite a while now. Someone said they'll give fritz and chessbase 7-piece support, but when is another question.

[Damir]

Chessbase release bullshit updates every time.... so no need for any of them…. thank you very much.

[lkaufman]

Chessbase release bullshit updates every time.... so no need for any of them…. thank you very much.

I don't know about Chessbase updates in general, but any updates they do for Komodo are ones that we give them because we are releasing them to our customers, so they are legit. But the contract only calls for two month of such updates.

[Marcus9]

Congratulations for Komodo 13!
Do you think the MCTS version can finally give knight odd to an FM with convincing results?
It would be great to see him in action in another odd match

[leavenfish]

No recent fritz update in quite a while now. Someone said they'll give fritz and chessbase 7-piece support, but when is another question.

Fritz...is mainly about the features in the GUI, not about simple chasing of (rating) numbers. They are too smart a company to chase numbers and instead focus on functionality - the 'best' engines are free.

[leavenfish]

~snip~

The scores reported by an MCTS engine like Komodo MCTS already reflect the possiblility of the opponent going wrong in plausible ways. Maybe it doesn't do it the same way you would, but at least to a significant degree it does what you want.

That's really interesting. If this is possible with MCTS, have you considered adding a mode to Komodo which adds more weight to the possibility of the opponent going wrong, which would allow people to find trappy lines in analysis?

If regular Komodo did that, it would just become a much weaker cousin of Komodo MCTS. That's the fundamental difference between standard ("Alpha-Beta") engines and MCTS engines; standard ones assume that the opponent will always play the move the engine considers best, whereas MCTS assumes that all reasonable moves have some chance of being chosen. Komodo MCTS (and Lc0 and spinoffs if you have suitable GPU) are the engines you should use.

There seems to be no real info on the Komodo website about vs 13.

Is there some info you can point me to about exactly how MCTS really works? I would like to see how, as you say, it 'already reflects the possibility of the opponent going wrong in plausible ways'. If it in some ways already does what I do manually for opening anaylsis, then it might be worth getting.

Otherwise, if you just look at certain tests that assign ratings for results, there has been little to no real improvement since K11.3.1 (perhaps even regression according to some) which I already have. The only thing 'new' being MCTS - which at least in 'play' is even weaker, but I am only interested in an analysis partner.

[lkaufman]

Congratulations for Komodo 13!
Do you think the MCTS version can finally give knight odd to an FM with convincing results?
It would be great to see him in action in another odd match

Assuming you are talking about long (45' + 15") games, I rather doubt it. Our record against the last two FMs at that time control giving knight odds was two draws out of 7 games with regular Komodo, and I doubt that MCTS will do so much better as to overcome a 6 to 1 score deficit. But maybe we'll try it anyway, they are both still active and available. In chess960 it's another story, we already beat one of them 4 to 0 giving knight odds.

[lkaufman]

~snip~

The scores reported by an MCTS engine like Komodo MCTS already reflect the possiblility of the opponent going wrong in plausible ways. Maybe it doesn't do it the same way you would, but at least to a significant degree it does what you want.

That's really interesting. If this is possible with MCTS, have you considered adding a mode to Komodo which adds more weight to the possibility of the opponent going wrong, which would allow people to find trappy lines in analysis?

If regular Komodo did that, it would just become a much weaker cousin of Komodo MCTS. That's the fundamental difference between standard ("Alpha-Beta") engines and MCTS engines; standard ones assume that the opponent will always play the move the engine considers best, whereas MCTS assumes that all reasonable moves have some chance of being chosen. Komodo MCTS (and Lc0 and spinoffs if you have suitable GPU) are the engines you should use.

There seems to be no real info on the Komodo website about vs 13.

Is there some info you can point me to about exactly how MCTS really works? I would like to see how, as you say, it 'already reflects the possibility of the opponent going wrong in plausible ways'. If it in some ways already does what I do manually for opening anaylsis, then it might be worth getting.

Otherwise, if you just look at certain tests that assign ratings for results, there has been little to no real improvement since K11.3.1 (perhaps even regression according to some) which I already have. The only thing 'new' being MCTS - which at least in 'play' is even weaker, but I am only interested in an analysis partner.

For analysis, there are two reasons you might want to use Komodo 13.01 MCTS. !. If you analyze in MultiPV Mode, Komodo MCTS is stronger than normal Komodo, because being forced to analyze multiple lines to get a score cripples all Alpha-Beta engines but is free for MCTS. 2. MCTS assumes that there is some probability that every legal move will be played at any point, with the probability depending on how good the move appears to be. So if other replies are inferior but not "obviously bad" that will make your candidate move look better. The more plausible ways there are to go wrong for the opponent, the better your move will look.

[chrisw]

~snip~

The scores reported by an MCTS engine like Komodo MCTS already reflect the possiblility of the opponent going wrong in plausible ways. Maybe it doesn't do it the same way you would, but at least to a significant degree it does what you want.

That's really interesting. If this is possible with MCTS, have you considered adding a mode to Komodo which adds more weight to the possibility of the opponent going wrong, which would allow people to find trappy lines in analysis?

If regular Komodo did that, it would just become a much weaker cousin of Komodo MCTS. That's the fundamental difference between standard ("Alpha-Beta") engines and MCTS engines; standard ones assume that the opponent will always play the move the engine considers best, whereas MCTS assumes that all reasonable moves have some chance of being chosen. Komodo MCTS (and Lc0 and spinoffs if you have suitable GPU) are the engines you should use.

I think that’s a bit cart before horse. Both MCTS and AB “assume” all (reasonable) moves have some chance of being played, else they would not be searching them.

AB creates and examines a tree like a little mouse that runs up and down branches examining the leaves on a sort of start at the left and end at the right basis. AB finds and outputs a PV which says: here’s a branch down the tree which picks out an optimal path to a tree leaf with a score that my opponent can’t stop me from achieving.

MCTS make single foray stabs into the tree. It stabs down a line, gets to the end, evaluates, and returns to the root. Then another stab, and so on. Stabs go into regions of the tree. MCTS finds an outputs a move which says: if I play this move, my opponent has several reasonable replies, and I have some reasonable replies to his reasonable replies, and so on, where I found that my stabbing forays, on average, in this particular region of the tree, led to leaves where I was winning more often than my opponent.

Richard Lang, a long time ago, likened search (which was AB) to picking a path through a minefield in order to reach the pot of gold at the other side without stepping on any mines. That’s a good summation of AB search.
By extension, MCTS search is about entering a minefield with disparate regions, where some mines are set to blow you up, and some set to blow up your opponent. MCTS avoids the regions full of mines that blow it up, and steers to the regions where are the mines that blow up its opponent.
So, AB is on the lookout for tactical pathways and MCTS plays positionally until its opponent position just disintegrates all by itself.