Rybka's knowledge

[Uri Blass]

http://rybkaforum.net/cgi-bin/rybkaforu ... t#pid22743

From Larry kaufman:

"I will make the general observation that if you give any other program enough time handicap to equalize the score against Rybka, and then you double the times for both programs, the result will depend very much on which version of Rybka is being tested. The earliest version of Rybka had very limited chess knowledge, and so should gain less than other programs with increased time. Each successive version had more knowledge, and my guess is that by 2.3.2 the chess knowledge was better than most other programs (though not all)"

In other words Larry admit that there are chess programs with more chess knowledge than rybka2.3.2a

I was surprised to read it because I expected the rybka team not to admit that there are programs with better knowledge than rybka.

I remember the times when vasik claimed that he believes that the main advantage of rybka beta is her evaluation(he did not deny that rybka has a good search but claimed that the main advantage relative to top programs is the evaluation).

[Gandalf]

My guess is that knowledge != evaluation. You can add all the chess theory that exists and still have a relatively bad evaluation function because of weights, efficiency, and other factors.

[Mike S.]

It is not clear to me why an engine with big knowledge would gain more from increased time, than an engine with small knowledge. (If it was the other way around, it wouldn't be clear to me why, either )

Maybe someone can explain the concept or the "mechanics" behind that , how or why more/less knowledge affects the gain from more time?

[revengeska]

I believe it's because more knowledge slows the program's search down, therefore hitting ply slower, and making the extra time more valuable. Less knowledge means a faster search, but since the number of moves needed to reach the next ply multiply astronomically rather quickly, the program with less knowledge really doesn't get a large gain from increased time.

In short, with more time, prorams with more knowledge will be able to catch up in ply with programs with less knowledge despite the difference in speed, when more time is allotted to think.

[Ryan Benitez]

It is not clear to me why an engine with big knowledge would gain more from increased time, than an engine with small knowledge. (If it was the other way around, it wouldn't be clear to me why, either )

Maybe someone can explain the concept or the "mechanics" behind that , how or why more/less knowledge affects the gain from more time?

Chess is a game of tactics unless there are not tactics at the time within your reach. Then you better your position so you can find some tactics later. The longer the game the fewer tactical mistakes.

[revengeska]

It is not clear to me why an engine with big knowledge would gain more from increased time, than an engine with small knowledge. (If it was the other way around, it wouldn't be clear to me why, either )

Maybe someone can explain the concept or the "mechanics" behind that , how or why more/less knowledge affects the gain from more time?

Chess is a game of tactics unless there are not tactics at the time within your reach. Then you better your position so you can find some tactics later. The longer the game the fewer tactical mistakes.

The question is in regards to computers, not humans:)

[Uri Blass]

My intuition tells me that it is the case for most types of knowledge and I can explain why it is the case.

imagine that your program does not know that it is bad to trade a piece for 3 pawns.

At small depth the mistake is not very important because there are going to be tactical mistakes later and at long time control the mistake is more important and the program is not going to be able to avoid the mistake at reasonable depth.

Here is a practical example from the noomen match that I play often between movei and fruit2.0

[D]r4rk1/1bpqbppp/p1np1n2/1p2p1B1/3PP3/1BP2N1P/PP3PP1/RN1QR1K1 b - - 0 11 am Nxe4


Fruit2.0 blunders by Nxe4 at depths 11-17 and probably also at bigger depths because it overevaluates pawns.
It is a positional blunder that search does not help to avoid.

It seems to me clear that fruit2.0 has better chances to win at fast time control after that blunder and not at slow time control..
Uri

[Michael Sherwin]

It is not clear to me why an engine with big knowledge would gain more from increased time, than an engine with small knowledge. (If it was the other way around, it wouldn't be clear to me why, either )

Maybe someone can explain the concept or the "mechanics" behind that , how or why more/less knowledge affects the gain from more time?

Chess is a game of tactics unless there are not tactics at the time within your reach. Then you better your position so you can find some tactics later. The longer the game the fewer tactical mistakes.

Thank you Ryan! This is what I have been trying to explain for the longest time.

In a position void of any winning tactics the evaluation rules!

Mike

[Uri Blass]

You first need to define tactics.
Every win in chess is tactics if you search deep enough and search clearly help programs to find better positional moves.

There are some type of positional moves that you cannot find by search when you have a bad evaluation and this is the reason that I think that evaluation can be more important at long time control but things are not so simple.

There may be cases when evaluation is less important at long time control.

An example:knowledge in the evaluation how to win some simple endgames may be productive at blitz but not productive at long time control when you can find the win by search.

Uri

[Michael Sherwin]

You first need to define tactics.
Every win in chess is tactics if you search deep enough and search clearly help programs to find better positional moves.

There are some type of positional moves that you cannot find by search when you have a bad evaluation and this is the reason that I think that evaluation can be more important at long time control but things are not so simple.

There may be cases when evaluation is less important at long time control.

An example:knowledge in the evaluation how to win some simple endgames may be productive at blitz but not productive at long time control when you can find the win by search.

Uri

Okay, I will try.

Tactics that one program sees immediately that the other program failed to see will result in a lowering of the evaluation (eventually) for the program that did not see the tactics. If neither program can find any tactics that will cause an immediate decrease in the evaluation for the other side then the position is not considered as one that is solved tactically.

In the above case the program with the better evaluation will more often, get tactical opportunities to cause a lowering in the other programs evaluation, first.