expRate

[deeds]

OK thanks! I will update when the engine has learned 1000 moves in my favorite opening.
It was just misleading for me when in the thread "training mode (Eman) with trouney mode (Raptora)" you already had a learning rate of 6% after a few rounds.

The Eman's experience file already learned 2 openings of the Sedat's Unique v50 opening list (expRate = 4%). After 2-3 rounds, it learned another opening (expRate = 6%). It's not hard to understand if Eman did more rounds, it would learn more openings. But as i don't want to help cheaters, i limited the rounds in order to reduce the amount of published Eman's moves.

[Martin_1969]

I see you didn't quite understand me. In your experiment "training mode (Eman) with trouney mode (Raptora)" you played a total of 300 games, covering only 1/5 of the Unique v50 openings. BUT your engine achieved a learning rate of 6%.
I think the learning rate is exaggerated. Because after 500 games and only one opening line of my choice I reach a learning rate of 0%. You can easily check this. Play 300 games and only one opening line with a fresh learning file and you will see that after 300 games played by the engine the result is 0% learning.
I like a lot of what you write, but not everything.

Everyone else can check this for themselves

All I'm saying is that you need a lot more games than just a few hundred or thousand, and that's quite painful because there are so many possible moves that only a very small part can be covered by this system.
Bye Martin

[deeds]

...
I think the learning rate is exaggerated. Because after 500 games and only one opening line of my choice I reach a learning rate of 0%.
...
Play 300 games and only one opening line with a fresh learning file and you will see that after 300 games played by the engine the result is 0% learning.
...

I think to draw conclusions from just one opening it is exaggerated, especially when the threshold of 500 games/opening was checked by the authors of the learning engines and the learning features. Maybe even in the face of the evidence, you wouldn't accept the result if it said the opposite of your thinking.

All I'm saying is that you need a lot more games than just a few hundred or thousand, and that's quite painful because there are so many possible moves that only a very small part can be covered by this system.
Bye Martin

This is the weak point of your reasoning. Engine learning is not a brute-force calculation. Every possible move doesn't have to be tried until the engine loses all games.

[Martin_1969]

you draw conclusions from 300 games in your experiment and give a value of 6%? Which is simply wrong.

If you answer again you should respond to my primary question and explain to me how you come to a value of 6% after 300 games with an opening set of 50 lines in the thread "training mode (Eman) with trouney mode (Raptora)", which is impossible.

But now really bye and have a nice day

[deeds]

Oops !