do the math first...
.01 * real eval + .99 * random() where random is between 0 and 100 (one pawn value).
don't know what your "completely random" comment means, but I have tested (and just did it again) with pure random scores.
Just take Crafty, and right at the top of evaluate.c return 100 * random_generator() (assuming random_generator() returns a float 0.0 <= N < 1.00). Then you won't be guessing.
Actually I did do the math but it seems you don't comprehend. What was talked about
was complete randomness, but you suddenly decided to mix order into it, no matter
how insignificant you think it is!. The skill-1 mixes 1% of 'order' with 99% of
'chaos', which roughly translates into a maximum of 3-sigma (99.7% or so) result if we
are to say it is completley based on randomness. So when I say completely random,
I mean 0% order. I don't know why you thought otherwise..
There was recently news on the discovery of Higgs boson based on a 3 sigma result.
Despite doubts of the source of this news, this statement was by itself enough to convince
scientists it is not a _discovery_ as that is something attributed to a 5 sigma experimental
result. More about odds of discovery here
http://www.fnal.gov/pub/ferminews/fermi ... 16/p1.html
I did not guess anything. I and Tord just did this to our engines and got something light years away
from 1800 elo.
I have no "eval cache". There is a pawn score cache (pawn hash) but the random trick is applied to the score after that is used,
so this has absolutely no effect on anything. yes it causes TT issues. Again, "so what"? We want worse play, not an optimal search. Let it fail low and then high on the same move, it just wastes more time.
You have to attention to details . The same evaluation should be assigned to the same position
when visited twice..What is the sense of giving two different scores to the same position ?
Infact I have one more detail that I think needs to be addressed. Just using random() gives out positive values
(winning) for either side to move. They both get the same values which completely breaks the
_zero sum_ game notion. I am going to change this so that the score of white is negative of score of black
for a given position.
We are using uniform PRNGs. The larger the sample, the greater the probability of getting a large PRN. That is pretty simple to understand.
Duh. Like I said you roughly get some kind of extereme value distribution from taking maximum of
random numbers. This is a little bit skewed to the left compared to normal. But If it were normal,
we could use the 1/sqrt(n) rule to make the comparison. You would need to multiply the sample size by 4
to double the certainity of getting a larger number from the sample. So if you compare 15 and 20, you see
it doesn't differ much.. Maybe when mobility difference is like 15 and 60 you start talking of
something and that is maybe. You can also take the exact mobility score (howevery you calculate it) if you like.
I do not belive mobility only brings 1800 elo, all it does will be to properly place his queen to the highest 'mobile' square only
to be captured by the opponent... epic fail!
Care to rephrase that? Who is talking about "amplifying Elo" anywhere? Just a simple way to introduce mobility into the eval, which does lead to decent play. Not GM play, but also not 1200-level play either. I want to get the ELo down to 800 or less. Right now, with 23.2, the best one can get is down to 1800, which is much too high. With a purely random eval, at that
Are you saying approximate mobility eval is the only ingredient added by the search?
I just want to make sure.