Author: Dieter Buerssner
Date: 17:52:26 07/11/04
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On July 11, 2004 at 20:36:52, Stuart Cracraft wrote: >You'd probably simply do much better to implement square of the pawn >with a couple hundred point strength gain. It would clarify a huge >number of the nodes with Fine #70. If enemy king is outside of >the square of your passed pawn and does not have the move, etc. Stuart, this sounds interesting, but perhaps testing just the other way around will be better (for debugging). Fine 70 can be solved with material only eval. After 26 plies, you can see, that you can force the winning of a pawn. So, I'd suggest, to debug this problem, disable all your eval, just return material score. Also, one might want to disable repetition detection (repetition does not mix well with transposition tables, and to make the debugging problem as easy as possible, disabling repetion detection might help). About the nuclear simulations of the other post. You might have misunderstood my point slightly. There are very good pseudo random number generators available in source code. Some have no failed any tests for randomness. That particilar lagged fibonacci PRNG did fail some simple tests. Simulating some easy statistics with a small and simple (but sufficient) program using that PRNG (a typical "Monte Carlo simulation" can give totally wrong results. While the same program will work perfectly with another PRNG. If in doubt, an one wants to do some simulation, using Mersenne Twister will probably be a good choice. If one wants to be really careful, combine Mersenne Twister with one or two other well known 32-bit PRNGs, for example KISS of Marsaglia, and some combined linear congruential generator. myrand32var = mersennetwister()^kissprng()^sophisticated_lcg(); If you find any problem where such a PRNG fails (even when uncombined Mersenne twister alone fails) in a correctly implemented simulation, your fame in the area of PRNGs will be guaranteed :-) Of coruse, this is very off topic here. Regards, Dieter
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