Author: Dieter Buerssner
Date: 09:29:35 09/28/00
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On September 28, 2000 at 12:02:42, Vincent Diepeveen wrote: >On September 28, 2000 at 11:41:50, Dieter Buerssner wrote: > >>On September 28, 2000 at 05:00:59, Bas Hamstra wrote: >> >>>On September 27, 2000 at 16:16:21, Peter McKenzie wrote: >>> >>>>On September 27, 2000 at 07:47:18, Bas Hamstra wrote: >>>> >>>>>Supposing no "lazy-errors" at all were made, does anyone know if there are >>>>>serious side-effects to lazy eval? >>>> >>>>You can't get the full benefits of fail-soft using lazy eval. >>> >>>I agree. This is the only factor I can think off too, you lose some bound info. >>> >>>Yet, I ran a couple of WAC tests at very short time controls, with and without >>>LE. And kept track of the average depth that was reached. In that quick test >>>NPS went up, but the average depth stayed the same! >>> >>>So it seems what you win in speed, you lose in bound info, net result zero? At >>>least in this case. I will rerun it more accurately, at longer tc. >> >>You might want to give the following idea a try. I think this could be called a >>fail soft version of lazy eval: > >I heart someone mention this trick before a couple of years ago, >but when i measured the largest eval score i had so far during the >search the trick looked a bit silly > >> es = s + largest_evalscore[side]; > >So that's roughly (can be a bit more or less): Sorry, I was too sloppy. s is the material score and largest_evalscore is the largest positional score found so far. With this, would you still think, this gives worse bounds? -- Dieter
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