Author: Andrew Williams
Date: 02:28:00 08/07/00
Go up one level in this thread
On August 06, 2000 at 20:15:46, Vincent Diepeveen wrote: >On August 06, 2000 at 16:48:16, Andrew Williams wrote: > >>On August 06, 2000 at 16:36:15, Vincent Diepeveen wrote: >> >>>Show me an MTD program that uses less nodes a ply as DIEP does. >>> >> >>I've no idea if Diep uses fewer nodes than others. However, even >>if it does, would you say this is due purely to the superiority >>of PVS over MTD? Surely your evaluation is different to other >>programs too? >> >>The point I want to make is that it's not helpful to Larry (or anyone >>anyone else) if you just say "MTD(f) sux! PVS rox!" UNLESS you provide >>some rationale for your opinion. > >DIEP uses hell of a lot nodes more if i use MTD. > It's not clear from this if you're saying you've tried it and you've got the figures, or if you are speculating that DIEP would be worse with MTD? Andrew >A pawn in DIEP is 1000 points worth. > >So correct me if i'm wrong: > >If this iteration i'm at +0.300 next iteration i'm at +0.600 with PVS, >then how many researches do i need with MTD? > >>Andrew >> >>PS Your "there are no commercial programs using MTD" argument doesn't >>really represent a rationale, in my opinion. >> >> >>>What diep is doing is very simple in search: >>> >>> PVS (starting with -infinite) >>> check extensions >>> checks in qsearch >>> nullmove R=3 >>> no other crap. no pruning. Perhaps at WMCC i prune a bit, >>> but that's because against computers playing is different. >>> >>> Yet i'm missing programs using less nodes a ply with MTD. >>> I"m missing *any* deep searching program that uses MTD actually. >>> >>>On August 06, 2000 at 10:31:58, An >>> >>> >>> >>>drew Williams wrote: >>> >>>>On August 06, 2000 at 09:38:18, Vincent Diepeveen wrote: >>>> >>>>>On August 05, 2000 at 11:37:01, Larry Griffiths wrote: >>>>> >>>>>>Which Algorithm is considered the best now-adays. >>>>> >>>>>Depends upon what kind of program you make. >>>>> >>>>>If you have an evaluation function that has patterns which all deliver >>>>>very small penalties and bonusses, from which the summation also adds up >>>>>to a near to material only evaluation, then MTD is an interesting >>>>>alternative. >>>> >>>>PostModernist uses MTD. It would be incorrect to describe its evaluation >>>>as being "near to material-only". This opinion (on MTD) is one that Vincent >>>>has expounded before, without much in the way of supporting evidence. >>>> >>>>> >>>>>If the evaluation function is either big, using a pawn as being >>>>>worth 1000 points instead of 1 point, the eval is huge, or having high scores >>>>>for for example king safety and or passers, >>>>>then you have only 1 option that outperforms >>>>>*anything*, and that's nullwindow search also called principal variation >>>>>search which is pretty easy to implement. >>>>> >>>>>Usually at the start of your program MTD looks interesting, if your >>>>>program gets better (more knowledge in eval, less bugs in search and >>>>>better move ordering), then PVS usually outperforms anything. >>>>> >>>> >>>>I don't think there is any evidence anywhere that supports Vincent's opinion >>>>about MTD. Just stating an opinion does not make it true :-) >>>> >>>>>My advice is to start with PVS and not look to the rest. >>>>> >>>>>>NegaScout? MTD? PVS? Others? I am looking to implement one of the best search >>>>>>type algorithms in my program. I would like to get it into the 2000 rated range >>>>>>as this has been my lifetime goal. Then, maybe install winboard or something so >>>>>>it can compete against other programs to get a rating. >>>>>>I dont like MTD as it seems to be complex. >>>>>> >>>>>>Larry. >>>> >>>>My advice would be to get a straight alpha-beta search working, starting >>>>with bounds of -inf..+inf. This won't be terribly competitive, but you >>>>can use it as a stable reference when you move on to more sophisticated >>>>approaches. When you're happy with your alpha-beta search, try implementing >>>>an aspiration-search, which is like alpha-beta except that you start with >>>>bounds of score-50 .. score+50, where score is the value returned from the >>>>previous iteration. You will need to provide some way of handling the case >>>>where the returned score from *this* search falls outside this "window". >>>>Once you've got your aspiration search working properly, you'll be in a >>>>strong position to decide where you want to go with your program. >>>> >>>>Above all, have fun with your program! >>>> >>>>Andrew Williams
This page took 0 seconds to execute
Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.