Author: Dave Gomboc
Date: 15:29:11 04/15/99
Go up one level in this thread
On April 15, 1999 at 12:35:57, Milton Zucker wrote: > >On April 15, 1999 at 09:45:53, Bruce Moreland wrote: > >> >>On April 15, 1999 at 09:34:12, Christophe Theron wrote: >> >>>On April 15, 1999 at 09:27:03, Bruce Moreland wrote: >> >>>>What is "knowledge based" ? >>>> >>>>bruce >>> >>>Good remark, Bruce. Here is another one that has no idea of what he is talking >>>about. >> >>It's an interesting term and I'd like to explore its meaning. I am not trying >>to blast anyone. >> >>The programs that have this term applied to them are either extremely weak >>ancient research programs, or very strong commercial programs that nobody knows >>anything about. >> >>bruce > >I will propose a naive definition of a "knowledge-based" chess program, which I >invite others to knock down. If two programs A and B have the same rating, the >slower program that searches less ply per unit of time is the more "knowledge >based" in the sense that it plays at the same strength as the faster program >without seeing the longer term tactical consequences of its move. Presumably its >decisions are based on more positional knowledge and less on tactical >consequences. >...Milton... Alright, here's the truck to knock it down with. :) The proposal measures the amount of knowledge in software by search depth. This has some intuitive appeal, the logic behind it being that programs that "know more" will take longer at each node, so they will search less deep. Unfortunately, there are several difficulties with the proposal: 1) Search depth is not uniform throughout a search tree. 2) Programs search differently-shaped trees, so their search depths are not (usefully) directly comparable. 3) What is considered "knowledge" is left unclear. Does this include measures such as futility pruning -- the understanding that one's position is so good that there is no need to finish expanding the last couple of ply here? This "knowledge" increases the speed of your search. 4) The purpose of chess-specific terms in the evaluation is to guide the search. This has no more claim to knowledge than non-chess-specific features that guide the search. A hash table has nothing to do with chess, but it does more to guide the iteratively deepening search than any chess-specific term. 5) Software that searches less ply per time unit may be doing so because they are extending certain continuations further. So, they might well understand the long-term tactical consequences of a move even though their reported depth is shallow relative to some other chess software. 6) What constitutes a "node" for reporting purposes varies from program to program. Therefore, node count is not an acceptable substitute for search depth as a measurement of knowledge. I could go on, but the point has (I hope) been made. No doubt, a correlation between search depth and search effort exists, but this relationship is individual to within a program, and should not be misleadingly generalized. With regards to the state of the art in computer chess today, "Knowledge-based" is a marketing buzzword, nothing more. IMO, M-Chess, Hiarcs, Rebel, CSTal2, and any other mainstream commercial chess product have about as much claim to "knowledge-based" as a hole in the ground. Dave
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