Author: Peter Fendrich
Date: 11:42:38 05/02/99
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On May 02, 1999 at 12:19:18, Dave Gomboc wrote: >>There are (at least) two ways to use the term Knowledge-based: >> 1) Strictly as in the AI field. I know of no program worth mentioning >> that uses knowledge engineering, knowledge bases or something like >> that. I don't even think it would be a good idea... > >Well, as a graduate student in the AI field, I hope that Christophe and you will >permit me my insistance that _this_ is the way that attaches real semantic >meaning to the term, and other uses debase the term's value. Don't get me wrong here Dave! I said exactly this in some other "Knowledge"-thread 3-4 weeks ago. I worked for 8 years in Volvo Data's AI group and during the 8'th year I was the manager of the AI department. Then we also should be able to agree on that none of the active chess-programs today are knowledge-based in this sense. >> 2) In a more general way, meaning that the program is build up by more or less >> *pure* chess knowledge. >> There are no *pure* chess knowledge in the program. Everything in the >> program has to be tuned, including the chess knowledge. It is not possible >> to include some evaluation term without thinking about how it cooperates >> with the search. For the same reason it is not possible to make good >> changes in the search heuristics without thinking about how it affects >> the evaluation code. The different parts of the program has to work together >> as a whole. The best program as a whole has the best chess knowledge. >> Of course we have something called luck but that's another story... :) > >The best program as a whole might not have the best chess knowkedge, it might >simply execute compute things more quicky. The computer is not self-aware that >it is computing something more quickly than it would had it chosen an >alternative way, so I reject that e.g. code optimization implies more knowledge, >even though performance may be improved. Now we are arguing about what chess-knowledge is. It's hard to define and hard to capture. Chess-knowledge in a program using search is not the same as chess-knowledge in peoples mind. There are many ways to optimize the code. One example is to change some evaluation term and make it simpler so search goes faster. If this change makes the program a better chess player, where is the chess knowledge now? Before the change, the programs evaluation term was maybe better expressed and that made it easy to find this specific chunk of knowledge. After the change the same knowledge is handled by a combination of the faster search, the simpler code and the other evaluation terms that are working together. The knowledge is there but hard to find. //Peter
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