Author: Gordon Rattray
Date: 07:30:00 04/17/01
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Great article! (thanks for posting it) As a CT/GT 2.0 user I've been extremely impressed with the program. Getting some insight into its actual workings is very interesting indeed. Thanks to Christope Theron for all his great work. There were some aspects that I didn't fully understand... [snip] >Question: Does Tiger use the null move search algorithm? > >CT: Null move is not the major selective search algorithm of Tiger. There are >several selective algorithm working together. Think of them as “filters”. Each >is able to filter (prune away) some moves, and putting a filter after a filter >after a filter... gives in the end a very selective filter. Does this imply that there are some positions that will never be solved given a theoretically infinite amount of time? i.e. if something is wrongly filtered/pruned then no amount of extra time will allow the program to see it? [snip] >Question: Christophe, do you believe that programs can be tuned so to play best >on tournament levels. Which means that if they play for example 40 minute games >they will play worse against an opponent than if they play 120 minutes games? > >CT: No I don't think so. If a program does better at game in 120 than at games >in 40, then in my opinion it is simply poorly designed. OK, here's this is my main misunderstanding. Incidentally, I'm pretty sure this has been discussed before and disagreements probably still exist. So, I'll just try to state why I'm still puzzled and try not to start another discussion. I view chess programs as complex algorithms, and hence they have complexity graphs of data size versus time. So, for example, like "bubble sort" compared with "quick sort" we can visualise graphs of how quickly the time required goes up as we process more data. For chess programs, I'd guess depth of search determines the data size primarily. Now, this leads me to believe that it is possible to have two chess programs A and B where: A is better for time less than, say, 30 minutes, but B is better at times greater than 30 minutes. I can't see how it is possible to say that either is definitely poorly designed? Although I don't have any figures, I think that GT 2.0 requires a certain amount of time to stabilise its search and I'm convinced that some opponents will do better against GT at shorter time controls. [snip] >Question: What about five minute games. If I play Tiger against a program x in >blitz and get a 60% score for Tiger, would you be willing to bet that in >tournament games there would be approximately the same result? > >CT: I think that if Tiger makes 60% against program X in blitz it will make 55% >(or so) against the same program at tournament time controls. It is not because >Tiger is weaker at long time controls, it is because strength differences >decrease with longer time controls. This phenomenon is not a property of Tiger, >it happens with all top chess engines. Eventually, if you use even longer time >controls I guess the winning percentage will come closer to 50%, but you will >never see program X winning. This continues my misunderstaning. If I design a chess program somewhat "brute force" and simplimatic, it may be relatively ok for shallow searches during blitz games. But this design will never scale up and I'd expect programs like GT to defeat it by an even bigger margin at longer time controls. Once again, my "complexity graph" thinking shows the divergence to increase with each extra ply. If you made the assumption that program X above is *well designed* (unlike my example), then I still think that GT may still scale up better. [snip] >CT: Yes. CT14 and GT2 would play the endgame identically. Do you have any exact definitions of "endgame". For example, if I showed you a test position could you easily tell if CT and GT will handle it the same? I'm just curious as I sometimes give both programs the same position to analyse. I'd guess it is an involved expression. Gordon
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