Author: Martin Giepmans
Date: 06:37:55 12/29/01
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On December 29, 2001 at 05:11:26, Tom Kerrigan wrote: >Here's my idea. > >You have a position and you want your program to play a certain move (which it >presumably isn't playing). You run this algorithm: > >1. Search the position, get a PV. The evaluation of the last position of the PV >is eval(1). >2. Search only the move that you want your program to make, get a PV. This >end-point evaluation is eval(2). >3. Figure out which eval terms are different between eval(1) and eval(2). >Decrease the weights of all the different eval(1) terms slightly. Increase the >eval(2) terms slightly. >4. Repeat until the program plays the move you want. > >You could run this on lots of positions from GM games, to get your program to >play like a GM. (At least in some positions, heh.) > >Has this been done before? Are there any glaring problems with this idea? Does >anybody want to try this? If so, I'd like some credit for it. If not, I'll >probably get around to trying it sometime... > >-Tom I think one of the bigger problems with this idea is that the minimax-eval at the root does not only depend on the eval of the last position of the PV. It usually also depends on the eval of many other positions in the search-tree. The other problem is tactics. If the move that you want your program to make is best because it is a tactical win, then what? Nevertheless, the idea appeals to me. Maybe it will work with some "fine-tuning". Martin
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