Author: Rafael Andrist
Date: 02:21:21 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 You may be interested in the temporal difference learning algo by Richard Sutton which is implemented in the program KnighCap by Andrew Tridgell and Jonathan Baxter. http://www.syseng.anu.edu.au/lsg/knightcap.html regards Rafael B. Andrist
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