This is nothing to do with what I'm talking about (which is optimising the nn for "perfect" play), but it's an interesting idea to contemplate.
It could be successful, if the bot can account for the opponent's error rate. Typically, it could take worse positions if believed the opponent would misplay them. However, you need to consider what happens if the opponent is actually superior. The bot would think the player was making errors, and adjust accordingly, but it would be adjusting in the wrong direction. Take my previous example: the bot would take a position it would drop if it assumed perfect play, and by taking is in an even worse position because it is being outplayed. It's possible that this could be overcome by factoring in some luck analysis and variance reduction to realise that it is being outplayed because the opponent is too unfeasibly "lucky", but I've not really thought about this angle. n Ian From: Thomas A. Moulton [mailto:t...@moulton.us] Sent: 16 December 2011 12:00 To: Ian Shaw Cc: Øystein Schønning-Johansen; Mark Higgins; Frank Berger; bug-gnubg@gnu.org Subject: Re: [Bug-gnubg] Neural network symmetry question If gnubg could estimate the opponents rating based upon error rate then it could be more aggressive on a redouble since the other player is likely to make errors to modify the cube decision. This may have NOTHING to do with what your're talking about right now... :) Tom On 12/16/2011 06:43 AM, Ian Shaw wrote: Øystein Schønning-Johansen wrote: Sent: 12 December 2011 20:59 So, we don't care about the exactness of the absolute evaluation, we care about the relative evaluation between the moves (or resulting positions after each move). That is what makes it select good moves! This strategy was originally adopted by Tesauro. I agree that it is fine for chequerplay, where you only have to find the best play relative to the alternatives. However, for cube decisions it is important to know the absolute equity. It is known that gnubg is inaccurate in some areas, most notably holding-game cube action, where gnubg overestimates the holding player's chances. I wonder if this is due to only training for relative move selection. It might be worth devising a training regime that trains for absolute equity. This ought to give good chequerplay, too, since if the nn can accurately determine the absolute value of each position it will inevitably rank candidates correctly, too. Ian _______________________________________________ Bug-gnubg mailing list Bug-gnubg@gnu.org<mailto:Bug-gnubg@gnu.org> https://lists.gnu.org/mailman/listinfo/bug-gnubg
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