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Subject: Re: How I Learned to Stop Hating 141

Author: Stuart Cracraft

Date: 14:35:43 09/04/04

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On September 03, 2004 at 18:14:56, Uri Blass wrote:

>On September 03, 2004 at 17:30:18, Stuart Cracraft wrote:
>
>>On September 03, 2004 at 16:52:34, Andrei Fortuna wrote:
>>
>>>On September 03, 2004 at 15:41:42, Stuart Cracraft wrote:
>>>
>>>>On September 03, 2004 at 05:08:01, Andrei Fortuna wrote:
>>>>
>>>>>This makes me think how funny would be if two engines play, engine A would have
>>>>>all kinds of those extensions in case of check etc, engine B would have
>>>>>implemented a good eval function (with many terms regarding positional play) and
>>>>>in the match engine B leads engine A towards the positions where engine A
>>>>>discovers those mate attacks and so forth ahead of engine B, but he is on the
>>>>>losing side due to B's positional play.
>>>>
>>>>I think this kind of self-play event and auto-tuning and genetic algorithms
>>>>in general are under-estimated by the computer chess programmers. Just
>>>>because good results haven't been generated and there is no easy "elixer"
>>>>doesn't mean we shouldn't be trying it.
>>>>
>>>>Think of the time-savings. Heck, your auto-tune doesn't have to produce
>>>>Bob Hyatt hand-crafted Crafty evaluation coefficients for terms you have
>>>>to find and prove first -- but even if you don't produce something other
>>>>than what you are doing now but saving a lot of time, then you have profited
>>>>more.
>>>
>>>
>>>Hi Stuart,
>>>
>>>Wasn't talking about auto-tuning, just was thinking that if someone invests in
>>>evaluation function versus someone who invests in various extensions - the
>>>former wins the game. Of course in reality programmers usually take care of both
>>>areas ...
>>>
>>>Andrei
>>
>>Yes -- I understand you weren't -- but there is a big savings if you do
>>it right.
>>
>>For me, it is worth investigating as I don't want to spend the rest of
>>my life tuning evaluation functions.
>
>I believe that I can earn more from adding new knowledge relative to tuning.
>
>Tuning can be done not automatically based on watching problems that repeat in
>games.
>
>Uri

If a problem repeats in games and the program loses, then tuning will
try various things to prevent it.

Look at Slate's "mouse" program and its learning capability. Highly
effective yet simple. No need to even adjust coefficients. Just store
a hash and a move in an avoid file.

Imagine what tuning could do.

I believe both Schaeffer and Marsland have very high expectations for
the future of tuning via various methods.

Stuart






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