RE: computer-go: Perl Module for next move.

["Staelin, Carl" <staelin@xxxxxxxxxxxxxxx>]

The original work on using temporal difference
learning for game players was by Gerald Tesauro
to train a backgammon player.  A copy of the 
paper can be found at:
	
	http://www.research.ibm.com/massive/tdl.html

Others thought it might be a nice technique to
apply to other games, such as checkers or GO.
Chellapilla and Fogel trained checkers players
using techniques similar to those used by 
Tesauro for his backgammon player.

	http://vision.ucsd.edu/~kchellap/papers
(Look for Chellapilla and Fogel, "Co-evolving
checkers playing programs using only win, lose
or draw", from SPIE 1999.

There has also been some work done on applying
similar techniques to GO players, such as Nici
Schraudolphs work on applying temporal difference
learning neural networks to GO:

	http://www.idsia.ch/~nic/pubs.html#gochap

Cheers,

Carl
_________________________________________________
[(hp)]	Carl Staelin
	Senior Research Scientist
	Hewlett-Packard Laboratories
	Technion City
	Haifa, 32000
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> -----Original Message-----
> From: Matthew Corey Brown [mailto:bromoc@xxxxxxxxxxxxxxxxx]
> Sent: Wednesday, June 06, 2001 12:51 AM
> To: computer-go@xxxxxxxxxxxxxxxxx
> Subject: RE: computer-go: Perl Module for next move.
> 
> 
> On Tue, 5 Jun 2001, Mark Boon wrote:
> 
> > In a previous post a checkers project was said to use neural nets
> > successfully, but I'm wondering how much was done by a fast 
> mini-max program
> > which used the neural net in some way (as a move-selector 
> for example)
> > instead of having the net learn the mini-max strategy as 
> well. I somehow
> > feel the latter is necessary for neural networks to be 
> successful in Go.
> > 
> 
> What i was told all it did was say which move you made result 
> in a better
> position.. it never looked ahead.. just what was best in the here and
> now and which move would it be to improve your position. I 
> learned it from
> a SIG in AI that the local game dev community has started up. 
> I'm going to
> a different SIG meeting tonight but the person who told me 
> about it will
> be there and I'll try and get more reference. But the neural 
> net was the
> only descion maker of the checkers game to my understanding. The idea
> intrigued me when i heard it last week. 
> 
> 
> Matthew Corey Brown                             
> bromoc@xxxxxxxxxxxxxxxxx 
>   "Death can not stop true love. All it can do is delay it 
> for awhile."
>