It seems like adaptation in the context of a game of Go just making
the best response to the opponent's move, however unexpected. So, if
there were such a thing as a perfect Go player, it would have no need
to learn, but it would be perfectly adaptive, in this context.
Of course, one could also
Hideki Kato wrote:
Creativity here is, to generate a new method by combining methods
the system already has, in order to solve a problem.
That is creativity for the job of designing algorithms. Playing
go, creativity is finding moves _that work_ that nobody would have
thought of.
I think
I was wondering how he knows it as well. Then I decided that an
Oracle must have revealed it to him.
On 7/23/07, Jim O'Flaherty, Jr. [EMAIL PROTECTED] wrote:
How do you know this is incorrect? Are you claiming omniscience?
[EMAIL PROTECTED] wrote:
No. Erik is wrong even in theory. An
I agree. Thank you for much better explanation than what I can do in
English :-).
(Imagine creativity like a thermal energy in simulated Annealing.)
I prefer, however, non-linear dynamics in massive neural networks
with feedback than SA because it's my home of research.
Hideki.
Jacques
Thanks. Like the discussion. Sometimes, learning and creation from machine
intelligence point of view is not much difference. For example, when a
computer is building a mathematical model from data set, it would need to
construct a proper formula (creation), and at the same time, adjust
I have a Phd in statistics. But Bayesian methods were at that time a
non-topic. I know the general principles, but I want to learn a little bit
more about the latest developments in the field. Bayes is now chic, there
are many books about it. I assume also a lot of bad ones.
Can anyone
On 7/23/07, chrilly [EMAIL PROTECTED] wrote:
I have a Phd in statistics. But Bayesian methods were at that time a
non-topic. I know the general principles, but I want to learn a little bit
more about the latest developments in the field. Bayes is now chic, there
are many books about it. I assume
chrilly wrote:
I have a Phd in statistics. But Bayesian methods were at that time a
non-topic. I know the general principles, but I want to learn a little
bit more about the latest developments in the field. Bayes is now chic,
there are many books about it. I assume also a lot of bad ones.
Can
Thanks, I did also a search on Amazon and these two looked the most
interesting ones. I can order now with greater confidence.
Chrilly
You could try something like:
Information Theory, Inference Learning Algorithms
by David MacKay
or maybe
Data Analysis: A Bayesian Tutorial
by Devinderjit
Don't forget that David MacKay's book can be downloaded free from his
site so you can see exactly what you are getting before you buy it.
http://www.inference.phy.cam.ac.uk/mackay/itila/book.html
- George
On 7/23/07, chrilly [EMAIL PROTECTED] wrote:
Thanks, I did also a search on Amazon and
Absolutely the best book I've seen is:
Christopher M. Bishop
Pattern Recognition and Machine Learning
It's totally awesome!
Strong points:
- It have both Bayesian and non Bayesian ways explained
- the explanation is clear
- figures are so helpful (and aesthetic)
- it concentrates on prediction
I own that book and can also recommend it.
- George
On 7/23/07, Łukasz Lew [EMAIL PROTECTED] wrote:
Absolutely the best book I've seen is:
Christopher M. Bishop
Pattern Recognition and Machine Learning
It's totally awesome!
Strong points:
- It have both Bayesian and non Bayesian ways
I have the Neural Network Book from Bishop. It is also a good book. It puts
Neural Nets into the proper statistical framework.
Chrilly
- Original Message -
From: George Dahl
To: computer-go
Sent: Monday, July 23, 2007 6:37 PM
Subject: Re: [computer-go] Hint for good Bayes
Here is an old e-mail I've found about the pricing of the computer go
congress. I assume it's still correct.
Original Message
Subject:Re: Casual attendance of the US Go Congress
Date: Tue, 24 Apr 2007 17:21:18 -0400
From: Peter N. Nassar [EMAIL PROTECTED]
To:
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