On 6/11/07, J Storrs Hall, PhD [EMAIL PROTECTED] wrote:
I'll try to answer this and Mike Tintner's question at the same time. The
typical GOFAI engine over the past decades has had a layer structure
something like this:
Problem-specific assertions
Inference engine/database
Lisp
on top of the
On Thursday 14 June 2007 02:12:29 am Joshua Fox wrote:
I don't want to join any herd -- perhaps I just want to figure out why there
is no AGI herd yet; as much a sociological question as a scientific one.
It's probably worth pointing out to this group that for the first 25 years of
its
Josh,
Your point about layering makes perfect sense.
I just ordered your book, but, impatient as I am, could I ask a question
about this, though I've asked a similar question before: Why have not the
elite of intelligent and open-minded leading AI researchers not attempted a
multi-layered
I'll try to answer this and Mike Tintner's question at the same time. The
typical GOFAI engine over the past decades has had a layer structure
something like this:
Problem-specific assertions
Inference engine/database
Lisp
on top of the machine and OS. Now it turns out that this is plenty to
Interesting points, but I believe you can get around alot of the problems with
two additional factors,
a. using either large quantities of quality text, (ie novels, newspapers) or
similar texts like newspapers.
b. using a interactive built in 'checker' system, assisted learning where the
AI
On 6/11/07, James Ratcliff [EMAIL PROTECTED] wrote:
Interesting points, but I believe you can get around alot of the problems
with two additional factors,
a. using either large quantities of quality text, (ie novels, newspapers) or
similar texts like newspapers.
b. using a interactive built in
Correct, but I don't believe that systems (like Cyc) are doing this type of
Active learning now, and it would help to gather quality information and
fact-check it.
Cyc does have some interesting projects where it takes a proposed statment and
when a engineer is working with it, will go out
Josh,
Thanks for that answer on the layering of mind.
It's not that any existing level is wrong, but there aren't enough of
them, so
that the higher ones aren't being built on the right primitives in current
systems. Word-level concepts in the mind are much more elastic and plastic
than
On Monday 11 June 2007 02:06:35 pm Joshua Fox wrote:
...
Could I ask also that you take a stab at a psychological/sociological
question: Why have not the leading minds of AI (considering for this
purpose only the true creative thinkers with status in the community,
however small a fraction
--- James Ratcliff [EMAIL PROTECTED] wrote:
Interesting points, but I believe you can get around alot of the problems
with two additional factors,
a. using either large quantities of quality text, (ie novels, newspapers) or
similar texts like newspapers.
b. using a interactive built in
Josh: If you want to understand why existing approaches to AI haven't
worked, try
Beyond AI by yours truly
Any major point or points worth raising here?
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Josh: If you want to understand why existing approaches to AI haven't
worked, try Beyond AI by yours truly
Any major point or points worth raising here?
Yo, troll,
If you're really interested, then go get the book and stop wasting
bandwidth.
If you had any clue about AGI, you'd
Here's a big one: Levels of abstraction.
I assume many of you are using a GUI mail client to read this. You're
interacting with it in terms of windows, panels, boxes, buttons, menus,
dragging and dropping.
The GUI was written in terms of a toolkit that implements those concepts on
top of an
Josh:
Most AI (including a lot of what gets talked about here) is the equivalent
of
trying to implement the mail-reader directly in machine code (or
transistors,
for connectionists). Why people can't get the notion that the brain is
going
to be at least as ontologically deep as a desktop GUI
The problem of logical reasoning in natural language is a pattern recognition
problem (like natural language recognition in general). For example:
- Frogs are green. Kermit is a frog. Therefore Kermit is green.
- Cities have tall buildings. New York is a city. Therefore New York has
Mark Waser wrote:
The problem of logical reasoning in natural language is a pattern
recognition
problem (like natural language recognition in general). For example:
- Frogs are green. Kermit is a frog. Therefore Kermit is green.
- Cities have tall buildings. New York is a city.
I've ended up with the following list. What do you think?
* Ming Li and Paul Vitanyi, An Introduction to Kolmogorov Complexity
and Its Applications, Springer Verlag 1997
* Marcus Hutter, Universal Artificial Intelligence: Sequential
Decisions Based On Algorithmic Probability, Springer Verlag
--- Charles D Hixson [EMAIL PROTECTED] wrote:
Mark Waser wrote:
The problem of logical reasoning in natural language is a pattern
recognition
problem (like natural language recognition in general). For example:
- Frogs are green. Kermit is a frog. Therefore Kermit is green.
On 6/9/07, Lukasz Stafiniak [EMAIL PROTECTED] wrote:
I've ended up with the following list. What do you think?
I would like to add Locus Solum by Girard to this list, and then is
seems to collapse into a black hole... Don't care?
* Ming Li and Paul Vitanyi, An Introduction to Kolmogorov
On 6/9/07, YKY (Yan King Yin) [EMAIL PROTECTED] wrote:
I'm not aware of any book on pattern recognition with a view on AGI, except
The Pattern Recognition Basis of Artificial Intelligence by Don Tveter
(1998):
http://www.dontveter.com/basisofai/basisofai.html
You may look at The Cambridge
On 6/7/07, Lukasz Stafiniak [EMAIL PROTECTED] wrote:
Reasoning about Uncertainty (Paperback)
by Joseph Y. Halpern
BTW, the .chm version of this book can be easily obtained on the net, as are
many others you listed...
I also recommand J Pearl's 2 books (Probabilistic Reasoning and Causality).
--- YKY (Yan King Yin) [EMAIL PROTECTED] wrote:
On 6/7/07, Lukasz Stafiniak [EMAIL PROTECTED] wrote:
Pattern Recognition, Third Edition (Hardcover)
by Sergios Theodoridis (Author), Konstantinos Koutroumbas (Author)
I have this one too, but the question is, how to apply pattern recognition
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