Phil wrote:
YKY is advocating the post-modern viewpoint that knowledge is context-dependent, and true-false assignments and numeric value judgements are both extremely problematic.Pei is pointing out the
commonsense, classicist position, and also the refutation of the post-modern tradition,
On 8/19/06, Ben Goertzel [EMAIL PROTECTED] wrote:
The problem of context may be avoided by using an unambiguous language (for internal representation).Context-dependent words are a feature of natural language (NL) only.It arises when an NL word maps to multiple concepts in
the knowledge
On 8/19/06, Ben Goertzel [EMAIL PROTECTED] wrote: Well, but I can generate a hypothetical grounding for mushrooom pie on the fly even though I haven't seen one ;-)
And I can form concepts of mathematical structures that I have never experienced nor exemplified and may in fact be inconsistent
On 8/19/06, Ben Goertzel [EMAIL PROTECTED] wrote: In blackboard the NL word maps to either a board that is black in color
or a board for writing that is usually black/green/white.The KR of those concepts are unambiguous; it's just that there are 2 alternatives. This is very naive...a
Isupport opensource AGIwith the following reasons:
1. It would be nearly impossible to enforcethe single-AGI scenario; I think the best strategy is to start aproject and tryour best in it.
2. One possibilityis to make the AGI software commercial, but at a very low cost, and with differential
I have worked out a more detailed AGI architecture:
http://www.geocities.com/genericai/GI-Architecture.htm
But I'm still working on the webpages to explain the modules.
It seems very suitable for theMAGIC message-passing model.
I think it's the simplest architecture for general intelligence.
On 9/5/06, M. Riad [EMAIL PROTECTED] wrote: Sorry to barge into the conversation in this way, but YKY mentioned something I needed clarification with.
You said: Withlogic I can write down a rule for recognizing this pretty easily, mainly due to the use of symbolic variables. So you see the
I forgot to add that, unsupervised learning is also needed, and desirable,inthe G0 architecture. How to conduct unsupervised learning under logic would be an interesting research topic.
YKY
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On 9/6/06, Fredrik Heintz [EMAIL PROTECTED] wrote: And inductive approaches have problems with overfitting and thereby
lack of generality. They can find a pattern that very closely match your examples, but if you give it a radically new example it will utherly fail to generalize. Therefore the
On 9/6/06, M Riad [EMAIL PROTECTED] wrote: Interesting. ILP is new for me. I did some basic reading and it's really a different form of supervised learning. But I still don't see how this can help build general knowledge. Using your bottle example, lets assume your ILP system recognizes bottles
On 9/7/06, Fredrik Heintz [EMAIL PROTECTED] wrote:
I haven't studied G0 in detail, but one of our current research problems is the execution and monitoring of plans. We have one of the worlds fastest and most expressive planners, TALplanner, which is
forward-chaining domain-dependent planner
My guess at a good basis for KR is simply the cleanest, most powerful, and most general programming language I can come up with. That's because to learn
new concepts and really understand them, the AI will have to do the equivalent of writing recognizers, simulators, experiment
David Clark wrote:
I agree that an AGI fundamentally will be created by a combination of data (databases) and procedures (programs) but how large and by who the programs will be created has yet to be determined. Why do you assume that all AGI programs will be created by humans? Why couldn't an
Matt:
(Sorry about the delay... I was busy advertising in other groups..)
But now that you have completed your theory on how to build AGI, what do you do next?Which parts will you write yourself and which parts will you contract out?
Ideally, any part that can be out-sourced should be
Hi Ben and others
The way I see it,we are close to buildinga complete AGI, but there are gaps to be filled in the details. In my opinion one thing that Ben can do betterto becomea leader in AGI RD is to delegatetaskstoother people / groups, ie adopt a division-of-labor strategy.
I think the
On 10/15/06, Ben Goertzel [EMAIL PROTECTED] wrote: [...]
The main problem is not the commercial one (that once you've finished your AGI, if it's privately held, you can more easily use it to make money). While I like money as much as the next guy, $$ is not the reason to make an AGI. There are
Re the Mind Ontology page: I have written a glossary of terms pertinent to our discussions, including Ben's suggestion of the terms:
-- perception
-- emergence
-- symbol grounding
-- logic
and I also added many of the terms in my architecture (which is not meant to be final, only as aproposal
Hi Peter,
I think in all of the categories you listed, thereshould be a lot ofprogress, but they will hit a ceiling because of the lack of an AGI architecture.
It is very clear that vision requires AGI to be complete. So does NLP. In vision, many objects require reasoning to recognize.NLP also
On 10/21/06, Philip Goetz [EMAIL PROTECTED] wrote: Commercially, I'm not sure if OS or CS is better.Remember Steve Job's
APPLE lost the PC market to IBM because IBM provided a more open architecture (in addition to the fact that IBM was more resourceful).We need to be careful not to lose
I have now addedterm logic enhancements to the G0 knowledge representation.
The new NL module can process NL in a way that mimics how babies learn language:
http://www.geocities.com/genericai/GI-NLP.htm
so it may be a genuine solution to the NL problem.
The new KR can also solve the doing
On 10/23/06, Matt Mahoney [EMAIL PROTECTED] wrote: [...]
One aspect of NARS and many other structured or semi-structured knowledge representations that concerns me is the direct representation of concepts such as is-a, equivalence, logic (if-then, and, or, not), quantifiers (all, some), time
On 11/7/06, John Scanlon [EMAIL PROTECTED] wrote:
James Ratcliff wrote: In some form or another we are going to HAVE to have a natural language interface, either a translation program that can convert our english to the machine understandable form, or a simplified form of english that is
Hi John,
This is the specification of my logic:
http://www.geocities.com/genericai/GI-Geniform.htm
I conjecture thatNL sentences can be easilytranslated to/fromthis form.
The definition of Jinnteera looks interesting, do you have a demo of how it works? =)
I'm now working on a
On 11/7/06, James Ratcliff [EMAIL PROTECTED] wrote: Yan, Do you have a version of the book layout that is all on one page, or PDF or anything?
I would like ot print the whole thing off and look over it in more detail. Also lots of broken links, run a link checker, the GO link on the front
This is an interesting thread, I'll add some comments:
1. For KR purposes, I think first order predicate logic is a good choice. Geniform 2.0 can be expressed in FOL entirely. ANN is simply not in a state advanced enough to represent complex knowledge (eg things that are close to NL). I
On 11/10/06, Ben Goertzel [EMAIL PROTECTED] wrote: 2.Ben raised the issue of learning.I think we should divide learning into 3 parts:
(1) linguistic eg grammar (2) semantic /concepts (3) generic / factual. This leaves out a lot, for instance procedure learning and metalearning... and also
On 11/10/06, Ben Goertzel [EMAIL PROTECTED] wrote: The word agent is famously polysemous in computer science.In my prior post, I used it in the sense of software agent not autonomous
mental agent.These Novamente MindAgents are just software objects with certain functionalities, that get
On 11/11/06, Michael Wilson [EMAIL PROTECTED] wrote: Ben Goertzel wrote: It is indeed complex, but I have not found anything simpler than
I think will work... The key problem with complex designs can probably be summed up with 'anyone can design a system so complex that they cannot
I don't think anyone here is not focusing on how to /succeed/ =) And I don't like trial and error either, I prefer to plan everything ahead instead of tinkering. But I'mquestioning whether emergence is really needed for AGI.
^^^ I meant emergence at the neural / subsymbolic level.
YKY
This
On 11/12/06, John Scanlon [EMAIL PROTECTED] wrote:
I get the impression that a lot of people interested in AIstill believe that the mental manipulation of symbols is equivalent to thought. As many other people understand now, symbol-manipulation is not thought. Instead, symbols can be
On 11/12/06, John Scanlon [EMAIL PROTECTED] wrote:The majormissing piece in the AI puzzlegoes between the bottom level of automatic learning systems like neural nets, genetic algorithms, and the like, and top-level symbol manipulation. This middle layer is the biggest, most important piece,
On 11/12/06, Michael Wilson [EMAIL PROTECTED] wrote: 'Understanding exactly how the system will succeed' is a lot harder
than (a) it sounds and (b) merely convincing yourself (or even a few of your peers) that the system will succeed. Of course it's pretty much impossible to plan everything out
On 11/16/06, James Ratcliff [EMAIL PROTECTED] wrote:
Correct,
Using inferences only works in toy, or small well understood domains, as
inevitably when it goes 2+ steps away from direct knowledge it will be
making large assumptions and be wrong.
My thoughts have been on an AISim as well, but
On 11/17/06, Matt Mahoney [EMAIL PROTECTED] wrote:
Learning logic is similar to learning grammar. A statistical model can
classify words into syntactic categories by context, e.g. the X is tells
you that X is a noun, and that it can be used in novel contexts where other
nouns have been
James: you said you're building a wiki-style AGI, and I've heard another guy
with a similar idea. I want to know if you intend it to have free
contributions or is there a way to pay the contributors?
It sounds like a good idea, I'm interested to help, but if it's free I'd
have to worry about
I'm not saying that the n-space approach wouldn't work, but I have used that
approach before and faced a problem. It was because of that problem that I
switched to a logic-based approach. Maybe you can solve it.
To illustrate it with an example, let's say the AGI can recognize apples,
bananas,
On 11/28/06, Mike Dougherty [EMAIL PROTECTED] wrote:
perhaps my view of a hypersurface is wrong, but wouldn't a subset of the
dimensions associated with an object be the physical dimensions? (ok,
virtual physical dimensions)
Is On determined by a point of contact between two objects? (A is
I'm considering this idea: build a repository of facts/rules in FOL (or
Prolog) format, similar to Cyc's. For example water is wet, oil is
slippery, etc. The repository is structureless, in the sense that it is
just a collection of simple statements. It can serve as raw material for
other
On 1/14/07, Pei Wang [EMAIL PROTECTED] wrote:
How do you plan to represent water is wet?
Pei
Well, we need to agree on some conventions. A pretty standard way is:
Is(water,wet).
But the one I use in my system is:
R(is, water, wet)
where R is a generic predicate representing a
On 1/14/07, Pei Wang [EMAIL PROTECTED] wrote:
Well, we need to agree on some conventions. A pretty standard way is:
Is(water,wet).
In the standard way of knowledge representation, a constant is
either a predicate name or an individual name. Mass noun like water
is neither. There is no
On 1/14/07, Bob Mottram [EMAIL PROTECTED] wrote:
If Mindpixel does get revived I think it should be an open source project,
with the results available to everyone. The idea of doing this on a
commercial basis with the issuing of shares turned out not to be viable.
This kind of effort is a
On 1/14/07, Chuck Esterbrook [EMAIL PROTECTED] wrote:
* Would it support separate domains/modules?
I didn't realize the importance of this point at first. Indeed, what we
regard as common sense may be highly subjective as it involves matters such
as human values, ideology or religion. So the
On 1/14/07, Benjamin Goertzel [EMAIL PROTECTED] wrote:
The choice of knowledge representation language makes a huge difference.
IMO, Cyc committed themselves to an overcomplicated representation
language that has rendered their DB far less useful than it would be
otherwise
If you want to
On 1/18/07, Charles D Hixson [EMAIL PROTECTED] wrote:
Joel Pitt wrote:
* I think such a project should make the data public domain. Ignore
silly ideas like giving be shares in the knowledge or whatever. It
just complicates things. If the project is really strapped for cash
later, then either
On 1/19/07, Matt Mahoney [EMAIL PROTECTED] wrote:
I think if you want to make a business out of AI, you are in for a lot of
work.First you need something that is truly innovative, that does
something that nobody else can do. What will that be? A search engine
better
than Google? A new
On 1/19/07, Bob Mottram [EMAIL PROTECTED] wrote:
My feeling is that this probably isn't a great business idea. I think
collecting common sense data and building that into a general reasoner
should really be thought of as a long term effort, which is unlikely to
appeal to business investors
On 1/19/07, Pei Wang [EMAIL PROTECTED] wrote:
For example, what you called rule in your postings have two
different meanings:
(1) A declarative implication statement, X == Y;
(2) A procedure that produces conclusions from premises, {X} |- Y.
These two are related, but not the same thing. Both
On 1/19/07, Benjamin Goertzel [EMAIL PROTECTED] wrote:
You have not explained how you will overcome the issues that plagued
GOFAI, such as
-- the need for massive amounts of highly uncertain background
knowledge to make real-world commonsense inferences
Precisely, we need to amass millions of
On 1/20/07, David Clark [EMAIL PROTECTED] wrote:
...
Do we divine the rules/laws/algorithms from a mass of data or do we
generate
the appropriate conclusions when we need them because we understand how it
actually works?
Just as chemistry is reducible to physics, in theory, while in reality
On 1/20/07, Benjamin Goertzel [EMAIL PROTECTED] wrote:
Backward chaining is just as susceptible to combinatorial explosions
as forward chaining...
And, importance levels need to be context-dependent, so that assigning
them requires sophisticated inference in itself...
The problem may not be
On 1/20/07, Stephen Reed [EMAIL PROTECTED] wrote:
I've been using OpenCyc as the standard ontology for my texai project.
OpenCyc contains only the very few rules needed to enable the OpenCyc
deductive inference engine operate on its OpenCyc content. On the other
hand ResearchCyc, whose
On 1/20/07, Benjamin Goertzel [EMAIL PROTECTED] wrote:
A) This is just not true, many commonsense inferences require
significantly more than 5 applications of rules
OK, I concur.
Long inference chains are built upon short inference steps. We need a
mechanism to recognize the interestingness
On 1/20/07, Pei Wang [EMAIL PROTECTED] wrote:
The bottomline is that the knowledge acquisition project is *separable*
from
specific inference methods.
What is your argument supporting this strong claim?
I guess every book on knowledge representation includes a statement
saying that whether
On 1/24/07, Bob Mottram [EMAIL PROTECTED] wrote:
I think it would be better to design a system with probabilistic reasoning
as a fundamental component from the outset, rather than trying to bolt this
on as an after thought. I know from doing a lot of stuff with machine
vision that modelling
On 1/25/07, Bob Mottram [EMAIL PROTECTED] wrote:
The trouble is that you can only really decide whether a statement is
non-probabilistic if enough people have voted unanimously yes or no. Even
then you can't be sure that the next person to vote won't go the opposite
way.
At the initial stage
On 1/25/07, Ben Goertzel [EMAIL PROTECTED] wrote:
If there is a major problem with Cyc, it is not the choice of basic
KR language. Predicate logic is precise and relatively simple.
I agree mostly, though I think even Cyc's simple predicate logic language
can be made even simpler and better.
for commonsense
reasoning -- if you closely
examine some of your own thoughts you'd see.
On 1/19/07, YKY (Yan King Yin) [EMAIL PROTECTED] wrote:
For the type of common sense reasoner I described, we need a *massive*
number of rules. You can either acquire these rule via machine learning
or
direct
On 1/25/07, Pei Wang [EMAIL PROTECTED] wrote:
Suppose I have a set of *deductive* facts/rules in FOPL. You can
actually
use this data in your AGI to support other forms of inference such as
induction and abduction. In this sense the facts/rules collection does
not
dictate the form of
On 1/27/07, Ben Goertzel [EMAIL PROTECTED] wrote:
Yes, you can reduce nearly all commonsense inference to a few rules,
but only if your rules and your knowledge base are not fully
formalized...
As I envision it, we would have a large number of rules. Some rules are
very abstract (eg rules
On 1/27/07, David Hart [EMAIL PROTECTED] wrote:
This license chooser may help: http://creativecommons.org/license/
Perhaps MindPixel2 discussion deserves its own list at this stage?
Listbox, Google and many others offer list services (Google Code also offers
a wiki, source version management,
On 1/29/07, Eric Baum [EMAIL PROTECTED] wrote:
I haven't played 20 questions recently, but in response to your
comment I just went to www.20q.net and played thinking of Alice in
Wonderland, the book. The neural net guessed is it a novel on
question 22, and then decided it had gone far enough and
Ben,
Is the probabilistic logic you use in Novamente the same as Pei Wang's
version? If not, why do you use your version?
YKY
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On 1/29/07, Ben Goertzel [EMAIL PROTECTED] wrote:
Pei Wang's uncertain logic is **not** probabilistic, though it uses
frequency calculations
IMO Pei's logic has some strong points, especially that it unifies fuzzy and
probabilistic truth values into one pair of values. I think in Pei's logic
On 2/19/07, John Scanlon [EMAIL PROTECTED] wrote:
[...]
Logical deduction or inference is not thought. It is mechanical symbol
manipulation that can can be programmed into any scientific pocket
calculator.
[...]
Hi John,
I admire your attitude for attacking the core AI issues =)
One is
On 3/2/07, Matt Mahoney [EMAIL PROTECTED] wrote:
What about English? Irregular grammar is only a tiny part of the language
modeling problem. Uaing an artificial language with a regular grammar to
simplify the problem is a false path. If people actually used Logban
then
it would be used in
I agree with Ben and Pei etc on this issue. Narrow AI is VERY different
from general AI. It is not at all easy to integrate several narrow
AI applications to a single, functioning system. I have never heard of
something like this being done, even for two computer vision programs.
IMO what we
Hi John,
Re your idea that there should be an intermediate-level representation:
1. Obviously, we do not currently know how the brain stores that
representation. Things get insanely complex as neuroscientists go higher up
the visual pathways from the primary visual cortex.
2. I advocate
On 3/8/07, Matt Mahoney [EMAIL PROTECTED] wrote:
[re: logical abduction for interpretation of natural language]
One disadvantage of this approach is that you have to hand code lots of
language knowledge. They don't seem to have solved the problem of
acquiring
such knowledge from training
This is the agenda for an *integrated* AGI system (vs Minsky's distributed
one):
1. Fix a knowledge representation scheme (eg CycL, or Novamentese? etc)
2. Work out an uncertain logic (ie some form of logic + probability /
fuzziness).
3. Develop an *efficient* deductive algorithm for said
On 3/11/07, Jey Kottalam [EMAIL PROTECTED] wrote:
I'm stuck at steps 1 and 2. Even if we assume that the remaining steps
can be implemented once a knowledge representation is chosen, how do I
evaluate and judge a knowledge representation scheme's appropriateness
for AGI?
All the steps are
On 3/11/07, Ben Goertzel [EMAIL PROTECTED] wrote:
All this is perfectly useful stuff, but IMO is not in itself sufficient
for an AGI design. The basic problem is that there are many tasks
important for intelligence, for which is it apparently not possible to
create adequately efficient
On 3/12/07, Ben Goertzel [EMAIL PROTECTED] wrote:
Natural concepts in the mind are ones for which inductively learned
feature-combination-based classifiers and logical classifiers give
roughly the same answers...
1. The feature-combination-based classifiers CAN be encoded in the
probabilistic
Hi Josh,
You touched on a lot of deep issues; I'll give a *tentative* answer here.
Let's see what happens...
My main point is: a unified KR allows people to *work together*.
On 3/12/07, J. Storrs Hall, PhD. [EMAIL PROTECTED] wrote:
1. Fix a knowledge representation scheme (eg CycL, or
On 3/12/07, Ben Goertzel [EMAIL PROTECTED] wrote:
Yeah, and what you will find is that these more efficient algorithms
are more efficient only if you let them work with non-logical
knowledge representations ;-p
In NM, we do in fact have a unified logical representation -- but we
also have a
On 3/12/07, Russell Wallace [EMAIL PROTECTED] wrote:
Represented in logic can mean a number of different things, just
checking to see if everyone's talking about the same thing.
Consider, say, a 5 megapixel image. A common programming language
representation would be something like:
struct
The problem:
1. To be able to read many fonts
2. even totally new and strange-looking ones
3. even for the FIRST time one encounters a new, strange font; and
4. To be able to improve proficiency for a familiar font.
The NeoLego or modular approach is very vague and
computationally
So why do we need superfluous and bloated things like NeoLego or
Helvetica modules??
...or GA-based algorithms, for that matter!
YKY
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On 3/12/07, J. Storrs Hall, PhD. [EMAIL PROTECTED] wrote:
Certainly. Yet I am convinced that that's how it actually works. Someone
who
came from a theoretical pure communist economy where there was only one
organization that everybody worked for, would be aghast at the random
madhouse of a
On 3/13/07, Chuck Esterbrook [EMAIL PROTECTED] wrote:
When your AGI sees A for the first time(s) in Helvetica and learns
rules to recognize Helvetica A, then it only has rules for Helvetica
A. As opposed to having rules for A in general and rules for A in
Helvetica.
When Times Roman Italic A
On 3/13/07, Bob Mottram [EMAIL PROTECTED] wrote:
Early stage vision involves the detection of primitive types of geometry -
edges, lines of different orientation, blobs, corners, colours and motion in
different directions. These seem to arise from simple self-organisation due
to the physical
3 issues have been raised in this thread, by different people:
1. Richard Loosemore: Symbol names -- should they be system-generated or
human-entered?
This is a good question. In Cyc there are so-called pretty names (English
terms that describe Cyc concepts) but they are not sophisticated
On 3/16/07, David Clark [EMAIL PROTECTED] wrote:
Is very complicated a good reason to have 1 cognitive engine? Why not
have many and even use many on the same problem and then accept the best
answer? Best answer might change for a single problem depending on other
issues outside the actual
On 3/17/07, Ben Goertzel [EMAIL PROTECTED] wrote:
4) So, the question is not whether DARPA, M$ or Google will enter the
AI race -- they are there. The question is whether they will adopt a
workable approach and put money behind it. History shows that large
organizations often fail to do so,
On 3/18/07, Ben Goertzel [EMAIL PROTECTED] wrote:
If we succeed at creating the first AGI, it will not be because anything
fell into our hands. It will be because we
a) put in the many years of hard thinking to create a working AGI design
b) put in the many years of hard, often tedious, work
On 3/20/07, J. Storrs Hall, PhD. [EMAIL PROTECTED] wrote:
There is one way you can form a coherent, working system from a congeries
of
random agents: put them in a marketplace. This has a fairly rigorous
discipline of its own and most of them will not survive... and of course
the
system has
On 3/23/07, rooftop8000 [EMAIL PROTECTED] wrote:
Suppose there was an AGI framework that everyone could add
their ideas to.. What properties should it have? I listed
some points below. What would it take for
you to use the framework? You can add points if you like.
On 3/24/07, Jey
On 3/25/07, rooftop8000 [EMAIL PROTECTED] wrote:
The richer your set of algorithms and representations, the more likely
the correct ones will emerge/pop out as you put it. I don't really like
the idea of hoping for extra functionality to emerge.
This particular version of emergence does not
I've never heard of it used for knowledge representation. Can you explain
what's the deal?
IMO we should first delineate the AGI problem in a conventional framework
and then try to find out where is the computational bottleneck. And then
focus our innovation on that particular area, rather
I have been working on AGI seriously since 2004. I also believe that the
core algorithms needed for AGI could be very compact (though I won't make
an estimation of its size), with the rest of the information encoded
declaratively in the knowledgebase.
In a nutshell my current approach is
Let's take a poll?
I believe that a minimal AGI core, *sans* KB content, may be around 100K
lines of code.
What are other people's estimates?
YKY
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On 3/28/07, Russell Wallace [EMAIL PROTECTED] wrote:
Do you have a source of finance? This is not a rhetorical question; if you
have, I'd be very interested in working for money.
Yes, I think I have seed capital, that is enough to get a conventional
startup started. Also I believe getting
On 3/29/07, Jean-Paul Van Belle [EMAIL PROTECTED] wrote:
I guess (50 to 100 modules) x (500 to 2500 locs) x fudge factor x language
factor
with fudge factor = 2 to 4 and language factor = 1 for eg Python; 5 for eg
C++
50-100 modules? Sounds like you have a very unconventional architecture.
How does the new phenomenon of web-based collaboration change the way we
build an AGI? I feel that something is amiss in a business model if we
don't make use of some form of Web 2.0.
I think rooftop8000 is on the right track by thinking this way, but he may
not have it figured out yet.
On 3/30/07, Russell Wallace [EMAIL PROTECTED] wrote:
I think there's at least one good practical reason to avoid doing that, or
at least to do it at arm's length in a potential users discussing potential
features mailing list rather than here's our code as we write it. In the
early stages of
I just talked to some Cyc folks, and they assured me that CycL is adequate
to represent entire stories like Little Red Riding Hood.
The AGI framework has to operate on a knowledge representation language, and
building that language is not a programming task, rather a ontology
engineering task,
On 3/30/07, Matt Mahoney [EMAIL PROTECTED] wrote:
Wouldn't it save time in the long run to build a system that could
translate
English into your KR?
Yes, that's the goal. I'm just doing a human translation of the first
paragraph or so, to get the feel of CycL.
It can also be compared with
On 3/31/07, rooftop8000 [EMAIL PROTECTED] wrote:
How do you write and verify in cycl?
Download OpenCyc. Install. Open the Cyc browser. Read online tutorials.
=)
The IRC chatroom #OpenCyc on freenode.net may be helpful.
It may take some time to learn Cyc. I'm not good at it either, but I
Hi all,
I'm not very familiar with OWL and the Semantic Web... I'm wondering if OWL
has the potential to become a knowledge representation for AGI?
In principle, it seems that OWL is expressive enough -- OWL Full is more
expressive than DL (description logic) but I'm not sure how it compares
On 4/18/07, James Ratcliff [EMAIL PROTECTED] wrote:
Mark,
This is the closest Ive seen so far to my work and what I believe in,
Have you got some more specific information / code / algorithm / papers on
gathering and processing world information and discovery of?
I have been working with
On 4/18/07, James Ratcliff [EMAIL PROTECTED] wrote:
It should be a combination fo the two, even as Cyc is finding out now with
their use of Google to search out new terms and facts.
A really simple example of that is related objects... a book scraping can
generate a listed of objects it
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