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 text processing and getting a bot to "read" and
process books/ newspapers as a main method of learning.
James Ratcliff
Mark Waser <[EMAIL PROTECTED]> wrote: Since everyone else is doing it
. . . .
My interests are
Coordinated Knowledge-Base/World-Model Building and
Friendliness/Morality/Goal Development & Optimization
Fundamentally, this means developing
Knowledge-harvesting agents
Knowledge-collapsing/coordinating agents
Knowledge-retrieval agents (includes planning, will be Friendliness
constrained)
Conversational agents (includes building a model of the other
conversant, will be Friendliness constrained)
My personal belief is that a collection of the above agents with a goal
and access to a knowledge-base/world-model *is* a self-willed mind. Given
that I believe that all of the above could be developed in a fairly brief
time-frame (i.e. during *my* lifetime), I am also extremely interested in
(Friendly!) motivational systems.
For *my* purposes, I am limiting *my* concept of AGI to the concept level
and above. I am not doing any sensory work other than with textual and
electronic data (well, except for some dabbling in two-dimensional image
reading for a specific project). I think that this is a rational partition
and does not violate the General in AGI since I *don't* believe that our
senses are "Intelligent".
I have an evolving knowledge representation scheme that grew out of some
dabbling with a link parser with some of the Novamente folk (since it's my
belief that language fairly closely mirrors the structures that the
brain/intelligence is using and that language and our brains have co-evolved
to a better-than decent solution). I am trying to create a "seed
knowledge-base/world model" starting with an initial *vocabulary* of Simple
English or Basic English, rules for parsing it into my knowledge scheme
(knowledge harvesting), and rules for coordinating/collapsing knowledge
(including tracking sources of knowledge and recognizing *and maintaining*
conflicting knowledge). Translating the knowledge scheme back into English is
fairly trivial (with most of the difficulties being where to terminate the
graph and how to organize the phrases for maximum clarity) but scaling is a
HUGE problem.
One of the PRODUCTS that I'd like to quickly produce is a system that
does conflict resolution for humans (i.e. clearly representing what the
disagreement is down to the level where they agree to disagree). I'd then
like to turn that product to work on my current (pretty much complete) model
of Friendliness and how to turn that into a motivational system (or, maybe, I
could just start a huge site for arguing politics :-).
I am currently trying to get a lot of this into shape where I can ask for
collaborators. Since the core of "my" scheme is a defined *common*
knowledge-representation framework, I believe that it will be possible to
parcel out various tasks (most of which will be agent-development,
translators, and user interfaces). My personal preference is the .NET
framework (solely due to the amount of infrastructure); however, I would love
to see interfaces to work done on any platform. While my description strikes
me as sounding very logic-based, the knowledge-representation is a giant
network and many of the agents I've spec'ed act using schemes more familiar to
neural networks (spreading activation) or enzymes (yes, I am truly going back
to my roots :-).
Having seen the internals of Novamente, I am very impressed but they are
currently going down a slightly different path than I would enjoy following
(doing more knowledge creation and discovery than harvesting and collapsing
coordination). I like what I've heard of Richard Loosemoore's ideas and would
like to see more. From this thread, I am intrigued by Stephen Reed and John
Rose since they seem to be on the same path that I'm following.
Oh yeah . . . . I started out as a biochemist and moved into computers
to facilitate upgrading our simulations (and even have a few published papers
in enzyme kinetics in the early 80's). I've worked in the financial arena
(including an Expert System Shell and Expert System Builder for Citicorp in
the early/mid 80's), government contracting (including a Project Manager's
Support System with an AI for scheduling, numerous Expert Systems for
procurement, and a neural network for diagnosing radioactive thallium images
of the heart for Air Force pilots), intelligence (which is why I am now *not*
willing to do most government contracting), international development (which
I'm pretty sour on as well), and a large number of data
collection/sharing/analysis systems. I have a M.S.E. in Artificial
Intelligence and bailed out of doing my dissertation on Machine Learning and
Human Decision-Making when my son was born.
Mark
----- Original Message -----
From: Russell Wallace
To: [email protected]
Sent: Monday, March 26, 2007 4:02 PM
Subject: Re: [agi] AGI interests
I don't believe AI in the sense of a self-willed mind is going to happen;
fortunately, it doesn't need to. The two problems I want to help solve are
the global loss of fifty million lives a year, and the difficulty in living
in the 99.999...999% of the universe that isn't Earth. Each of these is a
problem not of magnitude but of complexity, so to solve them we need better
tools for handling complexity.
At present we have marvellous tools for handling human-readable information,
but essentially all significant work still needs to be done by humans. Even
our richest, most sophisticated and flexible programs are tiny isolated
fragments, brittle and opaque, animated step by small painful step only by
the constant labor of armies of human workers. We need to do for
machine-readable information/procedural knowledge what we have done for
text: create a rich, fluid environment in which humans need merely say what
we want, and the machines will handle the details of delivering it to us. If
we can build tools that powerful, we can start making real progress on the
problems of complexity.
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James Ratcliff - http://falazar.com
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