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Subject: PIP-Bullet2-Cognitive Information Processing Technology DARPA BAA02-21
- From: Rex Brooks <rexb@starbourne.com>
- To: huml@lists.oasis-open.org
- Date: Wed, 11 Jun 2003 08:35:19 -0700
Title: PIP-Bullet2-Cognitive Information Processing
Technolog
Hi Everyone,
Here is the second bullet
point from the Broad Agency Announcement of DARPA's Cognitive
Information Processing Technology Call For Proposals
We didn't get much
response from the first bullet posting, and as I said, I may
well lose interest if we continue with no response. I will
include the preamble for the remainder of these first bullet
points.
Just so you know, I rather expected someone to address what
constitutes "substantial amounts of appropriately represented
knowledge." I am not at all sure that DARPA means high-level
ontologies when they state that. THAT's what I thought, but do you
all?
I will continue with this exploration for a while, but I would
not proceed on this on my own, so nuff said.
BAA #02-21
Cognitive Information
Processing Technology
Proposer Information Pamphlet
Cognitive Information Processing Technology
SOL BAA 02-21 POC: Dr. Ronald J. Brachman, Mr. Zachary J. Lemnios,
DARPA/IPTO
E-Mail: baa02-21@darpa.mil
FAX: (703) 741-7804
WEB:
http://www.darpa.mil/ipto/Solicitations/index
This is the first set of
bullet points I will address wrt to the PIP (Proposer Information
Pamphlet) of the BAA. I will post these responses with their own
number which relates only to the order in which I post them, and not
in any other framework.
This what DARPA is asking for:
"...
The DARPA Information Technology Processing Office (IPTO) is
soliciting innovative research proposals in the area of information
technology for a new class of cognitive systems that can be
characterized simply as follows: a cognitive system is one that, among
other things,
* can reason in a variety of ways, using substantial amounts of
appropriately represented knowledge;
* can learn from its experiences so that its performance improves as
it accumulates knowledge and experience;
* can explain itself and can accept direction;
* can be aware of its own behavior and reflect on its own
capabilities; and
* can respond in a robust manner to
surprises.
..."
bullet two:
* can learn from its experiences so that its performance improves as
it accumulates knowledge and experience;
Well, this one's a pickle and I would like the more expert AI folks
among us to clear up the two bottlenecks that will occur in any answer
to this stipulation:
1. What is the most widely accepted definition for proof or clear
indication of learning?
Is it only that wrong or inaccurate information, e.g. information that
is the basis for actions or conclusions which do not yield anticipated
outcomes, is corrected and that a series of trials and errors can be
conducted by the agent until the most accurate information is adopted
as the working hypothesis for a given set of conditions in a given
situation, yielding consistent outcomes?
This will result in improved performance statistically, but will it
allow the agent to learn and evaluate methods, and arrive at
conclusions about how best to conduct the process of learning? That
would seem to me to be the more important kind of learning, and I
wouldn't mind having some help with that myself.
2. What kind of criteria should an agent have in order to choose the
most appropriate experiences to use for models and comparisons when
confronted with new situations which call for the use of accumulated
knowledge and experience?
Obviously, we need not only to state what criteria we use for 2, but
also what definitions, since I suspect there are several, we choose
for 1. And, of course, can we know beforehand what definitions DARPA
accepts for 1 and what criteria it uses for 2? I suspect we are
allowed to ask, but I think such actions should be undertaken by those
who will be assembling the actual proposal.
Of course, none of this includes such things as the ability to infer
unexpressed information from what is included or left out of
information exchanged, or non-verbal behavioral cues, which together
comprise one of the more important aspects of cognitive
systems.
I'm sure there is much more that needs to be discussed for a
satisfactory answer to this bullet point.
I could argue several sides but I get real tired of talking to
myself, honest. ;)
Ciao,
Rex
--
Rex Brooks
GeoAddress: 1361-A Addison, Berkeley, CA, 94702 USA, Earth
W3Address: http://www.starbourne.com
Email: rexb@starbourne.com
Tel: 510-849-2309
Fax: By Request
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