Peter,

I'm afraid that your question cannot be answered as it is. AI is
highly fragmented, which not only means that few project is aiming at
the whole field, but also that few is even covering a subfield as you
listed. Instead, each project usually aims at a special problem under
a set of special assumptions. Consequently, it is not always
meaningful to compare them in functionality.

For example, many people may agree that "Stanley the Volkswagen"
represents the SOTA in robot car, but is it SOTA in Interactive
robotics systems? Is it ahead of Cog? When common-sense KB is
mentioned, people will think about Cyc, but is it SOTA? If it is not,
which one is? How can we compare an inference engine based on
first-order predicate calculus to one on Bayesian net?

Of course, in each field, there are projects that are more typical,
more influential, or more interesting than the rest, but they are not
really SOTA in the sense that it is ahead of the others in
functionality, since "the others" are usually running to different
directions.

In your list, NLP may be an exception to what I said above. Since I'm
not an expert in that field, I won't try to answer.

By definition, "Integrated intelligent systems" should be comparable,
but clearly there is no consensus on this topic yet. ;-)

Pei

On 10/19/06, Peter Voss <[EMAIL PROTECTED]> wrote:
I'm often asked about state-of-the-art in AI, and would like to get some
opinions.

What do you regard, or what is generally regarded as SOTA in the various AI
aspects that may be, or may be seen to be relevant to AGI?

For example:

- Comprehensive (common-sense) knowledge-bases and/or ontologies
- Inference engines, etc.
- Adaptive expert systems
- Question answering systems
- NLP components such as parsers, translators, grammar-checkers
- Interactive robotics systems (sensing/ actuation) - physical or virtual
- Vision, voice, pattern recognition, etc.
- Interactive learning systems
- Integrated intelligent systems
... whatever ...

I'm looking for the best functionality -- irrespective of proprietary,
open-source, or academic.



Peter

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