I happened to have read John Sowa's articles on the subject of logic
and
see for example
http://www.jfsowa.com/talks/souprepr.htm
www.isd.mel.nist.gov/research_areas/research_engineering/Performance_Metrics/PerMIS_2004/Proceedings/Sowa.pdf
and of course his other materials and I must confess, I rather liked
his phrase 'long long way' from total fix to the knowledge problem.
I have also had a look at concept net-MIT media lab which appears to
be more popular. Broadly there are two streams analogy logic and
formal logic and John sowa seems to advocate a mixture of the two
approaches .
To my undestanding both approaches have to use the predicate
representation or it's equivalent. Semantic network -concept net also
is loosely equivalent to FOL the only difference being in the
inferencing process.
First Question - How much /how many predicate/s to use in the complete
representation of knowledge. That is in order for human like
inferencing to be possible what all should the knowledge
representation include?
Second Question -Can Formal Logic with tem****al,modal and HOL fully
represent knowledge?
Here is a little hirearchy and I am really looking at the top level
-root (beyond LOGIC?= features needed to understand like humans.
LOGIC-Statements(HIGHER ORDER+TEM****AL+MODAL)
FOPC Predicates(e.g VERBNET ,SUO-KIF word net mappings)
RDF Triples(Simple Predicates standardized)
RDBMS/XML(advantage XML)
Hoping for a little enlightenment.
