a semantic inference system


Subject: a semantic inference system
From: Giuseppe Rossettini (elpaso@interplanet.it)
Date: Fri May 05 2000 - 12:04:28 MET DST


Usual inference systems first act on the possibility distribution induced
by a single fuzzy set, then they aggregate the actived consequents, in
order to obtain a defuzzified output. This approach does not express the
cognitive effects of the inference process: inference produces new
prototypical answers (linguistic values) by merging the meaning of the
reference-prototypes (the original consequent), given the partial
satisfaction of the antecedents.

This aspect emerges when considering problems whith highly qualitative
nature (MISO systems with a small consequent space partition). So the
inference engine, once evaluated the rules activation degree,
1) select the most plausible consequents to be selected
2) acts on the meaning of the their respective linguistic values (without
reducing their height)
3) then merges their meaning to obtain the new linguistic value.

4) An interpretation algorithm furnish the verbose answer.

People interested in this idea can contact me privately (I'm looking for a
Ph.D. position): indeed I provided it with a complete axiomatization, but I
did not fully investigate the operator's properties (expecially
monotonicity).

Giuseppe Rossettini

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