36 research outputs found
A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive Heuristics
We propose a nonmonotonic Description Logic of typicality able to account for
the phenomenon of concept combination of prototypical concepts. The proposed
logic relies on the logic of typicality ALC TR, whose semantics is based on the
notion of rational closure, as well as on the distributed semantics of
probabilistic Description Logics, and is equipped with a cognitive heuristic
used by humans for concept composition. We first extend the logic of typicality
ALC TR by typicality inclusions whose intuitive meaning is that "there is
probability p about the fact that typical Cs are Ds". As in the distributed
semantics, we define different scenarios containing only some typicality
inclusions, each one having a suitable probability. We then focus on those
scenarios whose probabilities belong to a given and fixed range, and we exploit
such scenarios in order to ascribe typical properties to a concept C obtained
as the combination of two prototypical concepts. We also show that reasoning in
the proposed Description Logic is EXPTIME-complete as for the underlying ALC.Comment: 39 pages, 3 figure
A Description Logic of Typicality for Conceptual Combination
We propose a nonmonotonic Description Logic of typicality able to
account for the phenomenon of combining prototypical concepts, an open problem
in the fields of AI and cognitive modelling. Our logic extends the logic of
typicality ALC + TR, based on the notion of rational closure, by inclusions
p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming
from the distributed semantics of probabilistic Description Logics. Additionally,
it embeds a set of cognitive heuristics for concept combination. We show that the
complexity of reasoning in our logic is EXPTIME-complete as in ALC