The monograph offers a view on Rough Mereology, a tool for
reasoning under uncertainty, which goes back to Mereology,
formulated in terms of parts by Lesniewski, and borrows from Fuzzy
Set Theory and Rough Set Theory ideas of the containment to a
degree. The result is a theory based on the notion of a part to a
degree.
One can invoke here a formula Rough: Rough Mereology: Mereology
= Fuzzy Set Theory: Set Theory. As with Mereology, Rough Mereology
finds important applications in problems of Spatial Reasoning,
illustrated in this monograph with examples from Behavioral
Robotics. Due to its involvement with concepts, Rough Mereology
offers new approaches to Granular Computing, Classifier and
Decision Synthesis, Logics for Information Systems, and
are--formulation of well--known ideas of Neural Networks and Many
Agent Systems. All these approaches are discussed in this
monograph.
To make the exposition self--contained, underlying notions of
Set Theory, Topology, and Deductive and Reductive Reasoning with
emphasis on Rough and Fuzzy Set Theories along with a thorough
exposition of Mereology both in Lesniewski and
Whitehead--Leonard--Goodman--Clarke versions are discussed at
length.
It is hoped that the monograph offers researchers in various
areas of Artificial Intelligence a new tool to deal with analysis
of relations among concepts. "
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