Granular computing, initiated by Lotfi A. Zadeh, has acquired wide popularity as a tool for approximate reasoning, fusion of knowledge, cognitive computing. The need for formal methods of granulation, and means for computing with granules, has been addressed in this work by applying methods of rough mereology. Rough mereology is an extension of mereology taking as the primitive notion the notio...

We propose a uniied formal treatment of problems of design, analysis, synthesis and control in distributed systems of intelligent agents. Our approach is rooted in rough set theory and we propose rough mereology as a foundational basis for our approach.

In this research paper, we explore the philosophical connections between Rough YSystems RYS, mereology and concepts in applied ontology, introduce the concept of contamination-free rough dependence and compare this to possible concepts of probabilistic dependence. The nature of granular rough dependence is also characterized and the reason for breakdown of comparison of rough set models with pr...

We propose a uniied formal treatment of problems of control in distributed systems of intelligent agents. Our approach is rooted in rough set theory and we propose rough mereology as a foundational basis for our approach. We present a general structure of rough mereological controller.

Rough mereology allows for similarity measures (called rough inclusions) which in turn form a basis for the mechanism of granulation of knowledge. Granules of knowledge, defined as classes of satisfactorily similar objects, can be regarded as worlds in which properties of entities are evaluated. Obtained in this way granular rough mereological intensional logics reveal essential properties of r...

This work aims at presenting to a wider audience fundamental notions and ideas of rough mereology. We discuss various methods for constructing rough inclusions in data sets, then we show how to apply them to the task of knowledge granulation, and finally, we introduce granular reflections of data sets with examples of classifiers built on them.

We discuss two basic questions related to the synthesis of decision algorithms. The rst question can be formulated as follows: what strategies can be used in order to discover the decision rules from experimental data? Answering this question, we propose to build these strategies on the basis of rough set methods and Boolean reasoning techniques. We present some applications of these methods fo...

Rough inclusion functions are mappings considered in the rough set theory with which one can measure the degree of inclusion of a set in a set (and in particular, the degree of inclusion of an information granule in an information granule) in line with rough mereology. On the other hand, similarity indices are mappings in cluster analysis with which one can compare clusterings, and clustering m...

Granular computing, initiated by Lotfi A. Zadeh, has acquired wide popularity as a tool for approximate reasoning, fusion of knowledge, cognitive computing. The need for formal methods of granulation, and means for computing with granules, has been addressed in this work by applying methods of rough mereology. Rough mereology is an extension of mereology taking as the primitive notion the notio...