Rough Sets and Intelligent Systems - Professor Zdzis aw Pawlak in Memoriam

This book demonstrates that the scientific approaches discovered by Professor Zdzislaw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by leading researchers worldwide.

This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being.

This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches.

We are proud to offer the readers this book.

Dedicated to the memory of Professor Zdzislaw Pawlak, the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence This book prepared in two volumes contains more than 50 chapters Demonstrates that the scientific approaches discovered by Professor Zdzislaw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by leading researchers worldwide

Inhalt
From the Contents: From Logic to Computer Science A Personal Experience.- Knowledge Algebras and Their Discrete Duality.- Comparison of Greedy Algorithms for Decision Tree Optimization.- A Review of the Knowledge Granulation Methods: Discrete vs Continuous Algorithms.- Game-theoretic Rough Sets for Feature Selection.- A Clustering Approach to Image Retrieval Using Range Based Query and Mahalanobis Distance.- Classifiers Based on Data Sets and Domain Knowledge: A Rough Set Approach.- Incorporating Rough Data in Database Design for Imprecise Information Representation.