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: Professor Zdzis.aw Pawlak (1926-2006): Founder of the Polish School of Artificial Intelligence.- List ofWorks by Professor Zdzis.aw Pawlak (1926-2006) :.- Rough Sets: From Rudiments to Challenges.- Zdzis.aw Pawlak, Databases and Rough Sets.- jMAF - Dominance-based Rough Set Data Analysis Framework.- Dynamic Programming Approach for Exact Decision Rule Optimization.- Approaches for Updating Approximations in Set-Valued Information Systems while Objects and Attributes Vary with Time.- On the Gradual Evolvement of Things.- An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough Classification.- Exploring Neighborhood Structures with Neighborhood Rough Sets in Classification Learning.