"To write a foreword to Professor Rutkowski's opus "Flexible Neuro-Fuzzy Systems" or FNFS for short, was a challenging task. Today, there exists an extensive literature on neuro-fuzzy systems, but Professor Rutkowski's work goes far beyond what is in print. FNFS ventures into new territory and opens the door to new directions in research and new application areas.
To say that Professor Rutkowski's work is a major contribution to the theory and application of neuro-fuzzy systems is an understatement. The wealth of new ideas, the thoroughness of analysis, the attention to detail, the use of computer simulation, the problems at the end of each chapter, and high expository skill, combine to make Professor Rutkowski's work a must reading for anyone interested in the conception, design and utilization of intelligent systems. Professor Rutkowski and the publisher, Kluwer, deserve a loud applause".
"Soft computing is a key concept for the creation of such human-friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present volume, based mostly on his own work, is a milestone in the development of soft computing, integrating various disciplines from the fields of information science and engineering.
The book has clear motivation to give strong impact to the field of soft computing. It is my pleasure to feel sympathies with the enthusiasm and energy of Professor Rutkowski to devote himself to the new emerging field."
"Publication of this book is a special event. This valuable title fills a serious gap in domestic science and technical literature. At the same time it introduces a reader to the most recent achievements in the quickly developing branch of knowledge which the computational intelligence has been for several years. The field, which is a subject of this book, is one of t hose important fields of science which enable to process information included in data and give their reasonable interpretation programmed by a user.
Recent decades have brought a stormy development of computer techniques and related computational methods. Together with their appearance and quick progress, theoretical and applied sciences developed as well, enabling the user to fully utilize newly created computational potential and to get knowledge out of increasing wealth of data. The development of computational intelligence is then strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors.
Without them the development of this field would be almost impossible, and its application practically marginal. That is why these techniques have especially developed in recent years.
The development of computational intelligence systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. Nature when undertakes intelligent actions processes data in parallel regulating and adjusting these actions through feedback mechanisms.
In such a system learning neural networks function. Another example can be optimization algorithms modelled based on natural selection processes or fuzzy logic systems reflecting vagueness fuzziness, subjectivity or relativism of human being assessments.
Computational intelligence is a new branch of science and its development dates back to the 60s of the last century when the first algorithms of learning machines -forerunners of today's neural networks - were developed.
Then, in the 70s foundations of set theory and fuzzy logic were created. In this early period of computational intelligence development genetic and evolutionary algorithms were introduced. In the 80s the bases for representation of knowledge using rough sets were also created. In recent years many hybrid techniques connecting learning systems with evolutionary and fuzzy ones were developed as well.
Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, in biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations.
The essence of the systems based on computational intelligence is to process and interpret data of various nature. These can be numerical, symbolic (e.g. language data of different degree of accuracy), binary, logical data or, for example, uncoded images read out directly on camera screen.
The data can be formatted as numbers, that means single elements of vectors, as vectors or tables or as strings of elements or tables composed of them. They can also be composed of ordered sequences of elements or tables and contain elements described in a very inaccurate or even subjective manner.
The common feature of computational intelligence systems is that they process information in cases when presentation in the form of algorithms is difficult and they do it in connection with a symbolic representation of knowledge. These can be relations concerning an object known only based on a finite number of measurements of output and input state (activation).
These can also be data binding the most probable diagnosis with a series of observed, often descriptive symptoms. In other cases these carl be data characterizing sets in respect to some special features which are initially intangible to the user until they are derived from data and defined as dominant features. These systems have the capability to reconstruct behaviours observed in learning sequences, can form rules of inference and generalize knowledge in situations when they are expected to make prediction or to classify the object to one of previously observed categories.
This book is not only a valuable title on the publishing market, but is also a successful synthesis of computational intelligence methods in world literature.
A special advantage of the book is that it contains many examples and illustrations of the methods described, which creates good opportunities to program the presented algorithms. This book should be recommended to engineers of various specialties, physicists, mathematicians, information technology specialists, economists and students of those or related specialties.
It should give great satisfaction both to the author due to its publishing and to many readers who will use the techniques described in the book to solve practical issues they are interested ill."
July 18, 2007
Jacek M. Zurada
Past President of IEEE Computational Intelligence Society
1. Danuta Rutkowska, Maciej Piliński, Leszek Rutkowski, Sieci Neuronowe, Algorytmy Genetyczne i Systemy Rozmyte, PWN, 1997.
2. Danuta Rutkowska, Maciej Piliński, Leszek Rutkowski, Sieci Neuronowe, Algorytmy Genetyczne i Systemy Rozmyte, PWN, 2004.
3. Leszek Rutkowski, New Soft Computing Techniques for System Modelling, Pattern Classification and Image Proceesing, Springer-Verlag, 2004. (see here)
From Prof. Shun-ichi Amari's preface:
"Soft computing is a key concept for the creation of such human-friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present volume, based mostly on his own work, is a milestone in the development of soft computing, integrating various disciplines from the fields of information science and engineering.
The book has clear motivation to give strong impact to the field of soft computing. It is my pleasure to feel sympathies with the enthusiasm and energy of Professor Rutkowski to devote himself to the new emerging field."
4. Leszek Rutkowski, Flexible Neuro-Fuzzy Systems: Structures, Learning and Performance Evaluation, Kluwer Academic Publishers, 2004. (see here)
From Prof. Lotfi Zadeh's foreword:
"To write a foreword to Professor Rutkowski's opus "Flexible Neuro-Fuzzy Systems" or FNFS for short, was a challenging task. Today, there exists an extensive literature on neuro-fuzzy systems, but Professor Rutkowski's work goes far beyond what is in print. FNFS ventures into new territory and opens the door to new directions in research and new application areas
To say that Professor Rutkowski's work is a major contribution to the theory and application of neuro-fuzzy systems is an understatement. The wealth of new ideas, the thoroughness of analysis, the attention to detail, the use of computer simulation, the problems at the end of each chapter, and high expository skill, combine to make Professor Rutkowski's work a must reading for anyone interested in the conception, design and utilization of intelligent systems. Professor Rutkowski and the publisher, Kluwer, deserve a loud applause"
5. Leszek Rutkowski, Computational Intelligence, Springer, 2008. (see here)
6. Leszek Rutkowski, Metody i Techniki Sztucznej Inteligencji (wydanie II rozszerzone), PWN, Warszawa, 2009. (see here)
7. Рутковский Лешек, Методы и технологии искусственного интеллекта, Горячая линия-Телеком, 2010.
a) Leszek Rutkowski, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek Żurada, (eds.), Proceedings of the Eight International Conference: Artificial Intelligence and Soft Computing, ICAISC - 2006, Zakopane, Springer-Verlag 2006. (see here)
b) Leszek Rutkowski, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek Żurada, (eds.), Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, vol. 5097, Springer-Verlag 2008. (see here)
c) Leszek Rutkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Żurada, (eds.), Artificial Intelligence and Soft Computing, 10th International Conference, ICAISC 2010, Zakopane, Poland, June 13-17, 2010, Lecture Notes in Artificial Intelligence, vol. 6113 and vol. 6114, Springer-Verlag 2010. (see here and here)
d) Leszek Rutkowski, Marcin Korytkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Żurada, (eds.), Artificial Intelligence and Soft Computing, 11th International Conference, ICAISC 2012, Zakopane, Poland, April 29-May 3, 2012, Lecture Notes in Artificial Intelligence, vol. 7267 and vol. 7268, Springer-Verlag 2012. (see here and here)
e) Leszek Rutkowski, Marcin Korytkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Żurada, (eds.), Artificial Intelligence and Soft Computing, 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Lecture Notes in Artificial Intelligence, vol. 7894 and vol. 7895, Springer-Verlag 2013. (see here and here)
f) L. Rutkowski, M. Korytkowski, R. Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (Eds.), Artificial Intelligence and Soft Computing, 13th International Conference, ICAISC 2014, Zakopane, Poland, 1-5 June, 2014, Lecture Notes in Artificial Intelligence. vol. 8467 and 8468, Springer 2014. (see here and here)
g) L. Rutkowski, M. Korytkowski, R. Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (Eds.), Artificial Intelligence and Soft Computing, 14th International Conference, ICAISC 2015, Zakopane, Poland, 14-18 June, 2015, Lecture Notes in Artificial Intelligence. vol. 9119 and vol. 9120, Springer 2015. (see here and here)
Leszek Rutkowski received the MSc and PhD degrees from the Technical University of Wroclaw, Poland, in 1977 and 1980, respectively. Since 1980, he has been with the Technical University of Czestochowa, where he is currently a professor and director of the Institute of Computational Intelligence. From 1987 to 1990, he held a visiting position at the School of Electrical and Computer Engineering, Oklahoma State University. His research interests include data stream mining, big data analysis, neural networks, fuzzy systems, computational intelligence, pattern classification, and expert systems. He has published more than 200 technical papers, including 22 in various series of IEEE Transactions. He is the author of the following books: Computational Intelligence (Springer, 2008), New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Springer, 2004), Flexible Neuro-Fuzzy Systems (Kluwer Academic, 2004), Methods and Techniques of Artificial Intelligence (2005, in Polish), Adaptive Filters and Adaptive Signal Processing (1994, in Polish), and coauthor of two others (1997 and 2000, in Polish) Neural Networks, Genetic Algorithms and Fuzzy Systems and Neural Networks for Image Compression. He is the president and founder of the Polish Neural Networks Society. He organized and served as a General Chair of the International Conferences on Artificial Intelligence and Soft Computing held in 1996, 1997, 1999, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2013, 2014, 2015, 2016 and 2017. He was an associate editor of the IEEE Transactions on Neural Networks (1998-2005) and IEEE Systems Journal (2007-2010). He is an editor-in-chief of the Journal of Artificial Intelligence and Soft Computing Research, and he is on the editorial board of the IEEE Transactions on Cybernetics, International Journal of Neural Systems, International Journal of Applied Mathematics and Computer Science and International Journal of Biometric. He is a recipient of the IEEE Transactions on Neural Networks 2005 Outstanding Paper Award. He served in the IEEE Computational Intelligence Society as the chair of the Distinguished Lecturer Program (2008-2009) and the chair of the Standards Committee (2006-2007). He is the founding chair of the Polish chapter of the IEEE Computational Intelligence Society, which won the 2008 Outstanding Chapter Award. In 2004, he was elected as a member of the Polish Academy of Sciences. In 2004, he was awarded by the IEEE Fellow membership grade for contributions to neurocomputing and flexible fuzzy systems. He received a degree honoris causa from prestigious AGH University of Science and Technology in Cracow “in recognition of outstanding scientific achievements in the field of artificial intelligence in particular neuro-fuzzy systems”.
