Rudolf Kruse is a full professor at the Department of Computer Science of the Otto-von-Guericke University of Magdeburg, Germany, where he leads the working group on computational intelligence. Christian Moewes and Pascal Held are research assistants at the same institution. Christian Borgelt is a principal researcher at the European Centre for Soft Computing, Mieres, Spain. Frank Klawonn is a Professor at the Department of Computer Science of Ostfalia University of Applied Sciences, Wolfenbüttel, Germany. Matthias Steinbrecher is a member of the SAP Innovation Center, Potsdam, Germany.

From the reviews: "This book teaches computational intelligence (CI) in a thorough, methodological manner that is theoretically profound and educationally oriented. ... this book is well designed for the independent student who wishes to learn the fundamentals of CI without the need for an instructor. The organization and thorough step-by-step methodology makes it an excellent startup guide for someone who wants to learn CI ... . This book is targeted at beginners, students, or professionals who wish to understand CI." (Mario Antoine Aoun, Computing Reviews, February, 2014) "The book under review is a textbook that features sub-symbolic approaches developed within the field of Artificial Intelligence ... . It can be used as a companion book for lectures, with exercises and slides to be found on the book's website. With its focus on sub-symbolic approaches, it presents a comprehensive and detailled source of information complementary to other commonly used textbooks in Artificial Intelligence that mostly focus on symbolic approaches." (Jana Kohler, zbMATH, Vol. 1283, 2014) "The book is a comprehensive treatise on computational intelligence with a focus on the underlying methodology and algorithms. ... The reader can enjoy a comprehensive and systematically arranged exposure of the material. ... The references following each chapter can serve as a list of introductory readings on the individual areas of computational intelligence. ... the reader gains a good sense of computational intelligence as an important endeavor supporting analysis and synthesis of intelligent systems. ... a useful compendium of knowledge for a broad audience." (Witold Pedrycz, Mathematical Reviews, November, 2013)

• Introduction.- Part I: Neural Networks.- Introduction.- Threshold Logic Units.- General Neural Networks.- Multi-Layer Perceptrons.- Radial Basis Function Networks.- Self-Organizing Maps.- Hopfield Networks.- Recurrent Networks.- Mathematical Remarks.- Part II: Evolutionary Algorithms.- Introduction to Evolutionary Algorithms.- Elements of Evolutionary Algorithms.- Fundamental Evolutionary Algorithms.- Special Applications and Techniques.- Part III: Fuzzy Systems.- Fuzzy Sets and Fuzzy Logic.- The Extension Principle.- Fuzzy Relations.- Similarity Relations.- Fuzzy Control.- Fuzzy Clustering.- Part IV: Bayes Networks.- Introduction to Bayes Networks.- Elements of Probability and Graph Theory.- Decompositions.- Evidence Propagation.- Learning Graphical Models.

Rudolf Kruse is a full professor at the Department of Computer Science of the Otto-von-Guericke University of Magdeburg, Germany, where he leads the working group on computational intelligence. Christian Moewes and Pascal Held are research assistants at the same institution. Christian Borgelt is a principal researcher at the European Centre for Soft Computing, Mieres, Spain. Frank Klawonn is a Professor at the Department of Computer Science of Ostfalia University of Applied Sciences, Wolfenbüttel, Germany. Matthias Steinbrecher is a member of the SAP Innovation Center, Potsdam, Germany.

From the reviews: "This book teaches computational intelligence (CI) in a thorough, methodological manner that is theoretically profound and educationally oriented. ... this book is well designed for the independent student who wishes to learn the fundamentals of CI without the need for an instructor. The organization and thorough step-by-step methodology makes it an excellent startup guide for someone who wants to learn CI ... . This book is targeted at beginners, students, or professionals who wish to understand CI." (Mario Antoine Aoun, Computing Reviews, February, 2014) "The book under review is a textbook that features sub-symbolic approaches developed within the field of Artificial Intelligence ... . It can be used as a companion book for lectures, with exercises and slides to be found on the book's website. With its focus on sub-symbolic approaches, it presents a comprehensive and detailled source of information complementary to other commonly used textbooks in Artificial Intelligence that mostly focus on symbolic approaches." (Jana Kohler, zbMATH, Vol. 1283, 2014) "The book is a comprehensive treatise on computational intelligence with a focus on the underlying methodology and algorithms. ... The reader can enjoy a comprehensive and systematically arranged exposure of the material. ... The references following each chapter can serve as a list of introductory readings on the individual areas of computational intelligence. ... the reader gains a good sense of computational intelligence as an important endeavor supporting analysis and synthesis of intelligent systems. ... a useful compendium of knowledge for a broad audience." (Witold Pedrycz, Mathematical Reviews, November, 2013)

• Introduction.- Part I: Neural Networks.- Introduction.- Threshold Logic Units.- General Neural Networks.- Multi-Layer Perceptrons.- Radial Basis Function Networks.- Self-Organizing Maps.- Hopfield Networks.- Recurrent Networks.- Mathematical Remarks.- Part II: Evolutionary Algorithms.- Introduction to Evolutionary Algorithms.- Elements of Evolutionary Algorithms.- Fundamental Evolutionary Algorithms.- Special Applications and Techniques.- Part III: Fuzzy Systems.- Fuzzy Sets and Fuzzy Logic.- The Extension Principle.- Fuzzy Relations.- Similarity Relations.- Fuzzy Control.- Fuzzy Clustering.- Part IV: Bayes Networks.- Introduction to Bayes Networks.- Elements of Probability and Graph Theory.- Decompositions.- Evidence Propagation.- Learning Graphical Models.

Rudolf Kruse is a full professor at the Department of Computer Science of the Otto-von-Guericke University of Magdeburg, Germany, where he leads the working group on computational intelligence. Christian Moewes and Pascal Held are research assistants at the same institution. Christian Borgelt is a principal researcher at the European Centre for Soft Computing, Mieres, Spain. Frank Klawonn is a Professor at the Department of Computer Science of Ostfalia University of Applied Sciences, Wolfenbüttel, Germany. Matthias Steinbrecher is a member of the SAP Innovation Center, Potsdam, Germany.

From the reviews: "This book teaches computational intelligence (CI) in a thorough, methodological manner that is theoretically profound and educationally oriented. ... this book is well designed for the independent student who wishes to learn the fundamentals of CI without the need for an instructor. The organization and thorough step-by-step methodology makes it an excellent startup guide for someone who wants to learn CI ... . This book is targeted at beginners, students, or professionals who wish to understand CI." (Mario Antoine Aoun, Computing Reviews, February, 2014) "The book under review is a textbook that features sub-symbolic approaches developed within the field of Artificial Intelligence ... . It can be used as a companion book for lectures, with exercises and slides to be found on the book's website. With its focus on sub-symbolic approaches, it presents a comprehensive and detailled source of information complementary to other commonly used textbooks in Artificial Intelligence that mostly focus on symbolic approaches." (Jana Kohler, zbMATH, Vol. 1283, 2014) "The book is a comprehensive treatise on computational intelligence with a focus on the underlying methodology and algorithms. ... The reader can enjoy a comprehensive and systematically arranged exposure of the material. ... The references following each chapter can serve as a list of introductory readings on the individual areas of computational intelligence. ... the reader gains a good sense of computational intelligence as an important endeavor supporting analysis and synthesis of intelligent systems. ... a useful compendium of knowledge for a broad audience." (Witold Pedrycz, Mathematical Reviews, November, 2013)

• Introduction.- Part I: Neural Networks.- Introduction.- Threshold Logic Units.- General Neural Networks.- Multi-Layer Perceptrons.- Radial Basis Function Networks.- Self-Organizing Maps.- Hopfield Networks.- Recurrent Networks.- Mathematical Remarks.- Part II: Evolutionary Algorithms.- Introduction to Evolutionary Algorithms.- Elements of Evolutionary Algorithms.- Fundamental Evolutionary Algorithms.- Special Applications and Techniques.- Part III: Fuzzy Systems.- Fuzzy Sets and Fuzzy Logic.- The Extension Principle.- Fuzzy Relations.- Similarity Relations.- Fuzzy Control.- Fuzzy Clustering.- Part IV: Bayes Networks.- Introduction to Bayes Networks.- Elements of Probability and Graph Theory.- Decompositions.- Evidence Propagation.- Learning Graphical Models.