Computational Intelligence: A Methodological Introduction

This textbook provides a comprehensive introduction to the field of computational intelligence, covering fundamental concepts, algorithms, and practical implementations. It has been revised and expanded with new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms. It features supplementary material, classroom-tested examples, and insights into the successful application of computational intelligence methods.

Format: Paperback / softback
Length: 639 pages
Publication date: 30 March 2023
Publisher: Springer Nature Switzerland AG

This comprehensive textbook offers a thorough and logical introduction to the field, delving into the fundamental concepts, algorithms, and practical implementations that drive the development of intelligent systems capable of exhibiting intelligent behavior in complex environments. In its enhanced third edition, this text has undergone a complete revision and expansion, incorporating extensive new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms.

Key Features:

Comprehensive Coverage: The textbook provides a comprehensive overview of computational intelligence, covering a wide range of topics essential for understanding and applying these methods. It covers classical areas such as artificial neural networks, fuzzy systems, and evolutionary algorithms, as well as emerging developments in the field, including ant colony optimization and probabilistic graphical models.

Supplementary Material: An associated website offers supplementary material, including lecture slides, code examples, and exercises, to enhance the learning experience. This resource is invaluable for students and practitioners seeking additional insights and hands-on practice.

Classroom-Tested Examples: Throughout the text, numerous classroom-tested examples and definitions are provided to aid in understanding complex concepts. These examples help to clarify the theoretical background and illustrate how computational intelligence methods can be applied to real-world problems.

Useful Insights: The textbook offers valuable insights into the necessary prerequisites for successful application of computational intelligence methods. It explains the theoretical foundations underpinning proposed solutions and discusses the practical considerations involved in implementing these solutions.

Detailed Discussion: The book delves into great detail, discussing the classical areas of artificial neural networks, fuzzy systems, and evolutionary algorithms. It provides a thorough understanding of the underlying principles, algorithms, and applications of these methods, enabling readers to apply them effectively to solve complex problems.

Latest Developments: The textbook reviews the latest developments in the field, covering topics such as deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms. It provides readers with an up-to-date understanding of the state-of-the-art techniques and applications in computational intelligence.

In conclusion, this comprehensive textbook is an invaluable resource for students, researchers, and practitioners interested in computational intelligence. Its thorough coverage, supplementary material, classroom-tested examples, useful insights, detailed discussion, and latest developments make it an essential tool for anyone seeking to advance their knowledge and expertise in this field.

Weight: 991g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030422295
Edition number: 3rd ed. 2022