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This book presents the fundamentals of Swarm Intelligence, from classic algorithms to emerging techniques. It presents comprehensive theoretical foundations and examples using the main Computational Intelligence methods in programming languages ​​such as Python, Java and MATLAB. Real-world applications are also presented in areas as diverse as Medicine, Biology and industrial applications.
Symbolic Artificial Intelligence is based on modeling the solution of problems such as search and optimization. Initially marked by statistical methods and Mathematical Programming, Symbolic Artificial Intelligence takes an evolutionary leap with meta-heuristics. From the inspiration in nature, with the advent of the Particle Swarm Optimization algorithm, Swarm Intelligence emerges. According to this paradigm, Artificial Intelligence is now understood as collective intelligence: intelligent agents capable of simple operations are able to solve complex problems through collective mechanisms of population evolution and with the modeling of adequate social relations, which promote both the individual as well as the collective. Ants, bees, birds, wolves and other collective animals, such as humans themselves, are a constant source of inspiration for the construction and improvement of new collective intelligence algorithms. Through Swarm Intelligence, it is possible not only to optimize well-established solutions according to certain quality parameters, but also to create new solutions for a world that increasingly depends on Artificial Intelligence to solve old and new problems in society.
In this book, “Swarm Intelligence: New Trends and Applications”, we aim to present the principles and advances of Swarm Intelligence and applications on industry and digital health. The book consists of two parts: the first four chapters are dedicated to the fundamentals of Swarm Intelligence algorithms and theoretical advances from the fifth chapter to the last one, we present several real-world applications, especially regarding machine learning on digital health.
This book is intended for academics, graduate and postgraduate students in Computer Science, Computer Engineering, Biomedical Engineering, Medicine, Biomedicine and everyone interested in understanding the fundamental basis of Swarm Intelligence, both algorithmic and theoretically, presenting the theoretical bases, new trends, emerging algorithms, examples, and real-world applications. This book is intended to be available to undergraduate and postgraduate students, academics and independent data scientists