Swarm Intelligence and Evolutionary Computation: Theory, Advances and Applications in Machine Learning and Deep Learning

The aim of this book is to present and analyse theoretical advances and also emerging practical applications of swarm and evolutionary intelligence. It comprises nine chapters. Chapter 1 provides a theoretical introduction of the computational optimization techniques regarding the gradient-based methods such as steepest descent, conjugate gradient, newton and quasi-Newton methods and also the non-gradient methods such as genetic algorithm and swarm intelligence algorithms. Chapter 2, discus...