Evolutionary Computation: Fundamentals and Applications

The term "evolutionary computation" refers to both a subfield of artificial intelligence and soft computing in the field of computer science that studies various optimization algorithms and a family of algorithms for global optimization that are inspired by biological evolution. They belong to a family of problem solvers known as population-based trial and error problem solvers, and they either have a metaheuristic or stochastic optimization flavor.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Evolutionary computation

Chapter 2: Differential evolution

Chapter 3: Dual-phase evolution

Chapter 4: Evolutionary algorithm

Chapter 5: Evolutionary programming

Chapter 6: Neuroevolution

Chapter 7: Evolutionary robotics

Chapter 8: Grammatical evolution

Chapter 9: Human-based evolutionary computation

Chapter 10: Interactive evolutionary computation

(II) Answering the public top questions about evolutionary computation.

(III) Real world examples for the usage of evolutionary computation in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of evolutionary computation' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of evolutionary computation.