Evolutionary algorithms have been gaining increased attention the past few years because of their versatility and are being successfully applied in several different fields of study. We group under this heading a family of new computing techniques rooted in biological evolution that can be used for solving hard problems. In this chapter we present a survey of genetic algorithms and genetic programming, two important evolutionary techniques. We discuss their parallel implementations and some notable extensions, focusing on their potential applications in the field of evolvable hardware
Nowadays the possibilities of evolutionary algorithms are widely used in many optimization and class...
Evolutionary algorithms incorporate principles from biological population genetics to perform search...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence...
This paper presents a brief overview of the field of evolutionary computation. Three major research ...
Evolutionary algorithms (EAs) are stochastic optimization techniques based on the principles of natu...
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
Evolutionary computation has been widely used in computer science for decades. Even though it starte...
Abstract: Genetic programming (GP) is an automated method for creating a working computer program ...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Abstract. Nowadays the possibilities of evolutionary algorithms are widely used in many optimization...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
Evolutionary computing (EC) is an exciting development in Computer Science. It amounts to building, ...
Nowadays the possibilities of evolutionary algorithms are widely used in many optimization and class...
Evolutionary algorithms incorporate principles from biological population genetics to perform search...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence...
This paper presents a brief overview of the field of evolutionary computation. Three major research ...
Evolutionary algorithms (EAs) are stochastic optimization techniques based on the principles of natu...
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
Evolutionary computation has been widely used in computer science for decades. Even though it starte...
Abstract: Genetic programming (GP) is an automated method for creating a working computer program ...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
Abstract. Nowadays the possibilities of evolutionary algorithms are widely used in many optimization...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
Evolutionary computing (EC) is an exciting development in Computer Science. It amounts to building, ...
Nowadays the possibilities of evolutionary algorithms are widely used in many optimization and class...
Evolutionary algorithms incorporate principles from biological population genetics to perform search...
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration origin...