Evolutionary Computation (EC) approaches are inspired by nature and solve optimization
problems in a stochastic manner. They can offer a reliable and effective approach to address …

Many machine learning tasks involve solving complex optimization problems, such as
working on non-differentiable, non-continuous, and non-unique objective functions; in some …

Benchmarking is a cornerstone in the analysis and development of computational methods,
especially in the field of evolutionary computation, where theoretical analysis of the …

Evolutionary computation uses computational models of evolutionary processes as key
elements in the design and implementation of computerbased problem solving systems. In …

Rapid advances in evolutionary computation have opened up a world of applications-a
world rapidly growing and evolving. Decision making, neural networks, pattern recognition …

Evolutionary computation has started to receive significant attention during the last decade,
although the origins can be traced back to the late 1950's. This article surveys the history as …

Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

This Third Edition provides the latest tools and techniques that enable computers to learn
The Third Edition of this internationally acclaimed publication provides the latest theory and …

Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …

Experimental studies are prevalent in Evolutionary Computation (EC), and concerns about
the reproducibility and replicability of such studies have increased in recent times, reflecting …