The issue of controlling values of various parameters of an evolutionary algorithm is one of the most important and promising areas of research in evolutionary computation: It has a potential of adjusting the algorithm to the problem while solving the problem. In this paper we: 1) revise the terminology, which is unclear and confusing, thereby providing a classification of such control mechanis...

Car racing is a successful genre of videogames, as proved, for example, by the racing simulator saga, Gran Turismo. In this genre of games, players not only race but they are also involved in the process of setting up the car, assuming the role of a technician/mechanic/engineer. Generally, this configuration deals with a large set of parameters that range from the amount of fuel loaded into the...

The balance of exploration versus exploitation (EvE) is a key issue on evolutionary computation. In this paper we will investigate how an adaptive controller aimed to perform Operator Selection can be used to dynamically manage the EvE balance required by the search, showing that the search strategies determined by this control paradigm lead to an improvement of solution quality found by the ev...

Parameterized evolutionary algorithms (EAs) have been a standard part of the Evolutionary Computation community from its inception. The widespread use and applicability of EAs is due in part to the ability to adapt an EA to a particular problem-solving context by tuning its parameters. However, tuning EA parameters can itself be a challenging task since EA parameters interact in highly non-line...

Evolutionary computation techniques have been widely studied to automate the synthesis of behavioural control for robots. In online evolution, an evolutionary algorithm is executed on the robots themselves during task execution so as to continuously optimise the robot controllers. Online evolution provides numerous potential benefits, including enabling robots to modify their behaviour in respo...

Evolutionary computation is an area of computer science that uses ideas from biological evolution to solve computational problems.Many such problems require searching through a huge space of possibilities for solutions, such as among a vast number of possible hardware circuit layouts for a configuration that produces desired behavior, for a set of equations that will predict the ups and downs o...

| In this paper, we present an overview of the most important representatives of algorithms gleaned from natural evolution, so-called evolutionary algorithms. Evolution strategies, evolutionary programming, and genetic algorithms are summarized, with special emphasis on the principle of strategy parameter self-adaptation utilized by the rst two algorithms to learn their own strategy parameters ...

This position paper addresses the relevance of evolution ary computation for iterative approaches to inverse prob lems We focus on a set of six real world problems se lected from the areas of space dynamics materials science geophysics heat transfer oceanography and meteorology These problems are far from being trivial and their asso ciated direct models yield a wide structural diversity thus p...