Supervised learning problems can be faced by using a wide variety of approaches
supported in machine learning. In recent years there has been an increasing interest in …

Genetic Improvement (GI) focuses on the development of evolutionary methods to automate
software engineering tasks, such as performance improvement or software bugs removal …

The selection mechanism plays a very important role in the performance of Genetic
Programming (GP). Among several selection techniques, tournament selection is often …

Featured Application Automatic packaging of fruit grading production line. Abstract
Automated packing is urgently needed in apple production. This paper proposes an …

Abstract Error-Correcting Output Codes (ECOC) is widely used in the field of multiclass
classification. As an optimal codematrix is key to the performance of an ECOC algorithm, this …

Genetic Improvement (GI) performs a search at the level of source code to find the best
variant of a baseline system that improves non-functional properties while maintaining …

A Novel Approach For Search-Based Program Repair Page 1 36 IEEE SOFTWARE | PUBLISHED
BY THE IEEE COMPUTER SOCIETY 0740-7459/21©2021IEEE FOCUS: AUTOMATIC …

This study examined the relative performance of Deep Reinforcement Learning compared to
a neuroevolution algorithm called NEAT when used to train AIs in a discrete game …

The design of efficient electroencephalogram (EEG) classification systems for the detection
of mental states is still an open problem. Such systems can be used to provide assistance to …

A topology synthesis method is introduced using genetic algorithms (GA) based on novelty
search (NS). NS is an emerging meta-heuristic, that guides the search based on the novelty …