It is our pleasure to introduce this special issue on multitask evolutionary computation (MTEC), focusing novel methodologies and applications of algorithms (EAs) crafted perform multiple search optimization tasks jointly. EAs are population-based methods inspired by principles natural evolution that have provided a gradient-free path solving complex learning problems. However, unlike the world...

In practical system identification, process optimization and controller design, it is often desirable to simultaneously handle several objectives and constraints. In some cases, these objectives and constraints are non-commensurable and they are not explicitly/mathematically available. This paper proposes a new subjective optimization method based on interactive evolutionary computation (IEC) t...

In this paper, we describe influence of viewpoints of observation in an interactive evolutionary robotics system. We have been proposed a behavior learning system ICS (Interactive Classifier System) using interactive evolutionary computation. In this system, a mobile robot is able to quickly learn rules by direct teaching of a human operator. ICS is a novel evolutionary robotics approach using ...

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the prop...

This paper introduces an interactive system called GraphCuisine that lets users steer an Evolutionary Algorithm (EA) to create random graphs that match user-specified measures. Generating random graphs with particular characteristics is crucial for evaluating graph algorithms, layouts and visualization techniques. Current random graph generators provide limited control of the final characterist...