Within the optimization community, the question of how to generate new optimization
problems has been gaining traction in recent years. Within topics such as instance space …

Dimensionality reduction (DR) is an important technique for data exploration and knowledge
discovery. However, most of the main DR methods are either linear (eg, PCA), do not …

Automatic programming (AP) is one of the most attractive branches of artificial intelligence
because it provides effective solutions to problems with limited knowledge in many different …

Denoising autoencoder genetic programming (DAE-GP) is a novel neural network-based
estimation of distribution genetic programming approach that uses denoising autoencoder …

Denoising autoencoder genetic programming (DAE-GP) is an estimation of distribution
genetic programming (EDA-GP) algorithm. It uses denoising autoencoder long short-term …

Abstract Emerging Proliferated Low Earth Orbit (P-LEO) constellations may be susceptible to
attacks launched by malevolent actors capable of compromising orbiting satellites. We …

A good initial population generation method is of necessity to improve the performance of
evolutionary multiobjective optimization (EMO) algorithms. However, until now only a few …

Human code is different from code generated by program search. We investigate if
properties from human-generated code can guide program search to improve the qualities …

The initial population in evolutionary algorithms (EAs) should form a representative sample
of all possible solutions (the search space). While large populations accurately approximate …

Estimation of distribution genetic programming (EDA-GP) replaces the standard variation
operations of genetic programming (GP) by learning and sampling from a probabilistic …