Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, the action selection problem is typically associated with intelligent agents and animats – artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behav...

the use of third-party logistics (3pl) providers is regarded as new strategy in logistics management. the relationships by considering 3pl are sometimes more complicated than any classical logistics supplier relationships. these relationships have taken into account as a well-known way to highlight organizations' flexibilities to regard rapidly uncertain market conditions, follow core competenc...

Faced with the dynamic demands of a changing market, companies are facing fierce competition, which forces them to consider more and more new approaches to improve quality, reduce costs, produce on time, control their risks and remain successful in the face of any disruption. It is clear that the choice of appropriate suppliers is one of the key factors in increasing the competitiveness of comp...

We describe in this article an in vitro system for the selection of restriction endonucleases using artificial cells. The artificial cells are generated in the form of a water-in-oil emulsion by in vitro compartmentalization. Each aqueous compartment contains a reconstituted transcription/translation mix along with the dispersed DNA templates. In the compartments containing endonuclease genes, ...

p2x 7 antagonist activity for a set of 49 molecules of the p2x 7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. the activity of these compounds was estimated by means of combination of principal component analysis (pca), as a well-known data reduction method, genetic algorithm (ga), as a variable selection technique, ...

The observed genetic gain (DeltaP) from selection in a finite population is the possible expected genetic gain E(Delta G) minus the difference in inbreeding depression effects in the selected and control lines. The inbreeding depression can be avoided by crossing the control and selected male symbol and female symbol parents to unrelated mates and summing the observed gains. The possible expect...

Artificial selection has been practiced by humans since the dawn of agriculture, but only recently have evolutionary ecologists turned to this tool to understand nature. To perform artificial selection, the phenotypic trait of interest is measured on a population, and the individuals with the most extreme phenotypic values are bred to produce the next generation. The change in the mean of the s...

Machine learning is useful for building robust learning models, and it is based on a set of features that identify a state of an object. Unfortunately, some data sets may contain a large number of features making, in some cases, the learning process time consuming and the generalization capability of machine learning poor. To make a data set easy to learn and understand, it is typically recomme...

Most living organisms exhibit extremely sophisticated learning and processing abilities that allow them to survive and proliferate generation after generation in their dynamic and competitive environments. For this reason, nature has always served as inspiration for several scientific and technological developments. This area of research is often referred to as Biologically Inspired Computing. ...

In this paper, we examine the clonal selection algorithm CLONALG and the suggestion that it is suitable for pattern recognition. CLONALG is tested over a series of binary character recognition tasks and its performance compared to a set of basic binary matching algorithms. A number of enhancements are made to the algorithm to improve its performance and the classification tests are repeated. Re...