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Ce document regroupe les codes TIKZ des figures utilisées pour le cours "TRANSFERTS THERMIQUES" situé à la page http://femto-physique.fr/physique_statistique/phystat_C5.php

Installation instructions for XAMPP

Template za izvještaje za studente Elektretehničkog fakulteta u Sarajevu

Modelo de artigo de periódico da PUC Minas proposto pelo professor Hugo de Paula da PUC MG - Unidade São Gabriel

Since the conception of the Quantum Computer (QC), their potential for greater magnitudes in speed of processing calculations has been realised by the vast majority of interested parties. This has led to a recent push in research and development in creating a stable QC which can perform quantum algorithms. To aid the creation of a stable and highly available quantum computer, simulators have been developed as a tool to as the thought processes. This report discusses details of a project that aims to investigate around the subject area, and produce an application to allow users to simulate quantum algorithms on a QC.

Ce document regroupe les codes TIKZ des figures utilisées pour le cours "DYNAMIQUE DES FUIDES PARFAITS" situé à la page http://femto-physique.fr/mecanique_des_fluides/mecaflu_C2.php

Poster based on Dreuw & Deselaer's Poster LaTeX Template (http://www-i6.informatik.rwth-aachen.de/~dreuw/latexbeamerposter.php) and downloaded from http://www.LaTeXTemplates.com.

Этот шаблон документа разработан в 2014 году Данилом Фёдоровых (danil@fedorovykh.ru) для использования в курсе «Документы и презентации в \LaTeX», записанном НИУ ВШЭ для Coursera.org: http://coursera.org/course/latex. Исходная версия шаблона — https://www.writelatex.com/coursera/latex/4.2

Although individual ants have an extremely basic intelligence, and are completely incapable of surviving on their own, colonies of ants can develop remarkably sophisticated and biologically successful behavior. This paper discusses a set of experiments which attempt to simulate one of these behaviors, namely the ability of ants to place pheromones as a way of communication. These experiments involved a variety of different environments, and tested two varieties of the genetic algorithm NEAT: the standard offline version, and its online counterpart rtNEAT. Since the experimental environment did not seem to offer any benefit to continuous learning, we had expected NEAT and rtNEAT to have roughly similar learning curves. However, our results directly contradict this hypothesis, showing much more succesful learning with rtNEAT than with standard NEAT.