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Ce document présente un point de vue synthétique sur plusieurs modèles et résultats essentiels de la psychologie cognitive. Il traite les thèmes de la mémoire, des représentations et des activités mentales opérant sur ces représentations. Il s'inscrit dans le courant du traitement de l'information dans une double perspective : symbolique et connexionniste.

Cognitive psychology --- Psychologie cognitive

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Investments --- Statistical methods. --- Criptomoneda --- Inversions --- Estadística matemàtica --- Estadística descriptiva --- Inferència estadística --- Matemàtica estadística --- Mètodes estadístics --- Estadística --- Anàlisi d'error (Matemàtica) --- Anàlisi de regressió --- Anàlisi de sèries temporals --- Anàlisi de variància --- Anàlisi multivariable --- Anàlisi seqüencial --- Astronomia estadística --- Correlació (Estadística) --- Dependència (Estadística) --- Estadística no paramètrica --- Estadística robusta --- Física estadística --- Mètode dels moments (Estadística) --- Models lineals (Estadística) --- Models no lineals (Estadística) --- Teoria de l'estimació --- Teoria de la predicció --- Tests d'hipòtesi (Estadística) --- Biometria --- Mostreig (Estadística) --- Inversions de capital --- Capital --- Accions (Borsa) --- Assignació d'actius --- Bons --- Capital de risc --- Inversions bancàries --- Inversions immobiliàries --- Inversions públiques --- Opcions (Finances) --- Rendibilitat --- Mercat de futurs --- Societats d'inversió --- Valors --- Estalvi --- Criptomonedes --- Moneda electrònica --- Bitcoin --- Contractes intel·ligents --- Investing --- Investment management --- Portfolio --- Finance --- Disinvestment --- Loans --- Saving and investment --- Speculation --- Criptomoneda.

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This Brief presents a study of SAX/GA, an algorithm to optimize market trading strategies, to understand how the sequential implementation of SAX/GA and genetic operators work to optimize possible solutions. This study is later used as the baseline for the development of parallel techniques capable of exploring the identified points of parallelism that simply focus on accelerating the heavy duty fitness function to a full GPU accelerated GA. .

Genetic algorithms. --- Parallel processing (Electronic computers) --- Pattern recognition systems. --- Engineering. --- Financial engineering. --- Economics, Mathematical. --- Computational intelligence. --- Computational Intelligence. --- Financial Engineering. --- Quantitative Finance. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Economics --- Mathematical economics --- Econometrics --- Mathematics --- Computational finance --- Engineering, Financial --- Finance --- Construction --- Industrial arts --- Technology --- Methodology --- High performance computing --- Multiprocessors --- Parallel programming (Computer science) --- Supercomputers --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Algorithms --- Combinatorial optimization --- Evolutionary computation --- Genetic programming (Computer science) --- Learning classifier systems --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Finance. --- Funding --- Funds --- Currency question --- Economics, Mathematical .

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This book presents a genetic algorithm that optimizes a grid template pattern detector to find the best point to trade in the SP 500. The pattern detector is based on a template using a grid of weights with a fixed size. The template takes in consideration not only the closing price but also the open, high, and low values of the price during the period under testing in contrast to the traditional methods of analysing only the closing price. Each cell of the grid encompasses a score, and these are optimized by an evolutionary genetic algorithm that takes genetic diversity into consideration through a speciation routine, giving time for each individual of the population to be optimized within its own niche. With this method, the system is able to present better results and improves the results compared with other template approaches. The tests considered real data from the stock market and against state-of-the-art solutions, namely the ones using a grid of weights which does not have a fixed size and non-speciated approaches. During the testing period, the presented solution had a return of 21.3% compared to 10.9% of the existing approaches. The use of speciation was able to increase the returns of some results as genetic diversity was taken into consideration.

Financial organisation --- Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- sociale interventies --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)