SABACO: Extensiones a los Algoritmos de Optimización basados en Colonias de Hormigas para la Toma de Decisiones Influenciada por Emociones y el Aprendizaje de Secuencias Contextuales en Ambientes Inteligentes

En el trabajo que presentamos en esta tesis hacemos inicialmente una revisión de cómo ha ido evolucionando la interacción hombre máquina en el contexto de la computación, desde los primeros y escasos computadores hasta el momento actual, en el que los avances tecnológicos han permitido que, en muchos de los escenarios en los que se desarrolla nuestra vida diaria, estemos rodeados de diversos dispositivos electrónicos con los que interactuamos para hacer uso de alguno de los servicios que ofrecen. Veremos cómo esta difusión tecnológica ha introducido los sistemas de información en ámbitos más allá del contexto del trabajo, como la educación o el hogar, haciendo necesario que se tenga en cuenta en el diseño de los sistemas no sólo la funcionalidad o facilidad de uso sino también otros factores como la experiencia de uso o las emociones que siente una persona al interactuar con el sistema. Además, ha dado lugar a la aparición de los conocidos como ambientes inteligentes, en los que son los sistemas presentes en el entorno los que deben adaptarse al usuario y al contexto en el que se encuentra, adaptación que, dados los nuevos contextos en los tiene lugar la interacción con el usuario, plantea algunos retos. En particular, en el presente trabajo identificamos dos factores clave que los ambientes inteligentes deben tener en cuenta para tomar las decisiones y llevar a cabo las acciones adecuadas para conseguir una mejor adaptación al usuario y al contexto. Estos factores son la influencia de las emociones en la interacción y la utilización de la información contextual histórica. Por ello hacemos una revisión tanto de las propuestas de sistemas de decisión influenciados por emociones existentes en el área de la computación afectiva, como de las propuestas de sistemas sensibles al contexto, mostrando propuestas basadas en sistemas multiagente, redes neuronales, modelos ocultos de Markov, e introduciendo las técnicas metaheurísticas. Recientemente parece haber un sentimiento en la comunidad investigadora sobre la necesidad de aproximaciones híbridas para resolver problemas reales, no existe por desgracia una base sistemática que describa de forma rigurosa como proceder para combinar las distintas aproximaciones existentes.Mocholí Agües, JA. (2011). SABACO: Extensiones a los Algoritmos de Optimización basados en Colonias de Hormigas para la Toma de Decisiones Influenciada por Emociones y el Aprendizaje de Secuencias Contextuales en Ambientes Inteligentes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11225Palanci

Artificial Intelligence Through the Eyes of the Public

Artificial Intelligence is becoming a popular field in computer science. In this report we explored its history, major accomplishments and the visions of its creators. We looked at how Artificial Intelligence experts influence reporting and engineered a survey to gauge public opinion. We also examined expert predictions concerning the future of the field as well as media coverage of its recent accomplishments. These results were then used to explore the links between expert opinion, public opinion and media coverage

Recent Trends in Computational Intelligence

Traditional models struggle to cope with complexity, noise, and the existence of a changing environment, while Computational Intelligence (CI) offers solutions to complicated problems as well as reverse problems. The main feature of CI is adaptability, spanning the fields of machine learning and computational neuroscience. CI also comprises biologically-inspired technologies such as the intellect of swarm as part of evolutionary computation and encompassing wider areas such as image processing, data collection, and natural language processing. This book aims to discuss the usage of CI for optimal solving of various applications proving its wide reach and relevance. Bounding of optimization methods and data mining strategies make a strong and reliable prediction tool for handling real-life applications

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

Assuming Data Integrity and Empirical Evidence to The Contrary

Background: Not all respondents to surveys apply their minds or understand the posed questions, and as such provide answers which lack coherence, and this threatens the integrity of the research. Casual inspection and limited research of the 10-item Big Five Inventory (BFI-10), included in the dataset of the World Values Survey (WVS), suggested that random responses may be common. Objective: To specify the percentage of cases in the BRI-10 which include incoherent or contradictory responses and to test the extent to which the removal of these cases will improve the quality of the dataset. Method: The WVS data on the BFI-10, measuring the Big Five Personality (B5P), in South Africa (N=3 531), was used. Incoherent or contradictory responses were removed. Then the cases from the cleaned-up dataset were analysed for their theoretical validity. Results: Only 1 612 (45.7%) cases were identified as not including incoherent or contradictory responses. The cleaned-up data did not mirror the B5P- structure, as was envisaged. The test for common method bias was negative. Conclusion: In most cases the responses were incoherent. Cleaning up the data did not improve the psychometric properties of the BFI-10. This raises concerns about the quality of the WVS data, the BFI-10, and the universality of B5P-theory. Given these results, it would be unwise to use the BFI-10 in South Africa. Researchers are alerted to do a proper assessment of the psychometric properties of instruments before they use it, particularly in a cross-cultural setting