Articulando las actividades de conjeturar y probar de los matemáticos profesionales desde la teoría de Peirce

“La formulación de conjeturas y el desarrollo de pruebas son dos aspectos fundamentales del trabajo de un matemático profesional” (Alibert y Thomas, 1991, p. 215). La investigación que estamos llevando a cabo pretende proponer un modelo, desde la educación matemática, que describa y explique cómo los matemáticos profesionales desarrollan las actividades de conjeturar y probar. Concretamente, y debido al carácter sociocultural de la investigación en matemáticas, los participantes considerados en este trabajo son investigadores en matemáticas que tienen al menos una publicación en “JCR science edition”

Comparación de la industria turística en potencias emergentes (Argentina y Brasil): de la rivalidad a la interdependencia

En los últimos años, además de los destinos maduros de Europa y América del Norte, hanirrumpido con fuerza nuevos subcontinentes como América del Sur. La industria turística deArgentina y Brasil ha evolucionado favorablemente, mostrando un considerable crecimientoy estabilidad económica que les ha convertido en potencias turísticas emergentes. En esteartículo se presenta, de manera comparada, la evolución del sector turístico en ambos países,identificando las principales causas que han influido en su desarrollo. El interés de estacomparación radica en que ambos países presentan importantes atractivos turísticos, fuertecrecimiento económico, grandes desequilibrios territoriales y altos niveles de inseguridad,unidos a una compleja interdependencia en cuanto a los flujos turísticos. Comprenderestas interrelaciones resulta vital para profundizar en los mecanismos de cooperación eintercambio, para permitir acabar definitivamente con los conflictos y rivalidades

An experimental study on evolutionary reactive behaviors for mobile robots navigation

Mobile robot's navigation and obstacle avoidance in an unknown and static environment is analyzed in this paper. From the guidance of position sensors, artificial neural network (ANN) based controllers settle the desired trajectory between current and a target point. Evolutionary algorithms were used to choose the best controller. This approach, known as Evolutionary Robotics (ER), commonly resorts to very simple ANN architectures. Although they include temporal processing, most of them do not consider the learned experience in the controller's evolution. Thus, the ER research presented in this article, focuses on the specification and testing of the ANN based controllers implemented when genetic mutations are performed from one generation to another. Discrete-Time Recurrent Neural Networks based controllers were tested, with two variants: plastic neural networks (PNN) and standard feedforward (FFNN) networks. Also the way in which evolution was performed was also analyzed. As a result, controlled mutation do not exhibit major advantages against over the non controlled one, showing that diversity is more powerful than controlled adaptation.Facultad de Informátic

An experimental study on evolutionary reactive behaviors for mobile robots navigation

Mobile robot's navigation and obstacle avoidance in an unknown and static environment is analyzed in this paper. From the guidance of position sensors, artificial neural network (ANN) based controllers settle the desired trajectory between current and a target point. Evolutionary algorithms were used to choose the best controller. This approach, known as Evolutionary Robotics (ER), commonly resorts to very simple ANN architectures. Although they include temporal processing, most of them do not consider the learned experience in the controller's evolution. Thus, the ER research presented in this article, focuses on the specification and testing of the ANN based controllers implemented when genetic mutations are performed from one generation to another. Discrete-Time Recurrent Neural Networks based controllers were tested, with two variants: plastic neural networks (PNN) and standard feedforward (FFNN) networks. Also the way in which evolution was performed was also analyzed. As a result, controlled mutation do not exhibit major advantages against over the non controlled one, showing that diversity is more powerful than controlled adaptation.Facultad de Informátic

Neuro-Controllers, scalability and adaptation

A Layered Evolution (LE) paradigm based method for the generation of a neuron-controller is developed and verified through simulations and experimentally. It is intended to solve scalability issues in systems with many behavioral modules. Each and every module is a genetically evolved neuro-controller specialized in performing a different task. The main goal is to reach a combination of different basic behavioral elements using different artificial neural-network paradigms concerning mobile robot navigation in an unknown environment. The obtained controller is evaluated over different scenarios in a structured environment, ranging from a detailed simulation model to a real experiment. Finally most important implies are shown through several focuses

Neuro-Controllers, scalability and adaptation

A Layered Evolution (LE) paradigm based method for the generation of a neuron-controller is developed and verified through simulations and experimentally. It is intended to solve scalability issues in systems with many behavioral modules. Each and every module is a genetically evolved neuro-controller specialized in performing a different task. The main goal is to reach a combination of different basic behavioral elements using different artificial neural-network paradigms concerning mobile robot navigation in an unknown environment. The obtained controller is evaluated over different scenarios in a structured environment, ranging from a detailed simulation model to a real experiment. Finally most important implies are shown through several focuses.Red de Universidades con Carreras en Informática (RedUNCI

Next Reaction Method for Solving Dynamic Macroeconomic Models: A Growth Regressions Simulation

277-280Recent studies apply the Monte Carlo method to try to solve multiple data problems for dynamic macroeconomic models such as measurement errors, residue correlation, and omitted variables. This paper evaluates the estimate of economic growth regressions from the Solow model by applying the Next Reaction Method, similar to the Monte Carlo kinetic methods. Our results indicate that with the said algorithm the estimation of these models improves since they increase the levels of precision of the existing models simulated with Monte Carlo, achieving faster the convergence of the coefficients of the variables reduces the possible measurement errors and the level of deviations. These results can be very useful in their application in dynamic macroeconomic models, which help the estimation challenges of policymakers and other related stakeholders