¿Pueden pensar las máquinas? Una evaluación del problema de la inteligencia artificial mediante el equilibrio refractivo

Revisión del problema de la filosofía de la Inteligencia Artificial a la vista del Equilibrio refractivo. La revisión del problema se lleva a cabo para mostrar como "¿pueden pensar las máquinas?" sólo se ha evaluado en los terminos humanos. El equilibrio refractivo se plantea como una herramienta para definir conceptos de tal modo que la experiencia y los preceptos se encuentren en equilibrio, para con él construir una definición de pensar que no esté limitada exclusivamente a "pensar tal y como lo hacen los humanos".

Las Jarretaderas, Nayarit, Mexico: a Social Interstice in Touristic Zona Metropolitana of Sun and Sand

The objective of the present article is to illustrate the social interstice (Las Jarretaderas) existing between the municipalities Bahía de Banderas, Nayarit and Puerto Vallarta, Jalisco. The researched community is an outstanding case-study providing an in-depth analysis of a number of social process mostly related to the chiapaneca migration. The text is divided into two sections. The first one deals with the urbanization process of the metropolitan area of Puerto Vallarta. The second and longer section defines the concept of social interstice and explains how the researched locality falls under under that previously-defined concept according to the processes analyzed.

An artificial economy based on reinforcement learning and agent based modeling

In this paper, we employ techniques from artificial intelligence such as reinforcement learning and agent based modeling as building blocks of a computational model for an economy based on conventions. First we model the interaction among firms in the private sector. These firms behave in an information environment based on conventions, meaning that a firm is likely to behave as its neighbors if it observes that their actions lead to a good pay off. On the other hand, we propose the use of reinforcement learning as a computational model for the role of the government in the economy, as the agent that determines the fiscal policy, and whose objective is to maximize the growth of the economy. We present the implementation of a simulator of the proposed model based on SWARM, that employs the SARSA(λ) algorithm combined with a multilayer perceptron as the function approximation for the action value function.