Entrepreneurship: a long way to go

Entrepreneurship education has emerged as one popular research domain in academic fields given its aim at enhancing and developing certain entrepreneurial qualities of undergraduates that change their state of behavior, even their entrepreneurial inclination and finally may result in the formation of new businesses as well as new job opportunities. This study attempts to investigate the Colombian student´s entrepreneurial qualities and the influence of entrepreneurial education during their studies.

Actitudes de los directivos en torno a la adopción del e-learning como herramienta de trabajo en las empresas

El desarrollo del presente documento constituye una investigación sobre las actitudes de los directivos frente a la adopción del e-learning como herramienta de trabajo en las organizaciones de Bogotá. Para ello se realizó una encuesta a 101 directivos, tomando como base el tipo de muestreo de conveniencia; esto con el objetivo de identificar sus actitudes frente al uso del e-learning y su influencia dentro de la organización. Como resultado se obtuvo que las actitudes de los directivos influencian en el uso de herramientas e-learning, así como también en las acciones que promueven su uso y en las actitudes de los empleados; por otro lado se identificó que las creencias relacionadas con la apropiación de herramientas e-learning y los factores facilitadores del uso de estas, influencian en las actitudes de los directivos. Lo anterior, corresponde a los análisis llevados a cabo a partir de los resultados contrastados con los estudios empíricos hallados y el marco teórico desarrollado.

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.