¿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".

International Law as a Source of Constitutional Law

This article has the purpose to prove that the Customary International Law and the Conventional International Law are sources of Constitutional Law. First, it analyses the matter of the relations between International Law and National or Domestic law according with the theories dualism and monist and international decisions. Then, it studies the reception and the hierarchy of International Customary and Conventional Law to Domestic Law including Constitution. This matter has been studied according with several Constitutions and the international doctrine. Then, it considers the constitutional regulations about international law in the Constitution of the Republic of Colombia. The general conclusion is that International Law is incorporated in domestic law according with the Constitution of each country. But every state has the duty to carry out in good faith its obligations arising from treaties and other sources of International Law, and it may not invoke provisions in its Constitutions or its Laws as an excuse for failure to perform this duty. Accordingly, state practice and decided cases have established this provision, and the same rule is established in articles 27 and 46 of the Vienna Convention on Law of Treaties of 1969.

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.