[EN] The use of simulation and reinforcement learning can be viewed as a flexible approach to aid managerial decision-making, particularly in the face of growing complexity in manufacturing and logistic systems. Efficient ...

[EN] The capacitated dispersion problem, which is a variant of the maximum diversity problem, aims to determine a set of elements within a network. These elements could symbolize, for instance, facilities in a supply chain ...

[ES] Este trabajo se enfoca en el entrenamiento de un agente robótico de navegación diferencial, utilizando técnicas de aprendizaje por refuerzo. El objetivo principal es capacitar al agente para realizar tareas de navegación ...

[ES] En el campo del aprendizaje por refuerzo se busca entrenar agentes inteligentes para que aprendan a tomar decisiones óptimas en situaciones complejas a través de la interacción con un ambiente. En este trabajo realizado ...

[EN] The aim of this master thesis is to study the state of art of reinforment learning, particularly those based on policy search methods and to apply such techniques to a 3DOFs inverted pendulum mechanism. The controller ...

Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performed in rather specific tasks such as ...

[ES] Con el presente trabajo se pretende llevar a cabo el desarrollo de controladores usando una arquitectura modular basada en software libre de código abierto. Para ello en la controladora se ejecutará el sistema operativo ...

[EN] In this paper, we describe a new trend analysis and forecasting method (Deflexor), which is intended to help inform decisions in almost any field of human social activity, including, for example, business, art and ...

[EN] Recently, many novel paradigms, concepts and technologies, which lay the foundation for the new revolution in manufacturing environments, have emerged and make it faster to address critical decisions today in supply ...

[EN] We consider a quasi-metric topological structure for the construction of a new reinforcement learning model in the framework of financial markets. It is based on a Lipschitz type extension of reward functions defined ...