Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

On AUV control architecture

This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment

Atomic diffusion induced by stress relaxation in InGaAs/GaAs epitaxial layers

The origin of the microscopic inhomogeneities in InxGa1-xAs layers grown on GaAs by molecular beam epitaxy is analyzed through the optical absorption spectra near the band gap. It is seen that, for relaxed thick layers of about 2.8μm, composition inhomogeneities are responsible for the band edge smoothing into the whole compositional range (0.05layers strain inhomogeneities are dominant. This evolution in line with layer thickness is due to the atomic diffusion at the surface during growth, induced by the strain inhomogeneities that arise from stress relaxation. In consequence, the strain variations present in the layer are converted into composition variations during growth. This process is energetically favorable as it diminishes elastic energy. An additional support to this hypothesis is given by a clear proportionality between the magnitude of the composition variations and the mean strain

Evaluación de la competencia comunicativa académica en semi-presencialidad

En la E.U. de Magisterio de Donostia de la Universidad del País Vasco (UPV/EHU), este curso 2010/2011 ha comenzado la oferta semi-presencial para aquellos estudiantes que no pueden matricularse a todas las asignaturas de primer curso. Dentro de esta experiencia piloto se ha impartido la asignatura "Desarrollo de la competencia comunicativa I" en el Grado de Educación Primaria, centrada en la competencia comunicativa académica. El diseño de esta asignatura se ha apoyado en investigaciones relacionadas con el desarrollo de esta competencia en entornos virtuales y ha contado con actividades diversas que han permitido a los estudiantes su autoevaluación y también la coevaluación

Impact of chlorophenols and heavy metals on soil microbiota: their effects on activity and community composition, and resistant strains with potential for bioremetiation

Pollution by toxic compounds is one of the most relevant environmental damages to ecosystems produced by human activity and, therefore, it must be considered in environmental protection and restoration of contaminated sites. According to this purposes, the main goal of this doctoral thesis has been to analyse the impact of several chlorophenols and heavy metals on the microbial communities of two typical Mediterranean soils. The ecological risk concentrations of each pollutant, which have been determined according to respirometric activity and changes in the microbial community composition, and the factors that influence on their effective toxic concentrations (bioavailable pollutants) have been analysed in order to predict their potential impact on different soil ecosystems and provide scientific data for the regulation of the soil protection policies. Moreover, resistant microorganisms with pollutant removal capacities have been isolated from artificially contaminated soil microcosms and tested in axenic cultures, to infer their potential usefulness for bioremediation.