Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians

This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications

A high-level perception architecture: real-time visual navigation for autonomous robots in structured environments

This thesis describes the design and implementation of a mobile robot which is able to perform a structural interpretation of indoor environments, using only visual and proprioceptive sensory information. The desired behaviour is real-time navigation based on this interpretation, instead of a reactive approach. The design is guided by a predictive criterion: the system must anticipate the consequences of its actions, showing a certain predictive understanding of the scene in which it moves.Facultad de Informátic

A high-level perception architecture: real-time visual navigation for autonomous robots in structured environments

This thesis describes the design and implementation of a mobile robot which is able to perform a structural interpretation of indoor environments, using only visual and proprioceptive sensory information. The desired behaviour is real-time navigation based on this interpretation, instead of a reactive approach. The design is guided by a predictive criterion: the system must anticipate the consequences of its actions, showing a certain predictive understanding of the scene in which it moves.Facultad de Informátic

School bullying: Empathy among perpetrators and victims

This study analyses the relationship between empathy and school bullying, taking both perpetrators and victims into consideration. The study sample comprised 840 students, 423 of which were female (50.36%), aged an average of 14.28 years. The instruments used were an ad hoc questionnaire for socioeconomic variables and bullying behaviour, an empathy questionnaire, and a personality questionnaire. Victims yielded higher scores in terms of empathic concern, while both groups, aggressors and victims, yielded similar results in terms of cognitive and affective empathy. Concerning the correlation between these variables and personality, anxiety was found to be correlated with affective empathy and empathetic concern in both groups. A correlation between cognitive empathy and impulsiveness and activity was also found in both groups. Remarkably, aggression and cognitive empathy were found to be correlated, but only among victims. Finally, experiences with classmates, anxiety, sincerity, and aggression were found to act as predictors of school bullying, while gender and aggression factors were found to act as predictors among perpetrators, but to a lesser extent, which suggests that other factors must be in place for bullying behaviour to occur. The results suggest that, although empathy levels are different in both groups, they cannot act as a predictor of bullying, especially concerning perpetrators