Incrementar la presencia en entornos virtuales en primera persona a través de interfaces auditivas: un acercamiento analítico al sonido y la música adaptativos

Tesis de la Universidad Complutense de Madrid, Facultad de Informática, leída el 25-11-2019The popularisation of virtual reality devices has brought with it an increased need of telepresence and player immersion in video games. This goals are often pursued through more realistic computer graphics and sound; however, invasive graphical user interfaces are still present in industry standard products for VR, even though previous research has advised against them in order to reach better results in immersion. Non-visual, multimodal communication channels are explored throughout this thesis as a means of reducing the amount of graphical elements needed in head-up displays while increasing telepresence. Thus, the main goals of this research are to find the optimal channels that allow for semantic communication without recurring to visual interfaces, while reducing the general number of extra-diegetic elements in a video game, and to develop a total of six software applications in order to validate the obtained knowledge in real-life scenarios. The central piece of software produced as a result of this process is called LitSens, and consists of an adaptive music generator which takes human emotions as inputs...La popularización de los dispositivos de realidad virtual ha traído consigo una mayor necesidad de presencia e inmersión para los jugadores de videojuegos. Habitualmentese intenta cumplir con dicha necesidad a través de gráficos y sonido por ordenador más realistas; no obstante, las interfaces gráficas de usuario muy invasivas aún son un estándar en la industria del videojuego de RV, incluso si se tiene en cuenta que varias investigaciones previas a la redacción de este texto recomiendan no utilizarlas para conseguir un resultado más inmersivo. A lo largo de esta tesis, varios canales de comunicación multimodales y no visuales son explorados con el fin de reducir la cantidad de elementos gráficos extradiegéticos necesarios en las capas de las interfaces gráficas de usuario destinadas a la representación de datos, todo ello mientras se logra un aumento de la sensación de presencia. Por tanto, los principales objetivos de esta investigación son encontrar los canales óptimos para efectuar comunicación semántica sin recurrir a interfaces visuales —a la vez que se reduce el número de elementos extradiegéticos en un videojuego— y desarrollar un total de seis aplicaciones con el objetivo de validar todo el conocimiento obtenido mediante prototipos similares a videojuegos comerciales. De todos ellos, el más importante es LitSens: un generador de música adaptativa que toma como entradas emociones humanas...Fac. de InformáticaTRUEunpu

Five Factor Model of Personality and Structure of Psychopathological Symptoms in Adolescents

This study aims to explore the factorial structure of the most prevalent psychopathological symptoms in adolescence, and to explore the associations between the resulting psychopathological factors with both the Five-Factor Model of personality and the General Factor of Personality (GFP). A sample of 835 adolescents (M = 14.35, SD = 1.58; 49% girls) completed personality and psychopathology self-reports. The confirmatory factor analyses showed that a bifactor model of psychopathology, which included a general psychopathological factor (p factor) and specific factors (i.e., internalizing, externalizing, and hyperactivity and attention problems), better fitted the data than other competing models. The main associations found in the regression analyses were: neuroticism and introversion with the internalizing factor; low agreeableness with the externalizing factor; low conscientiousness with the hyperactivity and attention problems score; high neuroticism, low conscientiousness and low agreeableness with the p factor. Last, the GFP and p factor were substantially related, with β coefficients between 0.42 and 0.49 (p < .001). This study suggests that a bifactor model adequately depicts the psychopathology structure in adolescence. This structure was supported by differential associations of personality traits with each resulting factor

Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art

Safe learning and optimization deals with learning and optimization problems that avoid, as much as possible, the evaluation of non-safe input points, which are solutions, policies, or strategies that cause an irrecoverable loss (e.g., breakage of a machine or equipment, or life threat). Although a comprehensive survey of safe reinforcement learning algorithms was published in 2015, a number of new algorithms have been proposed thereafter, and related works in active learning and in optimization were not considered. This paper reviews those algorithms from a number of domains including reinforcement learning, Gaussian process regression and classification, evolutionary algorithms, and active learning. We provide the fundamental concepts on which the reviewed algorithms are based and a characterization of the individual algorithms. We conclude by explaining how the algorithms are connected and suggestions for future research.Comment: The final authenticated publication was made In: Heintz F., Milano M., O'Sullivan B. (eds) Trustworthy AI - Integrating Learning, Optimization and Reasoning. TAILOR 2020. Lecture Notes in Computer Science, vol 12641. Springer, Cham. The final authenticated publication is available online at \<https://doi.org/10.1007/978-3-030-73959-1_12

Multi-Objective Archiving

Most multi-objective optimisation algorithms maintain an archive explicitly or implicitly during their search. Such an archive can be solely used to store high-quality solutions presented to the decision maker, but in many cases may participate in the search process (e.g., as the population in evolutionary computation). Over the last two decades, archiving, the process of comparing new solutions with previous ones and deciding how to update the archive/population, stands as an important issue in evolutionary multi-objective optimisation (EMO). This is evidenced by constant efforts from the community on developing various effective archiving methods, ranging from conventional Pareto-based methods to more recent indicator-based and decomposition-based ones. However, the focus of these efforts is on empirical performance comparison in terms of specific quality indicators; there is lack of systematic study of archiving methods from a general theoretical perspective. In this paper, we attempt to conduct a systematic overview of multi-objective archiving, in the hope of paving the way to understand archiving algorithms from a holistic perspective of theory and practice, and more importantly providing a guidance on how to design theoretically desirable and practically useful archiving algorithms. In doing so, we also present that archiving algorithms based on weakly Pareto compliant indicators (e.g., epsilon-indicator), as long as designed properly, can achieve the same theoretical desirables as archivers based on Pareto compliant indicators (e.g., hypervolume indicator). Such desirables include the property limit-optimal, the limit form of the possible optimal property that a bounded archiving algorithm can have with respect to the most general form of superiority between solution sets.Comment: 21 pages, 4 figures, journa

A Study of Scalarisation Techniques for Multi-Objective QUBO Solving

In recent years, there has been significant research interest in solving Quadratic Unconstrained Binary Optimisation (QUBO) problems. Physics-inspired optimisation algorithms have been proposed for deriving optimal or sub-optimal solutions to QUBOs. These methods are particularly attractive within the context of using specialised hardware, such as quantum computers, application specific CMOS and other high performance computing resources for solving optimisation problems. These solvers are then applied to QUBO formulations of combinatorial optimisation problems. Quantum and quantum-inspired optimisation algorithms have shown promising performance when applied to academic benchmarks as well as real-world problems. However, QUBO solvers are single objective solvers. To make them more efficient at solving problems with multiple objectives, a decision on how to convert such multi-objective problems to single-objective problems need to be made. In this study, we compare methods of deriving scalarisation weights when combining two objectives of the cardinality constrained mean-variance portfolio optimisation problem into one. We show significant performance improvement (measured in terms of hypervolume) when using a method that iteratively fills the largest space in the Pareto front compared to a n\"aive approach using uniformly generated weights