Patience as a Predictor for Environmental Attitudes

This paper aims to show the relationship between an individual’s value of patience and the degree to which they exhibit pro-environmental attitudes. My hypothesis is that country-wide patience has a strong impact on an individual’s attitudes towards protecting the environment. I present two methods to address this relationship, each method employs a different variable used to measure environmental attitudes. Given some discrepancies in the results from the first method, the second was the one utilized to reach the conclusion. The paper concludes that there is a positive and significant correlation between patience and environmental attitudes

Analytic and Learned Footstep Control for Robust Bipedal Walking

Bipedal walking is a complex, balance-critical whole-body motion with inherently unstable inverted pendulum-like dynamics. Strong disturbances must be quickly responded to by altering the walking motion and placing the next step in the right place at the right time. Unfortunately, the high number of degrees of freedom of the humanoid body makes the fast computation of well-placed steps a particularly challenging task. Sensor noise, imprecise actuation, and latency in the sensomotoric feedback loop impose further challenges when controlling real hardware. This dissertation addresses these challenges and describes a method of generating a robust walking motion for bipedal robots. Fast modification of footstep placement and timing allows agile control of the walking velocity and the absorption of strong disturbances. In a divide and conquer manner, the concepts of motion and balance are solved separately from each other, and consolidated in a way that a low-dimensional balance controller controls the timing and the footstep locations of a high-dimensional motion generator. Central pattern generated oscillatory motion signals are used for the synthesis of an open-loop stable walk on flat ground, which lacks the ability to respond to disturbances due to the absence of feedback. The Central Pattern Generator exhibits a low-dimensional parameter set to influence the timing and the landing coordinates of the swing foot. For balance control, a simple inverted pendulum-based physical model is used to represent the principal dynamics of walking. The model is robust to disturbances in a way that it returns to an ideal trajectory from a wide range of initial conditions by employing a combination of Zero Moment Point control, step timing, and foot placement strategies. The simulation of the model and its controller output are computed efficiently in closed form, supporting high-frequency balance control at the cost of an insignificant computational load. Additionally, the sagittal step size produced by the controller can be trained online during walking with a novel, gradient descent-based machine learning method. While the analytic controller forms the core of reliable walking, the trained sagittal step size complements the analytic controller in order to improve the overall walking performance. The balanced whole-body walking motion arises by using the footstep coordinates and the step timing predicted by the low-dimensional model as control input for the Central Pattern Generator. Real robot experiments are presented as evidence for disturbance-resistant, omnidirectional gait control, with arguably the strongest push-recovery capabilities to date

Dynamic Difficulty Adjustment

One of the challenges that a computer game developer faces when creating a new game is getting the difficulty right. Providing a game with an ability to automatically scale the difficulty depending on the current player would make the games more engaging over longer time. In this work we aim at a dynamic difficulty adjustment algorithm that can be used as a black box: universal, nonintrusive, and with guarantees on its performance. While there are a few commercial games that boast about having such a system, as well as a few published results on this topic, to the best of our knowledge none of them satisfy all three of these properties. On the way to our destination we first consider a game as an interaction between a player and her opponent. In this context, assuming their goals are mutually exclusive, difficulty adjustment consists of tuning the skill of the opponent to match the skill of the player. We propose a way to estimate the latter and adjust the former based on ranking the moves available to each player. Two sets of empirical experiments demonstrate the power, but also the limitations of this approach. Most importantly, the assumptions we make restrict the class of games it can be applied to. Looking for universality, we drop the constraints on the types of games we consider. We rely on the power of supervised learning and use the data collected from game testers to learn models of difficulty adjustment, as well as a mapping from game traces to models. Given a short game trace, the corresponding model tells the game what difficulty adjustment should be used. Using a self-developed game, we show that the predicted adjustments match players' preferences. The quality of the difficulty models depends on the quality of existing training data. The desire to dispense with the need for it leads us to the last approach. We propose a formalization of dynamic difficulty adjustment as a novel learning problem in the context of online learning and provide an algorithm to solve it, together with an upper bound on its performance. We show empirical results obtained in simulation and in two qualitatively different games with human participants. Due to its general nature, this algorithm can indeed be used as a black box for dynamic difficulty adjustment: It is applicable to any game with various difficulty states; it does not interfere with the player's experience; and it has a theoretical guarantee on how many mistakes it can possibly make

Effective parallelisation for machine learning

We present a novel parallelisation scheme that simplifies the adaptation of learning algorithms to growing amounts of data as well as growing needs for accurate and confident predictions in critical applications. In contrast to other parallelisation techniques, it can be applied to a broad class of learning algorithms without further mathematical derivations and without writing dedicated code, while at the same time maintaining theoretical performance guarantees. Moreover, our parallelisation scheme is able to reduce the runtime of many learning algorithms to polylogarithmic time on quasi-polynomially many processing units. This is a significant step towards a general answer to an open question [21] on efficient parallelisation of machine learning algorithms in the sense of Nick’s Class (NC). The cost of this parallelisation is in the form of a larger sample complexity. Our empirical study confirms the potential of our parallelisation scheme with fixed numbers of processors and instances in realistic application scenarios

Implementación de enlaces de banda ancha usando tecnología satelital VSAT HughesNet (DirecWay) en Ecuador

The following document describes the implementation process of a satellite link using HughesNet DirecWay technology. It is understood as a VSAT system a satellite link with antennas smaller than 2 or 3 meters in diameter, requiring the use of a geostationary satellite to communicate with other similar earth-stations. VSAT are considered an alternate solution for wired or radio communications for remote locations.En el presente documento se describe el proceso de implementación de enlaces satelitales utilizando la tecnología VSAT HughesNet DirecWay. Se entiende como sistema VSAT a aquel enlace satelital que posee antenas cuyo diámetro no sobrepasa los 2 o 3 metros, y que requiere de un satélite geoestacionario para comunicarse con otras estaciones de iguales características. Se considera a los sistemas VSAT como una alternativa a las soluciones cableadas o de radio para la comunicación con zonas aisladas

Regeneración urbana de la parroquia de San Antonio de Pichincha

San Antonio de Pichincha celebra sus tradicionales fiestas en el mes de Junio pero, de acuerdo a la Junta Parroquial, estas se celebran ya sea en las calles principales o en establecimientos que no pertenecen a la zona. Por otro lado para la educación hacen falta establecimientos donde se pueda incentivar el estudio y la cultura. Por estas razones se propone una edificación dedicada al estudio y la cultura con un amplio espacio para el desarrollo de sus distintas actividades