On the enigmatic scent glands of dyspnoan harvestmen (Arachnida, Opiliones): first evidence for the production of volatile secretions

La utilización en encuestas de preguntas con tarjetas de respuesta está totalmente aceptada por la comunidad investigadora. Esto supone una carga de trabajo “extra” en la tarea del entrevistador, lo que explica que en ocasiones no se utilicen correctamente. Pese a esta situación, hay muy poca literatura sobre la influencia de las tarjetas en las respuestas del entrevistado. El objetivo de este trabajo es profundizar en los efectos que la utilización de tarjetas tiene en la calidad de las respuestas del cuestionario, partiendo de la hipótesis que considera que las tarjetas —pese a complicar la tarea del encuestador— suponen importantes mejoras en la administración del cuestionario. Utilizaremos para ello un estudio del Centro de Investigaciones Sociológicas con 23 preguntas de tarjeta, comparando las respuestas de los entrevistados que utilizaron las tarjetas con aquellos que no las emplearon.Using “response cards” in question surveys is unanimously approved by the research community. The fact that this represents an extra workload for the interviewer’s task explains why they sometimes are not used correctly. Despite this situation there is a paucity of literature on the influence of the response card on the respondent’s answers. The aim of this study is to deepen the analysis of how using these cards affect the quality of the survey’s responses. To do so, we start from the assumption that the cards —while complicating the interviewer’s task, result in significant improvements in the survey’s administration. For this purpose we will use a study with 23 card questions (question cards) by the Centro de Investigaciones Sociológicas, (the Spanish Centre for Sociological Research), and we will compare the answers of respondents that used cards with those who did not

Reinforcement Learning for StarCraft II

Trabajo Fin de Grado en Desarrollo de Videojuegos, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021En este Trabajo Fin de Grado se estudian distintas técnicas de aprendizaje por refuerzo, una rama del aprendizaje automatico que ha demostrado en los últimos años ser una de las opciones mas populares dentro de este ámbito. DeepMind ha aplicado algoritmos de aprendizaje por refuerzo en distintos videojuegos, poniendo de relieve la utilidad de estas aplicaciones para contribuir al avance de la investigación en el campo del aprendizaje automático. En este marco, la finalidad de este trabajo es la aplicación de técnicas de aprendizaje por refuerzo en distintos entornos del videojuego StarCraft II. Las características de este videojuego, en concreto el hecho de que incluye tomas de decisiones a distintos niveles con información parcial del estado del entorno, suponen grandes ventajas a la hora de aplicar técnicas de aprendizaje automático respecto a otros videojuegos. Tras profundizar en el estudio de los algoritmos de aprendizaje por refuerzo QLearning y Deep Q-Learning con objeto de entender su funcionamiento correctamente, ambos algoritmos se han implementado en minijuegos de StarCraft II. Esta aplicación ha consistido en el desarrollo de jugadores automáticos que aprenden varios objetivos enfocados a la toma de decisiones a distintos niveles en videojuegos RTS. Para ello,se ha realizado un estudio sobre las estrategias habituales en estos videojuegos y se ha implementado una arquitectura reutilizable que permite intercambiar los distintos agentes y entornos de manera sencilla. Finalmente, se analizan los resultados obtenidos en los diferentes experimentos realizados y se presentan las conclusiones extraídas a partir de dichos resultados.In this Bachelor’s Degree Final Proyect, different reinforcement learning techniques are studied, a branch of machine learning that has proven in recent years to be one of the most popular options in this field. DeepMind has applied reinforcement learning algorithms in different videogames, highlighting the usefulness of these applications to contribute to the advancement of research in the field of machine learning. In this framework, the purpose of this work is the application of reinforcement learning techniques in different environments of the StarCraft II videogame. The characteristics of this video game, specifically the fact that it includes decision-making at different levels with partial information about the state of the environment, represent great advantages when applying machine learning techniques compared to other videogames. After delving into the study of Q-Learning and Deep Q-Learning reinforcement learning algorithms in order to correctly understand how they work, both algorithms have been implemented in StarCraft II minigames. This application has consisted of the development of automatic players that learn various objectives focused on decision-making at different levels in RTS video games. To do this, a study has been carried out on the usual strategies in these video games and a reusable architecture has been implemented that allows the different agents and environments to be exchanged easily. Finally, the results obtained in the different experiments carried out are analyzed and the conclusions drawn from these results are presented.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

The Future of Learning: Preparing for Change

This report aims to identify, understand and visualise major changes to learning in the future. It developed a descriptive vision of the future, based on existing trends and drivers, and a normative vision outlining how future learning opportunities should be developed to contribute to social cohesion, socio-economic inclusion and economic growth. The overall vision is that personalisation, collaboration and informalisation (informal learning) are at the core of learning in the future. These terms are not new in education and training but will have to become the central guiding principle for organising learning and teaching in the future. The central learning paradigm is thereby characterised by lifelong and life-wide learning, shaped by the ubiquity of Information and Communication Technologies (ICT). To reach the goals of personalised, collaborative and informalised learning, holistic changes need to be made (curricula, pedagogies, assessment, leadership, teacher training, etc.) and mechanisms need to be put in place which make flexible and targeted lifelong learning a reality and support the recognition of informally acquired skills.JRC.J.4-Information Societ

The future of learning: preparing for change

To contribute to this vision-building process, JRC-IPTS on behalf of DG Education and Culture launched a foresight study on “The Future of Learning: New Ways to Learn New Skills for Future Jobs”, in 2009. This study continues and extends IPTS work done in 2006-2008 on “Future Learning Spaces” (Punie et al., 2006, Punie & Ala-Mutka, 2007, Miller et al., 2008). It is made up of different vision building exercises, involving different stakeholder groups ranging from policy makers, and scientists to educators and learners. The majority of these stakeholder consultations were implemented on behalf of by a consortium led by TNO of the Netherlands with partners at the Open University of the Netherlands and Atticmedia, UK. The detailed results of these stakeholder discussions have been published in dedicated reports (cf. Ala-Mutka et al., 2010; Stoyanov et al., 2010; Redecker et al., 2010a). This report synthesizes and discusses the insights collected. It identifies key factors for change that emerge at the interface of the visions painted by different stakeholder groups and arranges them into a descriptive vision of the future of learning in 2020-2030. In a second step, the report discusses future solutions to pending challenges for European Education and Training systems and outlines policy options. Based on the descriptive vision presented in the first part, a normative vision is developed of an ideal learning future, in which all citizens are enabled to develop their talents to the best and to foster their own wellbeing and prosperity as well as that of the society they live in as active citizens. Strategies fostering such a vision and the policy implications supporting it are presented and discussed

On concepts and methods in horizon scanning : lessons from initiating policy dialogues on emerging issues

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)Future-oriented technology analysis methods can play a significant role in enabling early warning signal detection and pro-active policy action which will help to better prepare policy- and decision-makers in today’s complex and inter-dependent environments. This paper analyses the use of different horizon scanning approaches and methods as applied in the Scanning for Emerging Science and Technology Issues project. A comparative analysis is provided as well as a brief evaluation the needs of policy-makers if they are to identify areas in which policy needs to be formulated. This paper suggests that the selection of the best scanning approaches and methods is subject to contextual and content issues. At the same time, there are certain issues which characterise horizon scanning processes, methods and results that should be kept in mind by both practitioners and policy-makers

On concepts and methods in horizon scanning: Lessons from initiating policy dialogues on emerging issues

Future-oriented technology analysis methods can play a significant role in enabling early warning signal detection and pro-active policy action which will help to better prepare policy- and decision-makers in today's complex and inter-dependent environments. This paper analyses the use of different horizon scanning approaches and methods as applied in the Scanning for Emerging Science and Technology Issues project. A comparative analysis is provided as well as a brief evaluation the needs of policy-makers if they are to identify areas in which policy needs to be formulated. This paper suggests that the selection of the best scanning approaches and methods is subject to contextual and content issues. At the same time, there are certain issues which characterise horizon scanning processes, methods and results that should be kept in mind by both practitioners and policy-maker

Forlic: First series of personas

Presentation of 9 personas for the development of vision scenarios

A Novel Class of Defensive Compounds in Harvestmen: Hydroxy-γ-Lactones from the Phalangiid Egaenus convexus

When threatened, the harvestman Egaenus convexus (Opiliones: Phalangiidae) ejects a secretion against offenders. The secretion originates from large prosomal scent glands and is mainly composed of two isomers of 4-hydroxy-5-octyl-4,5-dihydro-3H-furan-2-one (1), a β-hydroxy-γ-lactone. The compounds were characterized by GC-MS of their microreaction derivatives, HRMS, and NMR. After the synthesis of all four possible stereoisomers of 1, followed by their separation by chiral-phase GC, the absolute configurations of the lactones in the Egaenus secretion was found to be (4S,5R)-1 (90%) and (4S,5S)-1 (10%). Hydroxy-γ-lactones represent a new class of exocrine defense compounds in harvestmen