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Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly-realistic,natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment(e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providingtheir capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is acomplex and multi-level task, varying from assuming control and assisting users to realise their creative intents, to deliveringintuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowdsimulation components, ranging from high-level behaviours and path-planning to local movements, as well as animation andvisualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influencethat the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical userinterfaces, drag-and-drop), identifying the trends of early and recent work. Finally, we suggest promising directions for futureresearch that mainly stem from the rise of learning-based methods, and the need for a unified authoring framework. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 860768 (CLIPE project). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy

Agent-Based Simulation is a suitable approach used now-a-days to simulate and analyze complex societal environments and scenarios. Current Agent-Based Simulation frameworks either scale quite well in computation but implement very simple reasoning mechanisms, or employ complex reasoning systems at the expense of scalability. In this paper we present our work to extend an agent-based HPC platform, enabling goal-driven agents with HTN planning capabilities to scale and run parallelly. Our extension includes preferences over their objectives, preferences over their plans, actions, and moral values. We show the expresiveness of the extended platform with a sample scenario. This work has been partially supported by EU Horizon 2020 Project StairwAI (grant agreement No.101017142).

When integrating artificial agents into physical or digital environments that are shared with humans, agents are often equipped with opaque Machine Learning methods to enable adapting their behaviour to dynamic human needs and environment. This brings about agents that are also opaque and therefore hard to explain. In previous work, we show that we can reduce an opaque agent into an explainable Policy Graph (PG) which works accurately in multi-agent environments. Policy Graphs are based on a discretisation of the world into propositional logic to identify states, and the choice of which discretiser to apply is key to the performance of the reduced agent. In this work, we explore this further by 1) reducing a single agent into an explainable PG, and 2) enforcing collaboration between this agent and an agent trained from human behaviour. The human agent is computed by using GAIL from a series of human-played episodes, and kept unchanged. We show that an opaque agent created and trained to collaborate with the human agent can be reduced to an explainable, non-opaque PG, so long as predicates regarding collaboration are included in the state representation, by showing the difference in reward between the agent and its PG. Code is available at https://github.com/HPAI-BSC/explainable-agents-with-humans This work has been partially supported by EU Horizon 2020 Project StairwAI (grant agreement No. 101017142).

Se propone el desarrollo de sistemas y algoritmos de aprendizaje reforzado profundo para entornos de vehículos autónomos. Para ello se propone inicialmente realizar una búsqueda bibliográfica sobre el uso de esta técnica de aprendizaje reforzado profundo para aplicaciones futuras de vehículos autónomos. Otro elemento básico de este proyecto será el desarrollo de herramientas de aprendizaje reforzado profundo, para mejorar en lo posible, la capacidad de aprendizaje del vehículo, la capacidad de adaptación a un entorno cambiante, y su capacidad final de decidir y realizar u The project explores the possibilities offered by reinforcement learning in the field of robotics with the vision of guiding robots in changing environments with collision avoidance through potential fields. For this, the DDPG, TD3, SAC and PPO reinforcement learning algorithms are implemented through the Matlab Toolbox "Reinforcement Learning" with the aim of carrying out a comparative study on which of them is the most optimal for different configurations of environments and parameters, with the help of training graphs and statistical tables. Also, potential fields have been developed in this project, demonstrating to be a suitable tool for guiding robots in changing environments, and even to implement multi agent scenarios, avoiding collisions among them and enhancing collaboration. El projecte explora les possibilitats que ofereix l'aprenentatge per reforç en l'àmbit de la robòtica amb la visió de guiar robots a través d'entorns canviants amb evitació de col·lisions mitjançant camps de potencials. Per això s'implementen els algorismes d'aprenentatge per reforç DDPG, TD3, SAC i PPO per mitjà de la Toolbox de Matlab Reinforcement Learning amb l'objectiu de fer un estudi comparatiu sobre quin d'ells és el més òptim per a diferents configuracions d'entorns i paràmetres; tot això amb l'ajuda de gràfiques d'entrenament i taules estadístiques. Així mateix, s'han desenvolupat camps potencials en aquest projecte, demostrant ser una eina adequada per a guiar robots en entorns canviants, i fins i tot per implementar escenaris multiagent, evitant col·lisions entre ells i potenciant la col·laboració. El proyecto explora las posibilidades que ofrece el aprendizaje por refuerzo en el ámbito de la robótica con la visión de guiar a robots a través de entornos cambiantes con evitación de colisiones mediante campos potenciales. Para ello se implementan los algoritmos de aprendizaje por refuerzo DDPG, TD3, SAC y PPO por intermedio de la Toolbox de Matlab "Reinforcement Learning" con el objetivo de realizar un estudio comparativo sobre cuál de ellos es el más óptimo para diferentes configuraciones de entornos y parámetros; todo ello con la ayuda de gráficas de entrenamiento y tablas estadísticas. Además, en este proyecto se han desarrollado campos potenciales, demostrando ser una herramienta adecuada para guiar robots en entornos cambiantes, e incluso implementar escenarios multiagente, evitando colisiones entre ellos y potenciando la colaboración.

Como estudiante, en muchas ocasiones he tenido la necesidad de preguntar sobre cuestiones académicas que no lograba encontrar. Y el hecho de que las entidades que pueden responderlas estén saturadas en ocasiones genera una sensación de frustración en el alumno que termina en un mayor descontento y en más saturación de las entidades en cuestión. Es por ello que el objetivo de este proyecto es crear un bot fácilmente escalable que permita a los alumnos facilitar sus problemas del día a día. Si bien no sustituye a dichas entidades, puede reducir su carga de trabajo mediante respuestas más automáticas a cuestiones que resulten más 'triviales' para el alumno. Juntando todo lo que el alumno pueda interesarle en un único menú y con la posibilidad de contactar desde allí con las entidades que necesite si se diera el caso. As a student, on many occasions, I have needed to ask academic questions that I could not find. And the fact that the entities that can answer them are sometimes saturated generates a feeling of frustration in the student that ends in greater discontent and more saturation of the entities in question. That is why the objective of this project is to create an easily scalable bot that allows students to facilitate their day-to-day problems. Although it does not replace these entities, it can reduce their workload through more automatic answers to questions that are more 'trivial' for the student. Bringing together everything that the student may be interested in in a single menu and with the possibility of contacting from there with the entities that they need if the case arises.

Supreme és una marca d'skate que comercialitza roba i altres tipus de productes. En els últims anys s'ha tornat molt popular, sobretot entre els adolescents, i ha esdevingut tot un fenomen de masses i un actor influent a la indústria de la moda. La característica més distintiva de Supreme és el seu model de negoci. Els productes de la marca no estan disponibles per comprar en qualsevol moment, en lloc d'això, la marca divideix les seves col·leccions en diversos llançaments («drops») setmanals. Els articles es llancen els dijous de cada setmana, a una hora determinada, amb un estoc molt limitat i quan s'esgoten no tornen a estar disponibles mai més. La majoria d'articles s'esgoten en qüestió de segons, això vol dir que hi ha una diferència notable entre l'oferta de productes i la seva demanda. Fet que ha propiciat l'aparició d'un gran mercat de revenda. Inicialment, els clients utilitzaven scripts rudimentaris i extensions de navegador per aconseguir un avantatge respecte els altres compradors i ser els primers en passar per caixa. Poc a poc, aquests mètodes van anar evolucionant fins als complexos bots de compra que existeixen avui en dia. Aquests bots són capaços de realitzar tot el procés de compra de forma automàtica i d'obtenir el producte desitjat per l'usuari sense la necessitat d'interacció humana. L'ús de bots de compra a Supreme està tan estès que si un usuari vol adquirir un dels articles més cobdiciats d'un llançament, llavors és imprescindible que n'utilitzi un. Al llarg d'aquest treball es descriu el desenvolupament d'un bot de compra basat en emulació del navegador, començant per l'estudi del context del projecte, passant per la definició de l'abast i la metodologia utilitzada, seguint amb l'especificació i el disseny de l'aplicació i acabant amb l'explicació de la implementació i la valoració dels resultats. Els bots basats en emulació interactuen amb la pàgina de Supreme a través del navegador, utilitzant els elements visuals de la interfície web, com si fossin un comprador qualsevol. L'avantatge d'aquest tipus de bots és que tenen l'empremta digital d'un navegador real i passen desapercebuts pels sistemes de control. Per implementar l'aplicació s'ha utilitzat Java com a llenguatge de programació base i la llibreria Jsoup i el «framework» Selenium per la interacció amb la pàgina web de Supreme. Supreme is a skate brand that sells clothing and other types of products. In recent years it has become very popular, especially among teenagers, and has become a mass phenomenon and an influential actor in the fashion industry. Supreme's most distinctive feature is its business model. The products of the brand are not available all the time, instead the brand divides its collections into several weekly releases ("drops"). The items are released on Thursdays of each week, at a certain time, with a very limited stock and when they run out they are never available again. Most items sell out in a matter of seconds, which means that there is a noticeable difference between product supply and demand. This fact has led to the appearance of a large resale market. Initially, customers used rudimentary scripts and browser extensions to gain an advantage over other shoppers and be the first to checkout. Gradually, these methods evolved into the complex shopping bots that exist today. These bots are capable of carrying out the entire purchase process automatically and obtain the product desired by the user without human interaction. The use of shopping bots on Supreme is so widespread that if a user wants to purchase one of the most coveted items from a drop, then using one is a must. This final thesis describes the development of a shopping bot that is based on browser emulation, starting with the study of the project context, going through the definition of the project scope and the methodology used, continuing with the specification and design of the application and ending with the explanation of the implementation and the evaluation of the results. Emulation-based bots interact with the Supreme page through the browser, using the visual elements of the web interface, as if they were normal buyers. The advantage of this type of bots is that they have the fingerprint of a real browser and they pass unnoticed by the control systems. To implement the application, Java has been used as the base programming language. The library Jsoup and the framework Selenium are used to interact with the Supreme website.

The rise of social networks and the increase of notifications we receive on our phones has had a negative impact on the way people work. Distractions have become a more serious problem on such times when productivity is the center of attention of many project managers. This project has analyzed this issue, and proposed a modern and flexible solution based on a conversational agent. It has implemented and evaluated a mobile application designed to support focused work, obtaining results that suggest the validation and effectiveness of a work assistant to increase productivity and well-being.

La Inteligencia Artificial es un área que trata de evolucionar constantemente con el fin de poder abordar cualquier problema, consiguiendo que hoy en día prácticamente todo pueda estar automatizado. En nuestro trabajo vamos a centrarnos en el aprendizaje por refuerzo, un área que cobra cada vez más fuerza dentro de este ámbito. Hace relativamente poco, Unity presento un kit de herramientas para el aprendizaje automático llamado ml-agents. Esta herramienta nos permite llevar a cabo proyectos muy sencillos así como otros de mucha complejidad, y todo esto sin la necesidad de tener una gran experiencia en el ámbito. En este proyecto vamos a diseñar e implementar un sistema complejo donde un agente aprenda a navegar por entornos naturales de la forma mas realista posible. Buscaremos explotar al máximo las capacidades de esta herramientas, tratando que las decisiones que toma nuestro agente sean lógicas y coherentes en función del escenario que tenga delante. Artificial Intelligence is an area that is constantly evolving in order to be able to tackle any problem, so that nowadays practically everything can be automated. In our work we are going to focus on reinforcement learning, an area that is gaining more and more strength in this field. Relatively recently, Unity introduced a machine learning toolkit called ml-agents. This tool allows us to carry out very simple projects as well as others of great complexity, and all this without the need of having a great deal of experience in the field. In this project we are going to design and implement a complex system where an agent learns to navigate through natural environments in the most realistic way possible. We will seek to exploit the capabilities of these tools to the maximum, trying to ensure that the decisions made by our agent are logical and coherent depending on the scenario he is faced with.

Donat l'enorme creixement de les tecnologies blockchain a finals de 2021. En particular un dels seus actius anomenat NFT, un actiu que és una nova forma d'escassetat digital. Aquest projecte pretén estudiar el seu mercat encara altament volàtil i desenvolupar tant un DataFrame com un bot, capaços de predir el rendiment economic d'una col·lecció de NFTs en el futur proper. El projecte es centra en el mercat principal de NFT Opensea i concretament en les col·leccions de l'ecosistema Ethereum, que té el 80% del mercat a principis de 2022. Degut a la seva novetat, fins ara s'han fet poques aplicacions i estudis sobre aquest nou mercat. Però això no ha impedit que aquest nou actiu augmenti ràpidament en popularitat des de els 10.000 usuaris fins a més d'1,5 milions només en l'últim any. És cert que a mesura que creix l'interès es publicaran més informació i projectes, però cap semblant a aquesta tesi a la data d'inici. Quan s'intenta fer un anàlisi de dades la mida de la mostra és un factor clau, però aquest és un escàs recurs quan es parla de transaccions NFT. Per això per fer tota l'anàlisi i proves d'aquest projecte, s'han seleccionat 36 de les col·leccions més venudes del mercat. Per crear aquest conjunt només s'han triat col·leccions principals, descartant col·leccions secundàries de marques ja consolidades en l'espai. A més, per garantir dades homogènies, tots els DataFrames emmagatzemen informació dels mateixos períodes des de l'1 de desembre de 2021 fins al 31 de març de 2022. Mitjançant l'API d'Opensea, la majoria de les dades necessàries s'han extret directament de la blockchain. Milers de transaccions de cada col·lecció NFT s'han processat i emmagatzemat en dataFrames, produint fitxers .csv facilment llegibles emmagatzemats en un directori per a un ús futur. Finalment, pel que fa al bot, s'ha utilitzat l'algoritme d'aprenentatge automàtic per a la predicció de dades LSTM (Long Short Term Memory). Aquest s'utilitza habitualment per a la predicció de la borsa i ha estat seleccionat com el més prometedor per a aquest projecte. Els models s'han entrenat i provat utilitzant subconjunts dels dataFrames previament construits. Finalment s'ha realitzat una experimentació addicional amb terminis de 4 i 5 mesos de dades i diferents mitjanes mòbils. Given the enormous growth of blockchain technologies at the end of 2021. Particularly one of its assets called NFTs, an asset that is a new form of digital scarcity. This project aims to study their still highly volatile market and develop both a dataFrame and a bot, capable of predicting a NFT collection performance in the near future. Project focuses on the NFT main marketplace Opensea and specifically the collections in the Ethereum ecosystem, which has 80% of the market as of early 2022. Because of its novelty few applications and studies have been done on this field to date. But this hasn't stopped this new asset to rapidly rise in popularity from a small 10k users to more than 1.5M only in the last year. It is true that as interest grows more and more information and projects are being published, but none similar to this thesis as of start date. When trying to do a data analysis sample size is a key factor, but a scarce resource when talking about NFT transactions. Because of this to make all the analysis and testing of this project 36 from the best-selling collections in the market have been selected. To create this set only main collections have been chosen, discarding secondary collections from already established brands. Moreover, to ensure homogeneous data, all dataFrames store information from the same periods from December 1st, 2021 to March 31, 2022. Using the Opensea API, most of the data needed has been taken directly from the blockchain. Thousands of transactions from each NFT collection have then been processed and stored into dataFrames, producing readable .csv files stored into a directory for future use. Lastly regarding the bot, machine learning algorithm for data prediction LSTM (Long Short Term Memory) have been used. Commonly used for stock market prediction, this algorithm has been selected as the most promising one for this project. Models have been trained and tested using subsets of each collection dataFrames. After that, further examination has been made with timeframes of 4 and 5 months of data and different moving averages.

International audience; We propose a hierarchical framework for collaborative intelligent systems. This framework organizes research challenges based on the nature of the collaborative activity and the information that must be shared, with each level building on capabilities provided by lower levels. We review research paradigms at each level, with a description of classical engineering-based approaches and modern alternatives based on machine learning, illustrated with a running example using a hypothetical personal service robot. We discuss cross-cutting issues that occur at all levels, focusing on the problem of communicating and sharing comprehension, the role of explanation and the social nature of collaboration. We conclude with a summary of research challenges and a discussion of the potential for economic and societal impact provided by technologies that enhance human abilities and empower people and society through collaboration with Intelligent Systems.; Nous proposons un cadre hiérarchique pour les systèmes intelligents collaboratifs. Ce cadre organise les défis de recherche en fonction de la nature de l'activité collaborative et des informations qui doivent être partagées, chaque niveau s'appuyant sur les capacités fournies par les niveaux inférieurs. Nous passons en revue les paradigmes de recherche à chaque niveau, avec une description des approches classiques basées sur l'ingénierie et des alternatives modernes basées sur l'apprentissage automatique, illustrées par un exemple courant utilisant un hypothétique robot de service personnel. Nous discutons des questions transversales qui se produisent à tous les niveaux, en nous concentrant sur le problème de la communication et du partage de la compréhension, le rôle de l'explication et la nature sociale de la collaboration. Nous concluons par un résumé des défis de la recherche et une discussion sur le potentiel d'impact économique et sociétal fourni par les technologies qui améliorent les capacités humaines et autonomisent les personnes et la société grâce à la collaboration avec les systèmes intelligents.

En aquest projecte es desenvolupa un plugin que integra Botonic (framework per desenvolupar aplicacions conversacionals) amb un CMS anomenat Directus. El problema que es vol resoldre amb aquesta integració és la gestió dels continguts que es mostren a les aplicacions conversacionals. D'aquesta manera, enlloc de guardar els continguts en fitxers de la propia aplicació, aquesta informació es guarda en bases de dades i s'obté des del CMS mitjançant una API. Les principals millores que s'hi presenten amb aquesta solució són: no és necessari deployar l'aplicació de nou cada vegada que es vulgui fer un canvi en els continguts, usuaris externs, sense haver de tocar codi, poden manipular els continguts i els canvis s'hi veuen reflectits instantàniament, els continguts es poden organitzar i gestionar d'una manera més endreçada, hi ha molta més flexibilitat i possibilitats per crear continguts de diferents formes, amb diferents atributs i diferents funcionalitats, fan que el codi de l'aplicació quedi molt més nét i llegible. Per a poder triar la millor solució, s'ha realitzat un estudi i anàlisi exhaustius del mercat. Un cop s'ha escollit quin CMS encaixa el màxim possible amb les necessitats que s'hi presenten, s'ha desenvolupat el plugin d'una manera estructurada i seguint el principi de programació SOLID. Per cada funcionalitat s'han anat creant tests unitaris per assegurar que el codi funcioni correctament i per disminuir la possibilitat de l'existència d'algun bug o error. Els resultats han estat satisfactoris i s'ha pogut resoldre el problema plantejat. S'ha aconseguit integrar el CMS, podent guardar-hi la informació i obtenint-la per mostrar-la en una aplicació conversacional. In this project a plugin has been developed in order to integrate Botonic (framework for developing conversational applications) with a CMS called Directus. The problem to be solved with this integration is the management of the content displayed in conversational applications. In this way, instead of saving the contents in files of the application itself, this information is saved in databases and is obtained from the CMS through an API. The main improvements that are presented with this solution are: it is not necessary to deploy the app every time you want to make a change to the content, external users, without having to touch code, can manipulate the contents and the changes are reflected instantly, the contents can be organized and managed in a more orderly way, there is much more flexibility and possibilities to create content in different ways, with different attributes and different functionalities, make the application code much cleaner and more readable. In order to choose the best solution, an exhaustive study and analysis of the market has been carried out. Once it has been chosen which CMS fits the maximum possible with the needs that are presented, the plugin has been developed in a structured way and following the SOLID programming principle. Unit tests have been created for each functionality to ensure that the code works correctly and to reduce the possibility of the existence of a bug or error. The results have been satisfactory and the problem raised has been solved. The CMS has been integrated, being able to save the information and obtain it to display it in a conversational application.

As long as critical levels of vaccination have not been reached to ensure heard immunity, and new SARS-CoV-2 strains are developing, the only realistic way to reduce the infection speed in a population is to track the infected individuals before they pass on the virus. Testing the population via sampling has shown good results in slowing the epidemic spread. Sampling can be implemented at different times during the epidemic and may be done either per individual or for combined groups of people at a time. The work we present here makes two main contributions. We first extend and refine our scalable agent-based COVID-19 simulator to incorporate an improved socio-demographic model which considers professions, as well as a more realistic population mixing model based on contact matrices per country. These extensions are necessary to develop and test various sampling strategies in a scenario including the 62 largest cities in Spain; this is our second contribution. As part of the evaluation, we also analyze the impact of different parameters, such as testing frequency, quarantine time, percentage of quarantine breakers, or group testing, on sampling efficacy. Our results show that the most effective strategies are pooling, rapid antigen test campaigns, and requiring negative testing for access to public areas. The effectiveness of all these strategies can be greatly increased by reducing the number of contacts for infected individual. This work has been supported by the Carlos III Institute of Health under the project grant 2020/00183/001, the project grant BCV-2021-1-0011, of the Spanish Supercomputing Network (RES) and the European Union’s Horizon 2020 JTI-EuroHPC research and innovation program under grant agreement No 956748. The role of all study sponsors was limited to financial support and did not imply participation of any kind in the study and collection, analysis, and interpretation of data, nor in the writing of the manuscript.

Although smart devices markets are increasing their sales figures, their computing capabilities are not sufficient to provide good-enough-quality services. This paper proposes a solution to organize the devices within the Cloud-Edge Continuum in such a way that each one, as an autonomous individual –Agent–, processes events/data on its embedded compute resources while offering its computing capacity to the rest of the infrastructure in a Function-as-a-Service manner. Unlike other FaaS solutions, the described approach proposes to transparently convert the logic of such functions into task-based workflows backing on task-based programming models; thus, agents hosting the execution of the method generate the corresponding workflow and offloading part of the workload onto other agents to improve the overall service performance. On our prototype, the function-to-workflow transformation is performed by COMPSs; thus, developers can efficiently code applications of any of the three envisaged computing scenarios – sense-process-actuate, streaming and batch processing – throughout the whole Cloud-Edge Continuum without struggling with different frameworks specifically designed for each of them. This work has been supported by the Spanish Government (PID2019-107255GB), by Generalitat de Catalunya (contract 2014-SGR-1051), and by the European Commission through the Horizon 2020 Research and Innovation program under Grant Agreement No. 101016577 (AI-SPRINT project).

Mobile applications have become a commodity in multiple daily scenarios. Their increasing complexity has led mobile software ecosystems to become heterogeneous in terms of hardware specifications, features and context of use, among others. For their users, fully exploiting their potential has become challenging. While enacting software systems with adaptation mechanisms has proven to ease this burden from users, mobile devices present specific challenges related to privacy and security concerns. Nevertheless, rather than being a limitation, users can play a proactive role in the adaptation loop by providing valuable feedback for runtime adaptation. To this end, we propose the use of chatbots to interact with users through a human-like smart conversational process. We depict a work-in-progress proposal of an end-to-end framework to integrate semi-automatic adaptation mechanisms for mobile applications. These mechanisms include the integration of both implicit and explicit user feedback for autonomous user categorization and execution of enactment action plans. We illustrate the applicability of such techniques through a set of scenarios from the Mozilla mobile applications suite. We envisage that our proposal will improve user experience by bridging the gap between users’ needs and the capabilities of their mobile devices through an intuitive and minimally invasive conversational mechanism. This work has been partially supported by AGAUR, code 2017-SGR-1694. The corresponding author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of his predoctoral grant FPI-UPC.

The advancement on explainability techniques is quite relevant in the field of Reinforcement Learning (RL) and its applications can be beneficial for the development of intelligent agents that are understandable by humans and are able cooperate with them. When dealing with Deep RL some approaches already exist in the literature, but a common problem is that it can be tricky to define whether the explanations generated for an agent really reflect the behaviour of the trained agent. In this work we will apply an approach for explainability based on the creation of a Policy Graph (PG) that represents the agent’s behaviour. Our main contribution is a way to measure the similarity between the explanations and the agent’s behaviour, by building another agent that follows a policy based on the explainability method and comparing the behaviour of both agents.

Path finding for autonomous agents has been traditionally driven by finding optimal paths, typically by using A* search or any of its variants. When it comes to simulating virtual humanoids, traditional approaches rarely consider aspects of human memory or orientation. In this work, we propose a new path finding algorithm, inspired by current research regarding how the brain learns and builds cognitive maps. Our method represents the space as a hexagonal grid with counters, based on brain research that has investigated how memory cells are fired. Our path finder then combines a method for exploring unknown environments while building such a cognitive map, with an A* search using a modified heuristic that takes into account the cognitive map. The resulting paths show how as the agent learns the environment, the paths become shorter and more consistent with the optimal A* search. Moreover, we run a perceptual study to demonstrate that the viewers could successfully identify the intended level of knowledge of the simulated agents. This line of research could enhance the believability of autonomous agents’ path finding in video games and other VR applications. This work was partly funded by the Spanish Ministry of Economy, Industry and Competitiveness under Grant No. TIN2017- 88515-C2-1-R.

There may be a lot of abusive behaviour in conversations between teenagers, which take place through social media. In this project, we develop classifiers to find out which texts present abuse such as violence, sexual behaviour, disorder, anxiety... For this reason, we use different classifiers that take advantage of the most recent techniques based on language modeling using deep neural networks, namely Transformers. But we find it difficult to obtain supervised data, i.e. data tagged with the feeling it contains. Luckily, thanks to the countless sources of information available on the Internet, we can get unsupervised data and examples of text on the Internet. Consequently, this project aims to explore the possibility of using unsupervised data, beyond using a supervised set to train a system in the task of sentiment classification. More specifically in short texts, in informal contexts and in Catalan and Spanish. We have a set of about 200,000 supervised samples and a set of 300,000 unsupervised samples. We will introduce and study different models of Transformers (BERT, GAN- BERT, XLM-RoBERTa and ELECTRA) and their performance in the work of sentiment analysis. To finish with, based on models that achieve a better score in the binary classification task of feelings, i.e. with ELECTRA and XLM-RoBERTa, we construct a multi- label classifier. En las conversaciones entre adolescentes, que se dan por medio de las redes sociales, pueden existir muchos comportamientos abusivos. En este proyecto desarrollamos clasificadores que detecten qué textos presentan algún abuso como violencia, conductas sexuales, desórdenes, ansiedad... Por este motivo, usamos diferentes clasificadores que aprovechan las técnicas más recientes basadas en modelado de lenguaje mediante redes neuronales profundas, concretamente Transformers. Pero nos encontramos con la dificultad de obtener datos supervisados, es decir datos etiquetados con el sentimiento que contiene. Por suerte, gracias a la infinidad de fuentes de información de las que disponemos en la red, podemos conseguir datos y ejemplos de texto no supervisado a internet. Por consiguiente, este proyecto quiere explorar la posibilidad de utilizar datos no supervisados, más allá de usar un conjunto de datos supervisado para entrenar un sistema en la tarea de clasificación de sentimientos. Más concretamente en textos cortos, en contextos informales y de lengua catalana y castellana. Contamos con un set de cerca de 200.000 muestras supervisadas y un set de 300.000 muestras no supervisadas. Introduciremos y estudiaremos diferentes modelos de Transformers (BERT, GAN-BERT, XLM-RoBERTa y ELECTRA) y su rendimiento en la tarea de análisis de sentimientos. Finalmente, a partir de los modelos que consiguen una mejor puntuación en la tarea de clasificación binaria de sentimientos, es decir con ELECTRA y XLM-RoBERTa, construimos un clasificador multi-etiqueta. En les converses entre adolescents, que es donen per mitjà de les xarxes socials, poden existir molts comportaments abusius. En aquesta tesi desenvolupem classificadors que detectin quins textos presenten algun abús com violència, conductes sexuals, desordres, ansietat... Per aquest motiu, faig servir diferents classificadors que aprofiten les tècniques més recents basades en modelat de llenguatge mitjançant xarxes neuronals profundes, concretament Transformers. Però ens trobem amb la dificultat d?obtenir dades supervisades, és a dir dades etiquetades amb el sentiment que conté. Per sort, gràcies a la infinitat de fonts d?informació de les que disposem a la xarxa, podem aconseguir dades i exemples de text no supervisat a internet. Per consegüent, aquest projecte vol explorar la possibilitat d'utilitzar dades no supervisades, més enllà de fer servir un set supervisat per entrenar un sistema en la tasca de classificació de sentiments. Més concretament en textos curts, en contextos informals i de llengua catalana i castellana. Comptem amb un set de prop de 200.000 mostres supervisades i un set de 300.000 mostres no supervisades. Introduirem i estudiarem diferents models de Transformers (BERT,GAN-BERT,XLM-Roberta i Electra) i el seu rendiment en la tasca d'anàlisi de sentiments. Finalment, a partir dels models que aconsegueixen una millor puntuació en la tasca de classificació binària de sentiments, és a dir amb Electra i XLM-Roberta, construïm un classificador multi-label

Hospital patient waiting times and length of stay are indicators of the quality of emergency department (ED) services, factors that are a ected by the number of patient arrivals. It is necessary to ac- curately estimate ED patient arrivals in order to manage resources e ectively. Prediction models, however, are conditioned by the hospi- tal population and its placement (i.e. meteorological conditions). In the particular case of a tourist region, the population has an impor- tant amount of variability which challenge EDs. This paper aims to address ED attendances predictions for an hospital placed in a tourist region by means of a new approach that combines multiple linear re- gression with arti cial neural networks and regression tree ensembles, looking for dealing for ED variability and prediction for a week time horizon that enables operational reaction to the ED responsible. The methodology uses exogenous variables such as calendar, weather and socio-economic data to improve the accuracy of these forecasts. Pre- diction models are built on data for 11-years and the predictions are tested over 1-year. The results showed that the proposed methodol- ogy is capable to perform weekly predictions with an error about 5%, demonstrating that it could be used by EDs The work was carried out with support from the Generalitat de Catalunya 2017 SGR 1551

La empresa Bookline ha desarrollado un asistente virtual que puede atender llamadas a restaurantes y ayudar a los usuarios a realizar una reserva. Este trabajo pretende implementar todas sus funcionalidades a través de un chatbot que permita al asistente atender a usuarios a través de los servicios de mensajería instantánea más populares. El objetivo és diseñar un programa que pueda atender a los usuarios a través de chatbots de Whatsapp, Telegram y Facebook Messenger, y que se pueda extender fácilmente a otros servicios insertando unas mínimas modificaciones. Para el desarrollo de este proyecto se han utilizado principalmente servicios de Google Cloud Platform y el lenguaje de programación Python. El resultado final del proyecto és un chatbot para cada servicio de mensajería que permita dialogar en castellano o inglés, capaz de responder a cualquier pregunta igual que lo haría el asistente de Bookline y que permita reservar una mesa en los restaurantes que contraten este servicio. The company Bookline has developed a virtual assistant that attends calls to restaurants and helps users at making reservations. This project aims to implement all of the assistant's functions in a chatbot that would allow the assistant to attend users through the most popular instant messaging services. My objective is to design a program capable of attending users through chatbots in Whatsapp, Telegram and Facebook Messenger, and make it easy to extend it to other services through some minimal modifications. For the development of this project the tools that have been primarily used were some services from Google Cloud Platform and the programming language Python. The project's final result is a chatbot for each messaging service that can follow a conversation in Spanish or English, capable of responding to any question as Bookline's assistant would, and capable of booking a table in any restaurant that has hired this service. L'empresa Bookline ha desenvolupat un assistent virtual que pot atendre les trucades a restaurants i ajudar als usuaris a realitzar una reserva. Aquest treball pretén implementar totes les seves funcions a través d'un chatbot que permeti a l'assistent atendre als usuaris a través dels serveis de missatgeria instantània més populars. L'objectiu és dissenyar un programa que pugui atendre als usuaris a través de chatbots de Whatsapp, Telegram i Facebook Messenger, i que es pugui estendre fàcilment a altres serveis fent les modificacions mínimes. Per al desenvolupament d'aquest projecte s'han fet servir principalment serveis de Google Cloud Platform i el llenguatge de programació Python. El resultat final del projecte és un chatbot per a cada servei de missatgeria que permet dialogar amb castellà o anglès, capaç de respondre a qualsevol pregunta igual que l'assistent de Bookline i que permeti reservar una taula en els restaurants que contractin aquest servei.

Els models BPMN (Business Process Modeling and Notation), els quals permeten representar els processos de negoci d'una empresa, no resulten fàcils d'entendre per part d'aquelles persones no qualificades. En l'àmbit laboral, la majoria de treballadors no tenen els coneixements per entendre'ls. Això fa que es requereixi algú que expliqui el funcionament del negoci. A més, no sempre és possible tenir algú a qui preguntar un dubte, el que pot causa que un treballador no sàpiga que fer. La problemàtica dels BPMN també pot aplicar-se a treballadors que si entenen els models. Per exemple, un alt càrrec, que vulgui consultar un detall d'un determinat procés, pot perdre molt de temps buscant entre molts models per tal de trobar el que busca. L'objectiu general del projecte és crear una aplicació que transformi processos de negoci en assistents virtuals. Concretament, el projecte construeix un prototip fent ús de les tecnologies més punteres i avalua les tecnologies segons la flexibilitat del llenguatge obtinguda. En aquest context, la flexibilitat del llenguatge s'entén com a la diversitat del vocabulari, que pot utilitzar una persona, en referir-se a un mateix concepte. El prototip selecciona un model BPMN, el processa i genera frases de resposta. A més, genera frases amb significat similar, per tal d'augmentar la flexibilitat del llenguatge. Un cop acabat el processat, s'utilitza Dialogflow (una eina de modelatge d'assistents virtuals) per tal de construir l'assistent virtual. Finalment i durant una conversa amb l'assistent, s'utilitza un servidor per a emmagatzemar la informació pertinent. Tenint en compte el prototip construït, el projecte conclou que dialogflow és una bona eina pel que fa a la generació d'assistents virtuals a partir d'un model BPMN. Tot i això, si es vol aconseguir un bon resultat en la flexibilitat del llenguatge, s'ha de dedicar grans esforços en la generació de frases amb significat similar. El projecte conclou que es requereix més recerca per aconseguir una major flexibilitat en el llenguatge Business Process Modeling and Notation (BPMN) models, which allow you to represent the business processes of a company, are not easy to understand by those who are not qualified. In the workplace, most workers do not have the knowledge to understand them. This requires someone to explain how the business works. Also, it is not always possible to have someone to ask a question to, which can cause a worker to not know what to do. The problem of BPMNs can also be applied to workers who do understand the models. For example, a senior official, who wants to consult a detail of a certain process, may waste a lot of time searching among many models in order to find what he is looking for. The overall goal of the project is to create an application that transforms business processes into virtual assistants. Specifically, the project builds a prototype using the most advanced technologies and evaluates the technologies according to the flexibility of the language obtained. In this context, the flexibility of language is understood as the diversity of vocabulary, which a person can use, when referring to the same concept. The prototype selects a BPMN model, processes it, and generates response sentences. In addition, it generates sentences with similar meanings, in order to increase the flexibility of the language. Once the processing is complete, Dialogflow (a virtual assistant modeling tool) is used to build the virtual assistant. Finally, during a conversation with the wizard, a server is used to store the relevant information. Given the prototype built, the project concludes that dialogflow is a good tool for generating virtual assistants from a BPMN model. However, if you want to get a good result in language flexibility, you have to put a lot of effort into generating sentences with similar meaning. The project concludes that more research is required to achieve greater flexibility in language. Los modelos BPMN (Business Process Modeling and Notation), los cuales permiten representar los procesos de negocio de una empresa, no resultan fáciles de entender por parte de aquellas personas no cualificadas. En el ámbito laboral, la mayoría de trabajadores no tienen los conocimientos para entenderlos. Esto hace que se requiera alguien que explique el funcionamiento del negocio. Además, no siempre es posible tener a alguien a quien preguntar una duda, lo que puede causa que un trabajador no sepa que hacer. La problemática de los BPMN también puede aplicarse a trabajadores que si entienden los modelos. Por ejemplo, un alto cargo, que quiera consultar un detalle de un determinado proceso, puede perder mucho tiempo buscando entre muchos modelos a fin de encontrar lo que busca. El objetivo general del proyecto es crear una aplicación que transforme procesos de negocio en asistentes virtuales. Concretamente, el proyecto construye un prototipo en uso de las tecnologías más punteras y evalúa las tecnologías según la flexibilidad del lenguaje obtenida. En este contexto, la flexibilidad del lenguaje se entiende como la diversidad del vocabulario, que puede utilizar una persona, al referirse a un mismo concepto. El prototipo selecciona un modelo BPMN, lo procesa y genera frases de respuesta. Además, genera frases con significado similar, a fin de aumentar la flexibilidad del lenguaje. Una vez terminado el procesado, se utiliza Dialogflow (una herramienta de modelado de asistentes virtuales) para construir el asistente virtual. Finalmente y durante una conversación con el asistente, se utiliza un servidor para almacenar la información pertinente. Teniendo en cuenta el prototipo construido, el proyecto concluye que dialogflow es una buena herramienta en cuanto a la generación de asistentes virtuales a partir de un modelo BPMN. Sin embargo, si se quiere conseguir un buen resultado en la flexibilidad del lenguaje, se debe dedicar grandes esfuerzos en la generación de frases con significado similar. El proyecto concluye que se requiere de más investigación para conseguir una mayor flexibilidad en el lenguaje.

Our work is concerned with user modelling in open environments. Our proposal then is the line of contributions to the advances on user modelling in open environments thanks so the Agent Technology, in what has been called Smart User Model. Our research contains a holistic study of User Modelling in several research areas related to users. We have developed a conceptualization of User Modelling by means of examples from a broad range of research areas with the aim of improving our understanding of user modelling and its role in the next generation of open and distributed service environments. This report is organized as follow: In chapter 1 we introduce our motivation and objectives. Then in chapters 2, 3, 4 and 5 we provide the state-of-the-art on user modelling. In chapter 2, we give the main definitions of elements described in the report. In chapter 3, we present an historical perspective on user models. In chapter 4 we provide a review of user models from the perspective of different research areas, with special emphasis on the give-and-take relationship between Agent Technology and user modelling. In chapter 5, we describe the main challenges that, from our point of view, need to be tackled by researchers wanting to contribute to advances in user modelling. From the study of the state-of-the-art follows an exploratory work in chapter 6. We define a SUM and a methodology to deal with it. We also present some cases study in order to illustrate the methodology. Finally, we present the thesis proposal to continue the work, together with its corresponding work scheduling and temporalisation

Low-cost low-margin implementation plays an essential role in upgrading optical metro networks required for future 5G ecosystem. In this regard, low-resolution analog-to-digital converters can be used in coherent optical transponders to reduce cost and power consumption. However, the resulting transmission systems become more sensitive to physical layer fluctuations like the events caused by fiber stressing. Such fluctuations might have a strong impact on the quality of transmission (QoT) of the signals. To guarantee robust operation, soft decision forward error correction (FEC) techniques are required to guarantee zero post-FEC bit error rate (BER) transmission, which could increase the power consumption of the receiver and thus operational expenses. In this paper, we aim at minimizing power consumption while keeping zero post-FEC errors by means of a predictive autonomic transmission agent (ATA) based on machine learning. We present a sophisticated ATA model that, taking advantage of real-time monitoring of state of polarization traces and the corresponding pre-FEC BER, predicts the right FEC configuration for short-term operation, thus requiring minimum power consumption. In addition, we propose a complementary long-term prediction of excessive pre-FEC BER to enable remote reconfiguration at the transmitter side through the network controller. A set of experimental measurements is used to train and validate the proposed ATA system. Exhaustive numerical analysis allows concluding that ATA based on artificial neural network predictors achieves the maximum QoT robustness with 80% power consumption reductions compared to static FEC configuration. The research leading to these results has received funding from the European Commission for the H2020-ICT-2016-2 METRO-HAUL project (G.A. 761727), from the AEI/FEDER TWINS project (TEC2017-90097-R), and from the Catalan Institution for Research and Advanced Studies (ICREA).

[EN] Existing HW/SW platforms for safety-critical systems suffer from limited performance and/or from lack of flexibility due to building on specific proprietary components. This jeopardizes their wide deployment across domains. While some research has been done to overcome these limitations, they have had limited success owing to missing flexibility and extensibility. Flexibility and extensibility are the cornerstones of industry adoption: industries dealing in capital goods need technologies on which they can rely on during decades (e.g. avionics, space, automotive). SELENE aims at covering this gap by proposing a new family of safety-critical computing platforms, which builds upon open source components such as the RISC-V instruction set architecture, GNU/Linux, and the Jailhouse hypervisor. SELENE will develop an advanced computing platform that is able to: (1) adapt the system to the specific requirements of different application domains, to changing environmental conditions, and to internal conditions of the system itself; (2) allow the integration of applications of different criticalities and performance demands in the same platform, guaranteeing functional and temporal isolation properties; (3) achieve flexible diverse redundancy by exploiting the inherent redundant capabilities of the multicore; and (4) efficiently execute compute-intensive applications by means of specific accelerators., This work has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement no. 871467.

El propósito de este proyecto es crear una aventura gráfica con puzzles generados proceduralmente para poder añadir rejugabilidad, junto con una historia ramificada, lo cual hará que el jugador pueda elaborar su propia historia sin repetir los mismos puzzles que ya hizo la primera vez. Pretendemos así estimular al jugador a embarcarse en la aventura más de una vez sabiendo que los retos que encontrará no serán los mismo que las veces anteriores. Con esto conseguimos una mayor motivación a disfrutar de más horas de juego suponiendo un menor coste para los desarrolladores. Este proyecto desarrollara un videojuego centrándose en la rejugabilidad y tratando de abaratar al máximo los costes del diseño y desarrollo. Tales from Vorkov City is an adventure game created for mobile devices. Throughout the following document will detail its design and implementation. The purpose of this project is to create an adventure game with procedurally generated puzzles in order to add replayability, along with a branching story, which will allow the player to create his own story without repeating the same puzzles he did the first time. The player to make his own story without repeating the same puzzles he did the first time. In this way we aim to encourage the player to embark on the adventure more than once knowing that the challenges they will encounter will not be the same as the previous times. With this we get a greater motivation to enjoy more hours of gameplay at a lower cost for the developers. This project will develop a videogame focusing on replayability and trying to reduce design and development costs as much as possible.

The growing need of technological assistance to provide support to people with special needs demands for systems more and more efficient and with better performances. With this aim, this work tries to advance in a multirobot platform that allows the coordinated control of different agents and other elements in the environment to achieve an autonomous behavior based on the user’s needs or will. Therefore, this environment is structured according to the potentiality of each agent and elements of this environment and of the dynamic context, to generate the adequate actuation plans and the coordination of their execution.

El L-System és una tècnica procedural que es basa amb la reescriptura de gramàtica basat amb regles i símbols. Les aplicacions que té són molt diverses, en aquest projecte ens centrarem amb la generació de vegetació. Donat que hi ha una manca important d’informació respecte els L-System en targes gràfiques, el propòsit principal és aconseguir una implementació d’un L-System dins una tarja gràfica. A més a més, aprofitant les capacitats de les targes gràfiques, un segon propòsit és aconseguir generar diferents arbres amb temps molt baixos de càlcul.

Este trabajo tiene como objetivo la creación de un chat bot para facilitar el acceso a la información del curso actual a los estudiantes de la escuela. La disponibilidad de bot estaría en una chat web y en aplicaciones de mensajería instantánea como Skype, Telegrama o Messenger. Ejemplos de la información a consultar seria horarios de clase y calendarios, consulta de fecha de exámenes y horarios de consulta del profesorado. Tecnologías a usar El trabajo usará tecnologías Microsoft para el desarrollo del bot. Las principales herramientas serán: · Microsoft Visual Studio 2017: Entorno de desarrollo integrado . · Azure Bot Service: Servicio de alojamiento web para el bot de Microsoft. · Lenguaje de desarrollo del bot: C#. · Azure Web Service: Servicio de alojamiento web de Microsoft. · Lenguaje de desarrollo de los entornos web: HTML y . · Microsoft SQL Server: Entorno de gestión de la base de datos que usará el bot. · Lenguaje de la base de datos: SQL. The present work aims to propose and implement a chatbot as a new information channel for the student who should be able to provide the academic information of the ETSETB regarding schedules, calendar and dates of final exams. This project aims to provide a design methodology for an extensible chatbot in different cases where, starting from a web with the information to be consulted, the guidelines are established to generate a chatbot. For the development of software throughout the project, Microsoft's languages, technologies and software have been used mainly. Specifically, the languages and tools used are mentioned: C # to develop the chatbot, Visual Studio as a development environment and Azure as a cloud environment to deploy web services. It should be noted that the chatbot to be designed has an interaction based on a dialog structure with buttons that guides the user in the queries that he wants to make. The main advantage of this design is simplicity, since each dialogue manages a different phase of the conversation. The final result of the project is a chatbot that can talk in Spanish, Catalan and English, and solve the user's queries in relation to the academic information discussed at the beginning of this section, but limited to the database created for this project. El presente trabajo tiene como objetivo proponer e implementar un chatbot como un nuevo canal de información al estudiante que ha de ser capaz de facilitar la información académica de la ETSETB relativa a horarios, calendario y fechas de exámenes finales. Este proyecto pretende aportar una metodología de diseño de un chatbot extensible a diferentes casos en donde, partiendo de una web con la información a consultar, se establezcan las pautas para generar un chatbot. Para el desarrollo de software en todo el proyecto se han usado principalmente lenguajes, tecnologías y software de Microsoft. Concretamente entre los lenguajes y herramientas usadas se mencionan: C# para desarrollar el chatbot, Visual Studio como entorno de desarrollo y Azure como entorno cloud para desplegar los servicios webs. Se ha de destacar que el chatbot a diseñar tiene una interacción basada en una estructura de diálogos con botones que guía al usuario en las consultas que quiera realizar. La principal ventaja de este diseño es la sencillez ya que cada diálogo gestiona una fase diferente de la conversación. El resultado final del proyecto es una chatbot capaz de dialogar en castellano, catalán e inglés, y solventar las consultas de los usuarios en relación con la información académica comentada al principio de esta sección, pero limitada a la base de datos creada para este proyecto. El present treball té com a objectiu proposar i implementar un chatbot com un nou canal d'informació a l'estudiant que ha de ser capaç de facilitar la informació acadèmica de l'ETSETB relativa a horaris, calendari i dates d'exàmens finals. Aquest projecte pretén aportar una metodologia de disseny d'un chatbot extensible a diferents casos on, partint d'una web amb la informació a consultar, s'estableixin les pautes per generar un chatbot. Per al desenvolupament de programari en tot el projecte s'han fet servir principalment llenguatges, tecnologies i programari de Microsoft. Concretament entre els llenguatges i eines usades s'esmenten: C # per desenvolupar el chatbot, Visual Studio com a entorn de desenvolupament i Azure com a entorn cloud per desplegar els serveis webs. S'ha de destacar que el chatbot a dissenyar té una interacció basada en una estructura de diàlegs amb botons que guia a l'usuari en les consultes que vulgui realitzar. El principal avantatge d'aquest disseny és la senzillesa ja que cada diàleg gestiona una fase diferent de la conversa. El resultat final del projecte és una chatbot capaç de dialogar en castellà, català i anglès, i solucionar les consultes dels usuaris en relació amb la informació acadèmica comentada al principi d'aquesta secció, però limitada a la base de dades creada per a aquest projecte.

The aim of this thesis is to describe and develop in detail the implementation of a Dynamic Health Data Aggregation System for research purposes in the framework of ISyPeM2. The motivation of this work responds to the need of simple, efficient and secure systems to perform medical research using patient sensitive data, which for the time being is handicapped by several requirements such as previously established agreements between institutions, heterogeneous databases and privacy issues. This thesis aims to document the implementation of a system that addresses these issues. To implement the system, we used the principles of P2P networks for discovery of data sources (the nodes in the system), the functionality of a Multi-Agent System for coordination between data sources and the use of anonymization techniques to preserve the patient’s privacy. The thesis first examines the motivation and application for such systems, as well as the concepts needed to understand the components that conform the system and then it will proceed to present the state of the art for similar or related systems and technologies being developed for the same purpose. Afterwards, the components in the implementation will be detailed. After that, there is an in-depth explanation on how the system works and the components it is comprised, along with other implementation details, as well as a description of the development environment. In the final chapters, the results from the tests performed and the conclusions of this work will be presented, and in the appendices, there is a description of the datasets used for the performance tests, as well as the last review of the implementation code. L’objectiu d’aquesta tesi és descriure amb detall el desenvolupament e implementació d’un Sistema d’Agregació de Dades Mèdiques per a la recerca en el marc de ISyPeM2. La motivació d’aquest treball respòn a la necessitat de sistemes senzills, efficients i segurs per realitzar investigació mèdica fent servir dades sensibles dels pacients. En aquests moments, aquests sistemes són limitats per varis requeriments com acords preestablerts entre institucions, bases de dades heterogenies i problemes de privacitat. Aqueta tesi documenta la implementació d’un sistema que adreça aquests problemes. Per implementar el sistema, utilitzem els principis de xarxes P2P per descobrir les fonts de dades (els nodes del sistema), la funcionalitat de Sistemes Multi Agent per la coordinació entre fonts de dades i l’ús de tècniques d’anonimització per preservar l’identitat del pacient. Aquesta tesi primer examina la motivació i aplicació d’aquests sistemes, com també els conceptes necessaris per comprendre els components que el formen, després es procedirà a presentar el State of the art per veure tecnologies similars o relacionades que estiguin sent desenvolipades amb el mateix propòsit. A continuació ens capbussarem en els components de la implementació. Després hi ha una explicació detallada de com funciona el sistema i els components que el formen, junt amb altres detalls de la implementació i una descripció de l’entorn de desenvolupament. En els últims capítols, es presentaràn els resultats dels test que s’han dut a terme. En els apèndixs s’inclou una descripció dels datasets que s’han fet servir pels experiments, juntament amb una còpia de l’última revisió del codi de l’implementació final. El objetivo de esta tésis es describir con detalle el desarrollo e implementación de un Sistema de Agregación de Datos Médicos para la investigación en el marco de ISyPeM2. La motivación de este trabajo responde a la necesidad de sistemas sencillos, eficientes y seguros para realizar investiación médica utlizando datos sensibles de los pacientes. Actualmente, estos sistemas estan limitados por varios requerimimentos como acuerdos preestablecidos entre instituciones, bases de datos heterogéneas, y problemas de privacidad. Esta tésis documenta la implementación de un sistema que trata estos problemas. Para implementar el sistema, utilizamos los principios de redes P2P para descubrir las fuentes de datos (los nodos del sistema), la funcionalidad de Sistemas Multi Agente para la coordinación entre fuentes de datos y el uso de técnicas de anonimización para preservar la identidad del paciente. Esta tesis primero indaga en la motivación y la aplicación para estos sistemas, como también en los conceptos necesarios para entender los componentes que conforman el sistema, luego se procederá a presentar el State of the art para ver tecnologías similares o relacionadas que estén siendo desarrolladas con el mismo propósito. A continuación entraremos de cabeza en los componentes de la implementación. Después hay una explicación detallada de como funciona el sistema y los componentes que lo forman, junto con otros detalles de la implementación y una descripción de el entorno de desarrollo. En los últimos capítulos, se presentarán los resultados de los test que se han llevado a cabo. En los apéndices se incluye una descripción de los datasets utilizados para los experimentos, junto con una copia de la última revisión del código de la implementación final.

This Bachelor Thesis aims to draw a first approach for building a highly versatile tool to simulate systems with adaptive modularity, that is, systems that are able to adapt their functional capabilities according to the type of mission or scanario they are involved into. The simulation framework follows an agent-based strategy, in which several agents with different roles (launcher, scenario, active agent) manage to accomplish missions. These missions consist of performing certain tasks of target observation in one or more spectral region (e.g, microwave, infrared, visible) with a certain set of temporal requirements and a score value. The goal of the system is to perform as many high-value observations as possible. If certain tasks require more requirements than a single agent can provide, it can build a coalition with other agents, which do carry enough resources for performing the task. These coalitions are temporal associations of agents that can be split or merged as considered by them, thus allowing the agents to adapt their modularity for better performing their mission. The main achievements attained in this thesis can be divided in two blocks: on the one hand, we have developed a support program using an open source Java-based platform that executes simulations upon a large set of possible scenarios (Turtlekit ), displays what agents are doing in real-time in a particular simulated case and stores their performance data for its posterior analysis; on the other hand, a widely known decentralized task allocation algorithm (Coupled Constraint Consensus Bundle-Based Algorithm, CCBBA) has been implemented and modiffied as necessary for handling speciffic constraints regarding adaptive modularity.

Realizar un Bot de Slack (chat / canal de comunicación multigrupo) que interprete lenguaje natural (via wit.ai) y realice consultas en gira imprimiendo la respuesta formateada en el canal Slack correspondiente. Avui en dia es indispensable el treball en equip per a dur a terme qualsevol tipus de projecte. Per a la gestió d’aquest treball apareixen infinitat d’eines en les que es necessari documentar totes les tasques que es van realitzant. A mesura que els equips creixen, creix també el volum d’informació emmagatzemada y per tant la complexitat del tractament d’aquesta informació. A més a més, poden haver-hi persones externes al projecte a les que també els podria ésser necessari l’accés a aquesta informació, però que careixen dels permisos per accedir a aquestes eines o en desconeixen el funcionament. Es per això que es va decidir programar un software per a facilitar una consulta interactiva a la informació dels projectes. Aquest software implementa el comportament d’un usuari robot dins d’una eina web de xat corporatiu, que mitjançant un intèrpret de llenguatge natural, entén les peticions de l’usuari, i segons aquestes, accedeix a la base de dades amb la informació del projecte i ens retorna la informació sol·licitada. Així, qualsevol persona amb accés al canal de xat del projecte en qüestió, pot conversar amb l’usuari robot i obtenir informació útil sobre el progrés de les tasques del projecte d’una manera ràpida i automatitzada, sense la necessitat de conèixer el funcionament de l’eina utilitzada per l’equip, ni haver d’interrompre a ningú per obtenir la informació. Finalment, el software és ampliable a noves funcionalitats que poguessin requerir altres projectes en els que s’instal·lés l’usuari robot. Ja que les funcionalitats es troben en fitxers separats i aquestes es carreguen a mesura que el robot interpreta que l’usuari vol utilitzar-les. El trabajo en equipo es hoy en día indispensable para la ejecución de cualquier tipo de proyecto. Para la gestión de este trabajo aparecen multitud de herramientas, en las que es necesario documentar todo el trabajo que se va realizando. A medida que estos equipos crecen, crece también el volumen de información almacenado y por tanto la complejidad del tratamiento de esta información. Además, podemos tener personas externas al proyecto para las que también podría ser necesario el acceso a dicha información, pero que carecen de permisos para acceder a las herramientas o desconocen su funcionamiento. Por eso se decidió programar un software para facilitar una consulta interactiva a la información de los proyectos. Este software implementa el comportamiento de un usuario robot dentro de una herramienta web de chat corporativo que, mediante un intérprete de lenguaje natural, interpreta las peticiones del usuario y, según éstas, accede a la base de datos del proyecto, y devuelve la información requerida. Así, cualquier persona con acceso al canal de chat del proyecto en cuestión puede conversar con el usuario robot y obtener información útil del progreso de las tareas dentro del proyecto de una forma rápida y automatizada, sin necesidad de conocer el funcionamiento de la herramienta utilizada por el equipo, ni tener que interrumpir a nadie para obtener dicha información. Finalmente, el software se ha implementado para ser extensible a nuevas funcionalidades que puedan requerir otros proyectos en los que se instale el usuario robot: las funcionalidades se han diseñado como objetos ejecutables separados que se cargan a medida que el robot interpreta que el usuario necesita esa funcionalidad. Teamwork is nowadays present in any kind of project that we want to do. To manage the work to be done in the projects, there are dozens of tools where we can follow the track of all the tasks that the team is doing. The bigger the teams are, the more difficult is to deal with all that information registered. On the top of that, we could have people from outside the project we are working in, that would also need to have access to the information stored in that tools and that they may not know how to access it. That’s the reason why it was needed to create some software to provide and interactive access to the information of the projects. This software implements the behavior of a bot user inside a corporative web chat. With a natural language interpreter it would understand the users needs and according to them, access the database of the project and return the requested information. In that way, any person with access to the chat of the project can talk to the bot user and get quick and useful information of the progress of the tasks within the project. Without the need to know how to use the tool used in the team to store that information, and without interrupting any colleague to check the information for them. Lastly, this software has been designed to be extendible to new functionalities that other teams could need, so that we can reuse this bot for different teams. The functionalities have been design as separated pieces of code that are loaded as they are needed depending on the users demands.

The purpose of this project is to analyze the railway context presenting the evolution of the different systems. For one of their functions, the train identification on the track on moving block, it is presentes both the existing limitations today and a system architecture and specification of an alternative solution based on axle counter technology. El objetivo de dicho proyecto es analizar el contexto ferroviario, presentando la evolución de los diferentes sistemas. Para una de sus funciones, la identificación de vehículos en la vía en bloco móvil, se presentan tanto las limitaciones existentes hoy en día como la arquitectura y las especificaciones sistema de una solución alternativa basada en la tecnología de contadores de ejes. L'objectiu d'aquest projecte és analitzar el contexte ferroviari presentant l'evolución dels diferents sistemes. Per una de les seves funcions, l'identificació de vehicles a la via en bloc mòvil, es presenten tant les limitacions existens aviu en dia com l'arquitectura i l'especificació sistema d'una solució alternativa basada en comptadors de eixos.

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

Extended version / Versió extesa Agent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models such as policy studies, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.

Changes in our society have created a challenge for policymakers, who confront a need of tools to evaluate the possible effects of their policies. Agent-based modelling and simulation is a promising methodology which can be used in the study of population dynamics. In this paper we introduce an agent-based simulation approach to project the population of Gambian migrants in Spain during 10 years. Our approach not only enables to simulate the life course of individuals, but also allows deeping on the movements, interactions, and behaviours of the target population. The model is able to capture individual characteristics and to overcome some data-related limitations with assumptions on behavioural rules. With this methodology, we want to show the potential of the tool with the study of a real case scenario.

Treball realitzat a la Technische Universität Darmstadt. Fachbereich Elektrotechnik und Informationstechnik

Since introduction of the European qualifications framework (EQF) as one instrument to bridge from learning institutions to competence driven lifelong learning, it remains a challenge for instructors and teachers in higher education to make efficient use of this framework for designing, monitoring, and managing their lessons. This paper presents a software suite for enabling teachers to make better use of EQF in their teaching. The software suite extends course design based on well-defined learning outcomes, monitoring performance and competence acquisition according to the EQF levels, assessment using scoring rubrics of EQF levels and competences in a 360-degree feedback, as well as visualizations of learning analytics and open student models in dashboards for different social perspectives in social planes. This paper includes a case study with 20 teachers who used the software suite in all phases of the course lifecycle for three programming courses. The results show that integrated applications for adopting the EQF in teaching practice are strongly needed. These results also show that the suite can assist teachers in creating contextual awareness, kindling reflection, understanding students and course progress, and inferring patterns of success and failure in competences development The authors thank the University of Valle for funding the research of Beatriz Florian-Gaviria. The presented work was partly sponsored by the ARrELS Project (TIN2011-23930) and funded by the Spanish Government. Further, they thank the University of Valle and University of Girona for the support in conducting the classroom study with their staff. Last but not the least, they thank Hendrik Drachsler and Marcus Specht from the Open University of the Netherlands for their kind support and collaboration with the related research throughout 2011 and 2012

[ANGLÈS] Adaptation of the decision unit "Artificial Recognition System", that was running in a simple simulator created on purpose to test the ARS decision unit into a more complex environment which is not created on purpose for the ARS. Check of the correct behaviour of the decision unit in the new environment afterwards. [CASTELLÀ] Adaptación de la unidad de decisión "Artificial Recognition System", que hasta ahora solamente funcionaba en un simulador sencillo creado a propósito para el testeo de ARS a un entorno más complejo y no creado a propósito para el ARS. Comprobación posterior del correcto funcionamiento de la unidad de decisión en el entorno nuevo. [CATALÀ] Adaptació de la unitat de decisió "Artificial Recognition System", que fins ara només treballava en un simulador senzill creat a propòsit per a testejar l'ARS a un entorn més complex i no creat a propòsit per a l'ARS. Comprovació posterior del correcte funcionament de la unitat de decisió en l'entorn nou.

Las políticas de gestión de la calidad del agua a nivel de cuenca hidrográfica son especialmente importantes para la prevención y/o reducción de la polución originada por el hombre en el medio ambiente. Los efluentes industriales son un elemento prioritario particularmente en los Sistemas Urbanos de Aguas Residuales (SUAR) que reciben mezcladas las aguas residuales provenientes de viviendas particulares y de industrias, así como el agua de lluvia. En este artículo, presentamos un análisis y una implementación de agentes normativos que capturan las regulaciones específicas de las políticas Catalanas de prevención de la polución. La implementación de los agentes normativos está basada en el Cálculo de Situaciones. // Water quality management policies on a river basin scale are of special importance in order to prevent and/or reduce environmental pollution caused by human sources. Industrial effluents are a priority issue particularly in Urban Wastewater Systems (UWS) that receive mixed household and industrial wastewaters, apart from rainfall water. In this paper, we present an analysis and implementation of normative agents that capture concrete regulations of the Catalan pollution- prevention policies. The implementation of the normative agents is based on Situation Calculus.

Projecte realitzat en el marc d'un programa de mobilitat amb la Vienna University of Technology. [ANGLÈS] Implementation of an artificial intelligence model based on the psychoanalytic theory of the ID-Ego-SuperEgo of Sigmund Freud into the computer game Unreal Tournament 2004. [CASTELLÀ] Implementación de un modelo de inteligencia artificial basado en la teoría psicoanalítica del ID-Ego-SuperEgo de Sigmund Freud en el videojuego Unreal Tournament 2004. [CATALÀ] Implementació d'un model d'intel·ligència artificial basat en la teoria psicoanalítica de l'ID-Ego-SuperEgo de Sigmund Freud en el videojoc Unreal Tournament 2004.

English: The goal of this thesis is to study the viability of an IDSS based on a LFAC. At the end, we intend to develop a complete IDSS application based on a LFAC which implements a real domain and which can be put to use in real scenarios. This thesis will focus on the problems combining two disciplines as di erent as IDSS and LFAC in order to make them work autonomously and transparently. We will work with the domain of a HSCW, a very common

Projecte final de carrera fet en col.laboració amb Leibniz Universtät Hannover Català: Avui en dia la vigilancia de grans àreas, com ara bancs, aeroports o ciutats es basa principalment en sistemas de video. Les Active Cameras (ACs) juguen un paper important per als sistemes de seguretat, ja que combinen video detecció, processament de video i comunicació en un sol dispositiu. Un punt feble és que les ACs son generalment fixes i poden apareixer oclusions que poden crear punts cecs al sistema. Aquests punts cecs poden ser superats mitjançant l?ús de ACs mòbils crean una xarxa mòbil, anomenada Active Camera Network (ACN), presentades en aquesta tesi. No obstant això, la mobilitat de les ACs ve juntament amb desafiaments en termes de coordinació i configuración. A més d?això, el cost de les ACs es més gran en comparació a les xarxes de cameres estatiques, però el nombre de guàrdies necessaris per inspeccionar una gran àrea com una ciutat per exemple o per controlar una gran quantitat de monitors es pot reduir considerablement amb les ACNs. El nostre objectiu és implementar l?arquitectura de un sistema auto-reconfigurable per una xarxa de ACs que poden anar muntades en robots mòbils pel terra o en microvehicles aeris (MAV). Així, les ACs decidirán per si mateixes on actualizar la seva posición per tal d?aconseguir un rendiment òptim del sistema. Per assolir aquest objectiu, les ACs aumentaran o disminuiran les regions espacials redundants amb el seus veïns fent focus en les regions mes sobrecarregades. El protocol presentat en aquesta tesi adapta la posición de les ACs per detectar les diferents trajectories que travessan la zona de vigilancia i que poden evolucionar amb el temps. Les simulacions han demostrat que el protocol presentat augmenta el rendiment general del sistema fins un 190% més gràcies a la reconfiguració i cooperación entre les ACs veïnes. Castellano: Hoy en día la vigilancia de grandes áreas, tales como bancos, aeropuertos o ciudades se basa principalmente en sistemas de video vigilancia. Las Active Cameras (ACs) juegan un papel importante para los sistemas de seguridad, ya que combinan video detección, procesamiento de video y comunicación en un solo dispositivo. Un punto débil es que las ACs son generalmente fijas y pueden aparecer oclusiones que creen puntos ciegos en el sistema. Estos puntos ciegos pueden ser superados mediante el uso de ACs móviles creando una red móvil, llamada Active Camera Network (ACN), presentadas en esta tesis. Sin embargo, la movilidad de las ACs viene junto con desafíos en términos de coordinación y configuración. Además de esto, el coste de las ACs es mayor en comparación a las redes de cámaras estáticas, pero el número de guardias necesarios para inspeccionar una gran área como una ciudad por ejemplo o para controlar una gran cantidad de monitores se puede reducir considerablemente con las ACNs. Nuestro objetivo es implementar la arquitectura de un sistema auto-reconfigurable para una red de ACs que pueden ir montadas en robots móviles por el suelo o en micro vehículos aéreos (MAV). Así, las ACs decidirán por sí mismas donde actualizar sus posiciones con el fin de conseguir un rendimiento óptimo del sistema. Para alcanzar este objetivo, las ACs aumentarán o disminuirán las regiones espaciales redundantes con sus vecinos haciendo foco en las regiones más sobrecargadas. El protocolo presentado en esta tesis adapta la posición de las ACs para detectar las diferentes trayectorias que atraviesan la zona de vigilancia y que pueden evolucionar con el tiempo. Las simulaciones han demostrado que el protocolo presentado aumenta el rendimiento general del sistema hasta un 190% más gracias a la reconfiguración y cooperación entre las ACs vecinas. English: Nowadays surveillance of large areas, such as banks, airports or cities is mostly based on vision systems. Smart Cameras (SCs) play an important role for security systems as they combine video sensing, video processing and communication within a single device. One weak point is that SCs are usually stationary and so occlusions may create blind spots in the system. These blind spots may be overcome by using mobile SCs, so called Active Camera Networks (ACNs), as introduced in this thesis. Nevertheless, mobility of SCs come along with challenges in terms of coordination and configuration. In addition to this, the cost of ACs is higher in comparison to static camera networks but the number of guards needed to survey a large area like a city or to control a lot of monitors can be reduced considerably with AC networks. Our goal is to implement a self-reconfiguration system architecture for networked smart cameras that could be mounted either on mobile robots on the ground or Micro Air Vehicles (MAVs). Thus, the ACs will decide by themselves where to update their position in order to achieve the optimal system's performance. To reach that goal, ACs will increase or decrease spatial redundancy regions with their neighbours to overcome overloaded regions. The protocol presented in this thesis adapts the position of the ACN to the different trajectories that traverse a surveillance area over time. The simulations have shown that the presented protocol increase the overall performance due to the node reconfiguration and cooperation between neighbouring ACs.

Estudi i implementació d'un sistema multiagent intel·ligent i la seva aplicació a sistemes difusos. Utilització de les llibreries JADE i JFuzzyLogic. Study and implementation of an intelligent multi-agent system and its application to fuzzy systems. Using the JADE libraries and JFuzzyLogic. Estudio e implementación de un sistema multiagente inteligente y su aplicación a sistemas difusos. Utilización de las librerías JADE y JFuzzyLogic.

Projecte fet en col.laboració amb Centre Tecnològic de Telecomunicacions de Catalunya Català: En les Xarxes Docents es por ta més enllà la idea d'elaborar decisions intel ligents. Per mitjà de compartir informació entre els nodes, amb l'objectiu primordial de reduir la complexitat i millorar el rendiment de les Xarxes Cognitives. Per a això es revisen alguns conceptes importants de les bases de l'Aprenentatge Automàtic, prestant especial atenció a l'aprenentatge per reforç. També es fa una visió de la Teoria de Jocs Evolutius i de la dinàmica de rèpliques. Finalment, simulacions ,basades en el projecte TIC-BUNGEE, es mostren per validar els conceptes introduïts. Castellano: Las Redes Docentes llevan más alla la idea de elaborar decisiones inteligentes, por medio de compartir información entre los nodos, con el objetivo primordial de reducir la complejidad y mejorar el rendimiento de las Redes Cognitiva. Para ello se revisan algunos conceptos importantes de las bases del Aprendizaje Automático, prestando especial atencion al aprendizaje por refuerzo, también damos una visón de la Teoría de Juegos Evolutivos y de la replicación de dinamicas. Por último, las simulaciones basadas en el proyecto TIC-BUNGEE se muestran para validar los conceptos introducidos. English: The Docitive Networks further use the idea of drawing intelligent decisions by means of sharing information between nodes with the prime aim of reduce complexity and enhance performance of Congnitive Networks. To this end we review some important concepts form Machine Learning, paying special atention to Reinforcement Learning, we also go insight Evolutionary Game Theory and Replicator Dynamics. Finally, simulations Based on ICT-BUNGEE project are shown to validate the introduced concepts.

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems.

Water quality management policies on a river basin scale are of special importance in order to prevent and/or reduce pollution of several human sources into the environment. Industrial effluents represent a priority issue particularly in Urban Wastewater Systems (UWS) that receive mixed household and industrial wastewaters, apart from rainfall water. In this paper, we present an analysis and an implementation of normative agents which capture concrete regulations of the Catalan pollution-prevention policies. The implementation of the normative agents is based on situation calculus.