From the end of 80's there has been a great interest in the study of qualitative models to represent and to reason with spatial aspects. The present work is centred in the development and application of a model to reason about the shape and about the movement in a qualitative way, which means in a way similar to the human reasoning. The interest of this study is originated in the necessity of solutions for the recognition of objects and the description and reasoning about the movement in situations with high uncertainty, as it is the case of robotic applications, where robots only have limited and vague sensorial information. In these situations the use of a qualitative reasoning, that allows us to handle ambiguities and errors, will be the most suitable.The movement of an object can be considered as a shape whose topologic relation with its environment (considered as another shape) changes in the time. On the other hand the shape of the objects is a spatial aspect in itself, and again for its study we have used topological concepts. The recognition of objects is important during the movement of a robot since for the accomplishment of certain tasks the robot must be able to recognize the objects with which it is finding during its trajectory, since these objects can be landmarks or reference points that provides to the robot spatial information of its environment.Therefore this work will be centred in the study of three space aspects: the shape of the objects, the topology and the movement. Several works exist about the shape of the objects [Jungert 94; Park and Gero 99, 00; Chase 96, 97; Shokoufandeh, Dickinson et al. 02], on topology [Cohn, Bennet ET al. 97; Renz & Nebel 98; Egenhofer & Franzosa 91; Clementini & Di Felice 95] and on movement [Zimmermann and Freksa 93; Musto, Stein et al. 00; Musto et al. 99; Rajagopalan and Kuipers 94; Forbus 83; Muller 98a, 98b]. However, most of these works are theoretical and they have not been applied to robotics.This PhD thesis presents a motion model as a qualitative representational model for integrating qualitatively time and topological information for reasoning about dynamic worlds in which spatial relations between regions and between regions and objects may change with time. This qualitative integration of time and topology has been accomplished thanks to the definition of an approach with the following three steps: (1) the definition of the algebra of the spatial aspect to be integrated, which will be time and topology. The representation of each aspect is seen as an instance of the Constraint Satisfaction Problem (CSP); (2) the definition of the Basic Step of the Inference Process (BSIP) for each spatial aspect to be integrated. In general, the BSIP consists on given two relationships which relate three objects A, B, and C (one object is shared among the two relationships, for instance A is related with B and B is related with C), we will find the third relationship between objects A and C; and (3) the definition of the Full Inference Process (FIP) for each spatial aspect to be integrated which consists on repeating the BSIP as many times as possible with the initial information and the information provided by some BSIP, until no more information can be inferred.On the other hand, the theory for the recognition of shapes developed is able to describe several types of shapes, as they are regular and non-regular polygons, with or without holes, with or without curved segments and even completely curvilinear forms. The theory describes shapes considering qualitatively the angles, relative side length, concavities and convexities, and types of curvatures of their boundaries using only their relevant points, which are defined as vertices, and the initial, final point and point of maximum curvature of the curves. To describe shapes with holes, topological and qualitative spatial orientation aspects have been considered in order to relate the hole with its container. Each object is described by a string which describes its qualitative distinguished features (symbolic representation), which is used to match an object against the others. This theory has been applied, in an industrial domain, for the automatic and intelligent assembly of ceramic mosaics. Mosaics are made of pieces of different shapes, colours and sizes, named tesseraes, that once they are assembled they create a unique composition with high added value, due its artist and decorative value. Mosaics are made usually following a design describing the position of each tesserae in the final composition. The application developed in this dissertation, recognise individual tesseraes from pictures, which represent the tesserae coming over a conveyor, against a vectorial mosaic design. Therefore, the application returns the position of the tesserae in the mosaic together with the angle that a robot arm has to do when picking the tesserae by its centroid in order to leave it in the correct orientation inside the mosaic. On the other hand the simplest version of this theory, in concrete the part that describes regular and non-regular polygonal objects, jointly with the developed theory of movement has been applied too for the simulated navigation of a real robot, in concrete of the Khepera2 robot. This application consists in a world formed by two rooms connected by a corridor. The robot first learns the topological map of the world. Then in each room there is an object and the robot has to decide if both objects represent the same object or not, for that purpose the robot uses the movement theory to plan the way to do and to detect possible deviations during its moving, and finally by using the qualitative theory for shape matching developed decides if the objects has the same shape or not.

Fuzzy logic has been applied successfully to systems modeling for ages. One of its main advantages is that it provides an understandable knowledge representation. Nevertheless, most investigations have focused their efforts on achieving accurate models and by doing so, they have omitted the linguistic capabilities of fuzzy logic.This thesis researches into the issues related to intelligible fuzzy models, because since science demonstrated the use of fuzzy logic when searching optimal models in terms of error (in fact a fuzzy model is a universal approximator), some but few investigators have focused their efforts in order to achieve really intelligible models in spite of losing some accuracy.In this work we propose a whole methodology able to find an intelligible fuzzy model in a local manner (rule by rule) from input-output data. In this sense we find the number and position of the necessary fuzzy sets and also the linguistic rules related to them. For this purpose we have developed a hierarchical process which takes into account several steps and techniques, some of which are original contributions.The resulting method is very simple and also intelligible. Therefore, this solution performs the final models with a low computational cost, but furthermore, allows the tuning of its different options depending on the nature of the problem and the characteristics of the users.In this thesis we explain the whole methodology and illustrate its advantages (but also its problems) with several examples which are benchmarks in most cases.

Technology-Enhanced Assessment (TEA) has become increasingly attractive in higher education. However, the nature of such assessments has often been limited to simple type of questions such as MCQs, which are usually knowledge-based. Cognitive skills and practical abilities cannot be assessed via simple types of questions. This raised the need to introduce interactive and intelligent dimensions into e-assessment. This research provides a new learning experience for students in both skill and knowledge assessment in online education. This was achieved through a design of a general TEA system which can be adapted to any context and an architecture that allows interoperability, security and integration of modules. The system also provides student, interactivity and the opportunity to act on the feedback through a proposed formative e-assessment model. After application of the system in the real context, it was observed that the use of the TEA system and the formative e-assessment model had a positive impact on students: they learned through engagement with the system and their performance in terms of final marks had improved. The system also provided added benefits to teachers through automated marking and tracking of students' progress throughout the whole course. Finally, with the ever increasing interests and adaptation of e-assessment, this research has produced a new perspective, not only theoretical but practical as well.

Aquest treball de tesi doctoral fa una aportació a les àrees de l'e-learning i la interacció persona-ordinador, en relació a l'obtenció d'informació dels usuaris i de l'ús que fan d'un sistema interactiu. Per a assolir aquest objectiu s'ha proposat una metodologia d'anàlisi que es basa en un estudi a tres nivells que permet abastar els objectius i motivacions dels usuaris en diferents períodes de temps. Concretament, s'ha definit una metodologia que permet obtenir informació rellevant de la navegació dels estudiants d'un entorn virtual d'aprenentatge, entenent que ho fan no només pels espais i serveis del campus virtual, sinó també pels continguts, activitats i recursos educatius de les assignatures, així com per les assignatures d'una o més titulacions i ofertes formatives, és a dir, a diferents nivells. Aquest objectiu es basa en la necessitat de conèixer als estudiants i les seves interaccions amb l'entorn virtual, per així poder millorar la usabilitat del sistema i la seva experiència d'ús, i aportar informació a un model d'usuari que permeti introduir elements de personalització en el procés d'aprenentatge. Els resultats obtinguts constitueixen noves evidències sobre la UOC, el seu entorn virtual d'aprenentatge i els seus usuaris, i proporcionen informació rellevant pel nou disseny del campus virtual i per la millora i personalització del procés d'aprenentatge. / This doctoral thesis makes a contribution to the areas of e-learning and human-computer interaction, related to obtaining information about the users and about how they use interactive systems. To achieve this goal a methodology of analysis has been proposed. This methodology is based on a three level approach that allows covering the goals and motivations of the users in different periods of time. More precisely, the proposed methodology of analysis allows obtaining new and relevant information about the students' navigation in a virtual learning environment, understanding that they visit not only the main areas and services of the virtual campus, but the contents, activities and educational resources of the courses, as well as other courses that are included in their program or formative offer. That is, at different levels in different points of time. This goal is based on the need to know the students' interactions with the virtual environment, to be able to improve the usability of the system and their experience of use, and to collect information to build a user model which allows embedding elements of personalization in the learning process. The obtained results constitute new evidence about the UOC, its virtual learning environment and its users, and provide relevant information for the design of the new virtual campus and to improve and personalize the learning process.

The automatic extraction of knowledge from the world by a robotic system as human beings interpret their environment through their senses is still an unsolved task in Artificial Intelligence. A robotic agent is in contact with the world through its sensors and other electronic components which obtain and process mainly numerical information. Sonar, infrared and laser sensors obtain distance information. Webcams obtain digital images that are represented internally as matrices of red, blue and green (RGB) colour coordinate values. All this numerical values obtained from the environment need a later interpretation in order to provide the knowledge required by the robotic agent in order to carry out a task. Similarly, light wavelengths with specific amplitude are captured by cone cells of human eyes obtaining also stimulus without meaning. However, the information that human beings can describe and remember from what they see is expressed using words, that is qualitatively. The exact process carried out after our eyes perceive light wavelengths and our brain interpret them is quite unknown. However, a real fact in human cognition is that people go beyond the purely perceptual experience to classify things as members of categories and attach linguistic labels to them. As the information provided by all the electronic components incorporated in a robotic agent is numerical, the approaches that first appeared in the literature giving an interpretation of this information followed a mathematical trend. In this thesis, this problem is addressed from the other side, its main aim is to process these numerical data in order to obtain qualitative information as human beings can do. The research work done in this thesis tries to narrow the gap between the acquisition of low level information by robot sensors and the need of obtaining high level or qualitative information for enhancing human-machine communication and for applying logical reasoning processes based on concepts. Moreover, qualitative concepts can be added a meaning by relating them to others. They can be used for reasoning applying qualitative models that have been developed in the last twenty years for describing and interpreting metrical and mathematical concepts such as orientation, distance, velocity, acceleration, and so on. And they can be also understood by human-users both written and read aloud. The first contributions presented are the definition of a method for obtaining fuzzy distance patterns (which include qualitative distances such as ‘near’, far’, ‘very far’ and so on) from the data obtained by any kind of distance sensors incorporated in a mobile robot and the definition of a factor to measure the dissimilarity between those fuzzy patterns. Both have been applied to the integration of the distances obtained by the sonar and laser distance sensors incorporated in a Pioneer 2 dx mobile robot and, as a result, special obstacles have been detected as ‘glass window’, ‘mirror’, and so on. Moreover, the fuzzy distance patterns provided have been also defuzzified in order to obtain a smooth robot speed and used to classify orientation reference systems into ‘open’ (it defines an open space to be explored) or ‘closed’. The second contribution presented is the definition of a model for qualitative image description (QID) by applying the new defined models for qualitative shape and colour description and the topology model by Egenhofer and Al-Taha [1992] and the orientation models by Hernández [1991] and Freksa [1992]. This model can qualitatively describe any kind of digital image and is independent of the image segmentation method used. The QID model have been tested in two scenarios in robotics: (i) the description of digital images captured by the camera of a Pioneer 2 dx mobile robot and (ii) the description of digital images of tile mosaics taken by an industrial camera located on a platform used by a robot arm to assemble tile mosaics. In order to provide a formal and explicit meaning to the qualitative description of the images generated, a Description Logic (DL) based ontology has been designed and presented as the third contribution. Our approach can automatically process any random image and obtain a set of DL-axioms that describe it visually and spatially. And objects included in the images are classified according to the ontology schema using a DL reasoner. Tests have been carried out using digital images captured by a webcam incorporated in a Pioneer 2 dx mobile robot. The images taken correspond to the corridors of a building at University Jaume I and objects with them have been classified into ‘walls’, ‘floor’, ‘office doors’ and ‘fire extinguishers’ under different illumination conditions and from different observer viewpoints. The final contribution is the definition of a similarity measure between qualitative descriptions of shape, colour, topology and orientation. And the integration of those measures into the definition of a general similarity measure between two qualitative descriptions of images. These similarity measures have been applied to: (i) extract objects with similar shapes from the MPEG7 CE Shape-1 library; (ii) assemble tile mosaics by qualitative shape and colour similarity matching; (iii) compare images of tile compositions; and (iv) compare images of natural landmarks in a mobile robot world for their recognition. The contributions made in this thesis are only a small step forward in the direction of enhancing robot knowledge acquisition from the world. And it is also written with the aim of inspiring others in their research, so that bigger contributions can be achieved in the future which can improve the life quality of our society.