Enhancing player experience in computer games: A computational Intelligence approach.

Ph.DDOCTOR OF PHILOSOPH

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

Managing Learner’s Affective States in Intelligent Tutoring Systems

Abstract. Recent works in Computer Science, Neurosciences, Education, and Psychology have shown that emotions play an important role in learning. Learner’s cognitive ability depends on his emotions. We will point out the role of emotions in learning, distinguishing the different types and models of emotions which have been considered until now. We will address an important issue con-cerning the different means to detect emotions and introduce recent approaches to measure brain activity using Electroencephalograms (EEG). Knowing the influ-ence of emotional events on learning it becomes important to induce specific emo-tions so that the learner can be in a more adequate state for better learning or memorization. To this end, we will introduce the main components of an emotion-ally intelligent tutoring system able to recognize, interpret and influence learner’s emotions. We will talk about specific virtual agents that can influence learner’s emotions to motivate and encourage him and involve a more cooperative work, particularly in narrative learning environments. Pushing further this paradigm, we will present the advantages and perspectives of subliminal learning which inter

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

Generative Models for Novelty Detection Applications in abnormal event and situational changedetection from data series

Novelty detection is a process for distinguishing the observations that differ in some respect from the observations that the model is trained on. Novelty detection is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains observations that were not known at the training time. In other words, the novelty class is often is not presented during the training phase or not well defined. In light of the above, one-class classifiers and generative methods can efficiently model such problems. However, due to the unavailability of data from the novelty class, training an end-to-end model is a challenging task itself. Therefore, detecting the Novel classes in unsupervised and semi-supervised settings is a crucial step in such tasks. In this thesis, we propose several methods to model the novelty detection problem in unsupervised and semi-supervised fashion. The proposed frameworks applied to different related applications of anomaly and outlier detection tasks. The results show the superior of our proposed methods in compare to the baselines and state-of-the-art methods

Public Engagement Technology for Bioacoustic Citizen Science

Inexpensive mobile devices offer new capabilities for non-specialist use in the field for the purpose of conservation. This thesis explores the potential for such devices to be used by citizen scientists interacting with bioacoustic data such as birdsong. This thesis describes design research and field evaluation, in collaboration with conservationists and educators, and technological artefacts implemented as mobile applications for interactive educational gaming and creative composition. This thesis considers, from a participant-centric collaborative design approach, conservationists' demand for interactive artefacts to motivate engagement in citizen science through gameful and playful interactions. Drawing on theories of motivation, frequently applied to the study of Human-Computer Interaction (HCI), and on approaches to designing for motivational engagement, this thesis introduces a novel pair of frameworks for the analysis of technological artefacts and for assessing participant engagement with bioacoustic citizen science from both game interaction design and citizen science project participation perspectives. This thesis reviews current theories of playful and gameful interaction developed for collaborative learning, data analysis, and ground-truth development, describes a process for design and analysis of motivational mobile games and toys, and explores the affordances of various game elements and mechanics for engaging participation in bioacoustic citizen science. This thesis proposes research into progressions for scaffolding engagement with citizen science projects where participants interact with data collection and analysis artefacts. The research process includes the development of multiple designs, analyses of which explore the efficacy of game interactions to motivate engagement through interaction progressions, given proposed analysis frameworks. This thesis presents analysed results of experiments examining the usability of, and data-quality from, several prototypes and software artefacts, in both laboratory conditions and the field. This thesis culminates with an assessment of the efficacy of proposed design analysis frameworks, an analysis of designed artefacts, and a discussion of how these designs increase intrinsic and extrinsic motivation for participant engagement and affect resultant bioacoustic citizen science data quantity and quality.Non

Socially intelligent robots that understand and respond to human touch

Touch is an important nonverbal form of interpersonal interaction which is used to communicate emotions and other social messages. As interactions with social robots are likely to become more common in the near future these robots should also be able to engage in tactile interaction with humans. Therefore, the aim of the research presented in this dissertation is to work towards socially intelligent robots that can understand and respond to human touch. To become a socially intelligent actor a robot must be able to sense, classify and interpret human touch and respond to this in an appropriate manner. To this end we present work that addresses different parts of this interaction cycle. The contributions of this dissertation are the following. We have made a touch gesture dataset available to the research community and have presented benchmark results. Furthermore, we have sparked interest into the new field of social touch recognition by organizing a machine learning challenge and have pinpointed directions for further research. Also, we have exposed potential difficulties for the recognition of social touch in more naturalistic settings. Moreover, the findings presented in this dissertation can help to inform the design of a behavioral model for robot pet companions that can understand and respond to human touch. Additionally, we have focused on the requirements for tactile interaction with robot pets for health care applications

Visualizing and Predicting the Effects of Rheumatoid Arthritis on Hands

This dissertation was inspired by difficult decisions patients of chronic diseases have to make about about treatment options in light of uncertainty. We look at rheumatoid arthritis (RA), a chronic, autoimmune disease that primarily affects the synovial joints of the hands and causes pain and deformities. In this work, we focus on several parts of a computer-based decision tool that patients can interact with using gestures, ask questions about the disease, and visualize possible futures. We propose a hand gesture based interaction method that is easily setup in a doctor\u27s office and can be trained using a custom set of gestures that are least painful. Our system is versatile and can be used for operations like simple selections to navigating a 3D world. We propose a point distribution model (PDM) that is capable of modeling hand deformities that occur due to RA and a generalized fitting method for use on radiographs of hands. Using our shape model, we show novel visualization of disease progression. Using expertly staged radiographs, we propose a novel distance metric learning and embedding technique that can be used to automatically stage an unlabeled radiograph. Given a large set of expertly labeled radiographs, our data-driven approach can be used to extract different modes of deformation specific to a disease