Generative neural data synthesis for autonomous systems

A significant number of Machine Learning methods for automation currently rely on data-hungry training techniques. The lack of accessible training data often represents an insurmountable obstacle, especially in the fields of robotics and automation, where acquiring new data can be far from trivial. Additional data acquisition is not only often expensive and time-consuming, but occasionally is not even an option. Furthermore, the real world applications sometimes have commercial sensitivity issues associated with the distribution of the raw data. This doctoral thesis explores bypassing the aforementioned difficulties by synthesising new realistic and diverse datasets using the Generative Adversarial Network (GAN). The success of this approach is demonstrated empirically through solving a variety of case-specific data-hungry problems, via application of novel GAN-based techniques and architectures. Specifically, it starts with exploring the use of GANs for the realistic simulation of the extremely high-dimensional underwater acoustic imagery for the purpose of training both teleoperators and autonomous target recognition systems. We have developed a method capable of generating realistic sonar data of any chosen dimension by image-translation GANs with Markov principle. Following this, we apply GAN-based models to robot behavioural repertoire generation, that enables a robot manipulator to successfully overcome unforeseen impedances, such as unknown sets of obstacles and random broken joints scenarios. Finally, we consider dynamical system identification for articulated robot arms. We show how using diversity-driven GAN models to generate exploratory trajectories can allow dynamic parameters to be identified more efficiently and accurately than with conventional optimisation approaches. Together, these results show that GANs have the potential to benefit a variety of robotics learning problems where training data is currently a bottleneck

Learning to Search in Reinforcement Learning

In this thesis, we investigate the use of search based algorithms with deep neural networks to tackle a wide range of problems ranging from board games to video games and beyond. Drawing inspiration from AlphaGo, the first computer program to achieve superhuman performance in the game of Go, we developed a new algorithm AlphaZero. AlphaZero is a general reinforcement learning algorithm that combines deep neural networks with a Monte Carlo Tree search for planning and learning. Starting completely from scratch, without any prior human knowledge beyond the basic rules of the game, AlphaZero managed to achieve superhuman performance in Go, chess and shogi. Subsequently, building upon the success of AlphaZero, we investigated ways to extend our methods to problems in which the rules are not known or cannot be hand-coded. This line of work led to the development of MuZero, a model-based reinforcement learning agent that builds a deterministic internal model of the world and uses it to construct plans in its imagination. We applied our method to Go, chess, shogi and the classic Atari suite of video-games, achieving superhuman performance. MuZero is the first RL algorithm to master a variety of both canonical challenges for high performance planning and visually complex problems using the same principles. Finally, we describe Stochastic MuZero, a general agent that extends the applicability of MuZero to highly stochastic environments. We show that our method achieves superhuman performance in stochastic domains such as backgammon and the classic game of 2048 while matching the performance of MuZero in deterministic ones like Go

The design, implementation and evaluation of a web-based learning environment for distance education

In this study, the need was emphasised to investigate the effects of using the Web in teaching students at a distance using a multi-level evaluation framework. A Web-based learning environment was designed, developed, implemented and evaluated for this purpose. Constructivist epistemology provided the basis for developing various components and developing problem-centred and interactive activities. Management, tutorial, interaction and support components were designed to work with each other to construct the learning environment, deliver course content, facilitate interaction and monitor student progress.A methodology was designed to describe and assess the learning environment in terms of access (standardisation, speed, resources, the tutor and peers), costs (types, structure, factors influencing, etc.), teaching and learning functions (quality of course objectives, materials and resources, learning approach and student achievement), interactivity (quantity and quality of student-tutor and student-peer interaction), user-friendliness (user-interface design, ease of use and navigation design) and organisational issues. The learners were Egyptian first-grade secondary school students (32), assigned randomly, and the topic selected for the course being developed was mathematics. Feedback was obtained from both learners and experts in distance education and on-line learning during the developmental and field-testing of the learning environment. Quantitative and qualitative methods (on-line student and expert questionnaires, students' logs, performance in formative evaluation, content analysis of peer discussions, achievement test and cost-analysis) were combined to gain insights into students' satisfaction with the different instructional and technical features and capabilities of the learning environment, achievement of course objectives in comparison with conventional classroom students, factors influencing their learning and perceptions and the unit cost per student study hour.The results indicated that although the learning environment and course materials were accessible, interactive, well-structured, user-friendly and achievement was successful for the on-line group, no significant differences were identified between the on-line students and traditional classroom students in overall achievement or achievement of low-order and high-order learning objectives. In addition, it is unlikely any cost saving would be made from shifting to the Internet to deliver instruction and many major factors were found to influence the development and support costs of on-line learning

Empirical studies of Quality of Experience (QoE) : A Systematic Literature Survey

Quality of Experience (QoE) is a relatively new phenomenon. The main focus of this thesis has been to conduct a systematic literature survey of research done in the field of QoE over a ten year period. The method, developed by A. Fink, has been used to survey empirical studies. A framework of QoE has been developed, which created the possibility of grouping together and analysing all the studies in a common framework. In total, 44 studies were analysed. 66 per cent of them were studies with human participants and 34 per cent of them were studies without human participants. The majority of the selected empirical studies have analysed the sub-aspect ‘satisfaction’. Among other vital sub-aspects, which were of interest to researches, were ‘usefulness’, ‘ease of use’, ‘communication’, ‘loss/packet loss’, ‘delay’, ‘bandwidth’, and ‘jitter’. The results of this survey show that different sub-aspects depend on different services. It is not enough that one sub-aspect functions very well, because most of sub-aspects are closely related to each other. Therefore, it is very important that sub-aspects, which are dependent on each other, are functioning as one group to achieve higher QoE on user experience. This thesis may contribute to deeper understanding of the phenomenon QoE. Knowledge of QoE can bring in new ideas and new possibilities for developing a new system or products for achieving satisfaction of user experience

A novel non-intrusive objective method to predict voice quality of service in LTE networks.

This research aimed to introduce a novel approach for non-intrusive objective measurement of voice Quality of Service (QoS) in LTE networks. While achieving this aim, the thesis established a thorough knowledge of how voice traffic is handled in LTE networks, the LTE network architecture and its similarities and differences to its predecessors and traditional ground IP networks and most importantly those QoS affecting parameters which are exclusive to LTE environments. Mean Opinion Score (MOS) is the scoring system used to measure the QoS of voice traffic which can be measured subjectively (as originally intended). Subjective QoS measurement methods are costly and time-consuming, therefore, objective methods such as Perceptual Evaluation of Speech Quality (PESQ) were developed to address these limitations. These objective methods have a high correlation with subjective MOS scores. However, they either require individual calculation of many network parameters or have an intrusive nature that requires access to both the reference signal and the degraded signal for comparison by software. Therefore, the current objective methods are not suitable for application in real-time measurement and prediction scenarios. A major contribution of the research was identifying LTE-specific QoS affecting parameters. There is no previous work that combines these parameters to assess their impacts on QoS. The experiment was configured in a hardware in the loop environment. This configuration could serve as a platform for future research which requires simulation of voice traffic in LTE environments. The key contribution of this research is a novel non-intrusive objective method for QoS measurement and prediction using neural networks. A comparative analysis is presented that examines the performance of four neural network algorithms for non-intrusive measurement and prediction of voice quality over LTE networks. In conclusion, the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution with a Mean Square Error (MSE) rate of 0.001 and regression value of 0.998 measured for the testing data set

A Study of Non-Linguistic Utterances for Social Human-Robot Interaction

The world of animation has painted an inspiring image of what the robots of the future could be. Taking the robots R2D2 and C3PO from the Star Wars films as representative examples, these robots are portrayed as being more than just machines, rather, they are presented as intelligent and capable social peers, exhibiting many of the traits that people have also. These robots have the ability to interact with people, understand us, and even relate to us in very personal ways through a wide repertoire of social cues. As robotic technologies continue to make their way into society at large, there is a growing trend toward making social robots. The field of Human-Robot Interaction concerns itself with studying, developing and realising these socially capable machines, equipping them with a very rich variety of capabilities that allow them to interact with people in natural and intuitive ways, ranging from the use of natural language, body language and facial gestures, to more unique ways such as expression through colours and abstract sounds. This thesis studies the use of abstract, expressive sounds, like those used iconically by the robot R2D2. These are termed Non-Linguistic Utterances (NLUs) and are a means of communication which has a rich history in film and animation. However, very little is understood about how such expressive sounds may be utilised by social robots, and how people respond to these. This work presents a series of experiments aimed at understanding how NLUs can be utilised by a social robot in order to convey affective meaning to people both young and old, and what factors impact on the production and perception of NLUs. Firstly, it is shown that not all robots should use NLUs. The morphology of the robot matters. People perceive NLUs differently across different robots, and not always in a desired manner. Next it is shown that people readily project affective meaning onto NLUs though not in a coherent manner. Furthermore, people's affective inferences are not subtle, rather they are drawn to well established, basic affect prototypes. Moreover, it is shown that the valence of the situation in which an NLU is made, overrides the initial valence of the NLU itself: situational context biases how people perceive utterances made by a robot, and through this, coherence between people in their affective inferences is found to increase. Finally, it is uncovered that NLUs are best not used as a replacement to natural language (as they are by R2D2), rather, people show a preference for them being used alongside natural language where they can play a supportive role by providing essential social cues

Computer assisted education : design, development and evaluation.

Thesis (M.Sc.)-University of Natal, 2001.Educational institutions throughout the world are increasingly facing classes of educationally, culturally and linguistically diverse student groups. At the same time economic constraints require these institutions to expand their student base and they are therefore looking to distance education and continuing education modules to meet these challenges. Simultaneously rapid advances in desktop computing capabilities and Internet delivered information have revived interest in Computer Assisted Education (CAE). The University of Natal is no exception to these trends; schools, departments and individual members of staff are increasingly exploring the possibility of using the University's computer infrastructure to assist in delivering quality education, maintaining current standards, and addressing the multiple needs of the students. To investigate these issues a CAE program was developed for use in the Nelson R. Mandela School of Medicine to investigate how students would make use 'of the technology, and to report on the development and evaluation processes of such a development. In doing so various lessons could be learnt which could inform the further development of such software at the University. In order to support the development of the CAE program an extensive literature survey into current educational theory was conducted. Its objectives were to explore and understand all the factors affecting the development and use of computer based systems as an educational tool. Particular aspects considered were • the debate between constructivist and instructivist theory in their applicability to both the medium and the subject material. • instructional styles, and with them the learning styles, that could be used to support the educational goals of the diverse student population. • instructional design methodologies that are currently used as well as media production methodologies. The goal of this aspect of the research was to advise both the development of the case study and to gain a broader understanding of the methodology that could be used for other developments. Included in this phase of the research are methods and criteria for selection of authoring systems and interface design issues in a multi-cultural multi-lingual environment. • the review of different evaluation strategies in order to incorporate appropriate evaluation in the CAE case study. • the investigation of broader sociological and historical factors that may influence the way in which CAE can be used effectively in a South African context. The presumption was that students from historically disadvantaged backgrounds and those with English as a second language would be less willing to use technological interventions than those who were more likely to have had access to computers earlier in their education. The case study set out to investigate if this presumption was valid, and if so what elements of design and delivery could facilitate these students' usage of such systems. However, these presumptions were not validated by the case study, showing the exact opposite of expectations, with more historically disadvantaged students showing a willingness to use the module

Everyday economics: ideas new and old from lay theories of economic life

This project explores divergences and parallels between lay theories of economic life as experienced and developed in two virtual worlds – Final Fantasy XI (FFXI) and Second Life (SL) – and academic theories from sociology and anthropology as well as economics. My intent is not a critique of economics, but a suggestion that other economic sociologies are possible, and to provide points of departure and ideas for such alternative configurations. Exploration of lay theories is organised around four key conceptual categories – value, exchange, money and markets – which were suggested by participants' accounts and economic organisation within each field site. Respondents' theories offer polyphonic, heteroglossic approaches to economic life that sometimes diverge substantially from academic conceptualisations. Lay theories examined in this research emphasising plurality and multiplicity – especially with respect to monies – going so far as to suggest a radical reorganisation of economies based on monies rather than markets. When lay theories from each category are pieced together, they reveal a social imaginary of boundless abundance, strong reliance upon practices as ways of knowing about and theorising economic life, and strange parellels with studies of “primitive” cultures. This dissertation is based on comparative ethnographies of two disparate virtual worlds, FFXI and SL, which offer different slant-wise views of contemporary capitalist, consumer societies. Final Fantasy XI is a proprietary massively multiplayer online role-playing game (MMORPG) created, owned and maintained by Square-Enix, while Second Life (SL) is a free-form, nonproprietary, three-dimensional virtual world created and maintained in a laissezfaire fashion by Linden Lab. Fieldwork consisted of participant observation, one-on-one interviews, group interviews with FFXI respondents and analysis of fan-made media and corporate texts