In the thesis we present a new approach to providing soft real-time guarantees for Belief-Desire-Intention (BDI) agents. We analyse real-time guarantees for BDI agents and show how these can be achieved within a generic BDI programming framework. As an illustration of our approach, we develop a new agent architecture, called AgentSpeak(RT), and its associated programming language, which allows the development of real-time BDI agents. AgentSpeak(RT) extends AgentSpeak(L) [28] intentions with deadlines which specify the time by which the agent should respond to an event, and priorities which specify the relative importance of responding to a particular event. The AgentSpeak(RT) interpreter commits to a priority-maximal set of intentions: a set of intentions that is maximally feasible while preferring higher priority intentions. Real-time tasks can be freely mixed with tasks for which no deadline and/or priority has been specified, and if no deadlines and priorities are specified, the behavior of the agent defaults to that of a non real-time BDI agent. We perform a detailed case study of the use of AgentSpeak(RT) to demonstrate its advantages. This case study involves the development of an intelligent control system for a simple model of a nuclear power plant. We also prove some properties of the AgentSpeak(RT) architecture such as guaranteed reactivity delay of the AgentSpeak(RT) interpreter and probabilistic guarantees of successful execution of intentions by their deadlines. We extend the AgentSpeak(RT) architecture to allow the parallel execution of intentions. We present a multitasking approach to the parallel execution of intentions in the AgentSpeak(RT) architecture. We demonstrate advantages of parallel execution of intentions in AgentSpeak(RT) by showing how it improves behaviour of the intelligent control system for the nuclear power plant. We prove real-time guarantees of the extended AgentSpeak(RT) architecture. We present a characterisation of real-time task environments for an agent, and describe how it relates to AgentSpeak(RT) execution time profiles for a plan and an action. We also show a relationship between the estimated execution time of a plan in a particular environment and the syntactic complexity of an agent program.

Treating variable data documents as functions over their data bindings opens opportunities for building more powerful, robust and flexible document architectures to meet the needs arising from the confluence of developments in document engineering, digital printing technologies and marketing analysis. This thesis describes a combination of several XML-based technologies both to represent and to process variable documents and their data, leading to extensible, high-quality and 'higher-order' document generation solutions. The architecture (DDF) uses XML uniformly throughout the documents and their processing tools with interspersing of different semantic spaces being achieved through namespacing. An XML-based functional programming language (XSLT) is used to describe all intra-document variability and for implementing most of the tools. Document layout intent is declared within a document as a hierarchical set of combinators attached to a tree-based graphical presentation. Evaluation of a document bound to an instance of data involves using a compiler to create an executable from the document, running this with the data instance as argument to create a new document with layout intent described, followed by resolution of that layout by an extensible layout processor. The use of these technologies, with design paradigms and coding protocols, makes it possible to construct documents that not only have high flexibility and quality, but also perform in higher-order ways. A document can be partially bound to data and evaluated, modifying its presentation and still remaining variably responsive to future data. Layout intent can be re-satisfied as presentation trees are modified by programmatic sections embedded within them. The key enablers are described and illustrated through example.

This thesis looks at the development of a framework for a functional quantum programming language. The framework is first developed in Haskell, looking at how a monadic structure can be used to explicitly deal with the side-effects inherent in the measurement of quantum systems, and goes on to look at how a dependently-typed reimplementation in Agda gives us the basis for a formally verified quantum programming language. The two implementations are not in themselves fully developed quantum programming languages, as they are embedded in their respective parent languages, but are a major step towards the development of a full formally verified, functional quantum programming language. Dubbed the “Quantum IO Monad”, this framework is designed following a structural approach as given by a categorical model of quantum computation.

Desktop Virtual Reality (VR) is an easy and affordable way to implement VR technology within an organisation. It provides an experience that can be shared by many people, and its 3D, interactive capability facilitates the communication of ideas not possible using other media formats. There are a number of software toolkits available for the building and programming of Virtual Environments (VEs), but very few resources that can help developers acquire the skills and techniques required to give their VEs utility and usability. This thesis reviews existing research into VE design with an emphasis on interactivity and usability, and then uses a case study based approach to conceptualise the VE development process and develop exemplar guidance tools. The first group of case studies date from the early 1990s, with an emphasis on finding ways to build VEs incorporating functionality. The experience gained through these case studies was used to discover the issues most relevant to the VE developer and report on the techniques used to resolve them. Several models are then presented to explain these techniques and relate them to the VE development context. For the second set of case studies the emphasis moves to finding ways of making VEs more usable. Several approaches are presented and further conceptualisation results in a decision table based guidance tool. The third set of case studies was carried out within the framework provided by the Virtual Environment Development Structure (VEDS), developed jointly by the author and other members of the Virtual Reality Applications Research Team (VIRART) at the University of Nottingham. In the light of this practical application of the framework and the experience gained throughout the case studies, changes are made to the structure to make it more accurately represent the actual process employed by VE developers. This version of VEDS is then used to more effectively define the areas where VE development guidance tools are needed. Using this information, and based on the experience acquired and the techniques developed throughout this research, three exemplar tools are presented.

The synthesis of abiotic life-like behaviour in complex chemical systems is one of the great scientific challenges in today’s research environment. Very often in this type of design, the parameter space is so large and the system so complex that analytical, rational design techniques are extremely difficult to manage, and more often than not, unavailable altogether. Machine learning methods have found many applications in the realm of design and manufacture and the research described in this thesis describes the application of these tools towards the development of pre-specified chemical functionality in complex systems. A detailed description of the ‘Evolutionary Engine’ built with this sort of design in mind is given, including preliminary investigations into coupling this engine to a ‘real life’ chemical reactor array. Studies are performed on a range of complex systems, including benchmark problems based on cellular automata, and, for the first time in this domain, on real world problems in self-organised scanning probe microscopy. Given a target behaviour of the system in question, usually represented by a series of patterns in a 2D image, it is shown that parameters can be ‘reverse engineered’ through a sophisticated combination of machine learning techniques and image analysis methods, such that the target behaviour/pattern can be faithfully reproduced. Finally, techniques for the approximation of a complex system and its associated fitness function are explored, giving rise to a dramatic decrease in computation time with little compromise to the quality of results.

Over the past few years, IRC bots, malicious programs which are remotely controlled by the attacker, have become a major threat to the Internet and its users. These bots can be used in different malicious ways such as to launch distributed denial of service (DDoS) attacks to shutdown other networks and services. New bots are implemented with extended features such as keystrokes logging, spamming, traffic sniffing, which cause serious disruption to targeted networks and users. In response to these threats, there is a growing demand for effective techniques to detect the presence of bots/botnets. Currently existing approaches detect botnets rather than individual bots. In our work we present a host-based behavioural approach for detecting bots/botnets based on correlating different activities generated by bots by monitoring function calls within a specified time window. Different correlation algorithms have been used in this work to achieve the required task. We start our work by detecting IRC bots' behaviours using a simple correlation algorithm. A more intelligent approach to understand correlating activities is also used as a major part of this work. Our intelligent algorithm is inspired by the immune system. Although the intelligent approach produces an anomaly value for the classification of processes, it generates false positive alarms if not enough data is provided. In order to solve this problem, we introduce a modified anomaly value which reduces the amount of false positives generated by the original anomaly value. We also extend our work to detect peer to peer (P2P) bots which are the upcoming threat to Internet security due to the fact that P2P bots do not have a centralized point to shutdown or traceback, thus making the detection of P2P bots a real challenge. Our evaluation shows that correlating different activities generated by IRC/P2P bots within a specified time period achieves high detection accuracy. In addition, using an intelligent correlation algorithm not only states if an anomaly is present, but it also names the culprit responsible for the anomaly.

An increasing number of devices are being situated in public spaces yet interactions with such devices are problematic: they tend to be impersonal and subject to social apprehension while devices suitable for specific tasks may be difficult to locate. This thesis considers how one might design for these environments to overcome these issues and deliver engaging user experiences. It proposes the coupling of the interactive features of mobile and situated devices to facilitate personalised interactions with those situated devices. The thesis explores coupling techniques that extend the computational capabilities of the situated device through the addition of the input, output and storage capabilities of the mobile device. Finally it considers how multiple points of coupling can be used to link sequences of interactions with different situated devices providing rich, cohesive experiences across an environment. The thesis presents a novel framework that builds upon previous work. Existing work is reviewed that links mobiles with single situated displays, and that uses mobiles for mediating exploration of physical spaces to address the lack of work addressing multiple situated de-vices in public. This review grounds a proposal and elaboration of a core model of interaction within a coupling environment, providing the basis for a design framework. This was sup-ported by the implementation of a test-bed that consisted of six couples in various configura-tions, underpinned by a software infrastructure. Formative user studies refined the framework and revealed novel aspects of the user experi-ence for study. It was found that through support for narrative and personal orchestration, coupling environments afford personalised trajectories. By designing for personal trajectories the visitor has a more enjoyable personal experience and seeks to improve the experiences of others. In addition, coupling environments support social experiences; the step-by-step nature of a visitor’s trajectory through the coupling environment lends itself to gradually introducing visitors to social coupled interaction and reducing social awkwardness.

This thesis is concerned with single and multiple target visual tracking algorithms and their application in the real world. While they are both powerful and general, one of the main challenges of tracking using particle filter-based algorithms is to manage the particle spread. Too wide a spread leads to dispersal of particles onto clutter, but limited spread may lead to difficulty when fast-moving objects and/or high-speed camera motion throw trackers away from their target(s). This thesis addresses the particle spread management problem. Three novel tracking algorithms are presented, each of which combines particle filtering and Kernel Mean Shift methods to produce more robust and accurate tracking. The first single target tracking algorithm, the Structured Octal Kernel Filter (SOK), combines Mean Shift (Comaniciu et al 2003) and Condensation (Isard and Blake 1998a). The spread of the particle set is handled by structurally placing the particles around the object, using eight particles arranged to cover the maximum area. Mean Shift is then applied to each particle to seek the global maxima. In effect, SOK uses intelligent switching between Mean Shift and particle filtering based on a confidence level. Though effective, it requires a threshold to be set and performs a somewhat inflexible search. The second single target tracking algorithm, the Kernel Annealed Mean Shift tracker (KAMS), uses an annealed particle filter (Deutscher et al 2000), but introduces a Mean Shift step to control particle spread. As a result, higher accuracy and robustness are achieved using fewer particles and annealing levels. Finally, KAMS is extended to create a multi-object tracking algorithm (MKAMS) by introducing an interaction filter to handle object collisions and occlusions. All three algorithms are compared experimentally with existing single/multiple object tracking algorithms. The evaluation procedure compares competing algorithms' robustness, accuracy and computational cost using both numerical measures and a novel application of McNemar's statistic. Results are presented on a wide variety of artificial and real image sequences.

This thesis presents a comparison between two simulation methods, namely Discrete Event Simulation (DES) and Agent Based Simulation (ABS). In our literature review we identified a gap in comparing the applicability of these methods to modelling human centric service systems. Hence, we have focused our research on reactive and different level of detail of proactive of human behaviour in service systems. The aim of the thesis is to establish a comparison for modelling human reactive and different level of detail of proactive behaviour in service systems using DES and ABS. To achieve this we investigate both the similarities and differences between model results performance and the similarities and differences in model difficulty performance. The comparison of the simulation methods is achieved by using a case study approach. We have conducted three case studies, the choice of our case study systems taking into consideration the number of different key proactive behaviours that can be observed. In the first case study (fitting room services) we consider single proactive staff behaviour, in the second case study (international support services) we consider two proactive staff behaviours and, finally, the third case study (airline check-in services) considers three proactive staff behaviours. The proactive behaviours considered are: taking charge from experience, taking the initiative to fulfil a goal and supervising by learning. To conduct our case studies we have created two sets of simulation models. The first set consists of one DES model for each of the case studies. As service systems have an organisational structure we could not implement our agent-based simulation models purely as agent-based models. Instead, for the second set we have created combined DES/ABS models (one for each case study), where the DES part represents the system and the ABS part represents the active entities inside the system (i.e. the people).With these models we have carried out two sets of experiments: Set A is concerned with modelling results performance, while set B is related to model difficulty performance. We have then conducted statistical analysis on the results of these experiments. Evidence from the experiments reveals that DES and combined DES/ABS are found suitable to model the reactive and most levels of proactive behaviour modelled in this thesis. In addition, combined DES/ABS is found more suitable for modelling higher levels of proactive behaviour (complex behaviour). Another finding from the experiments is that it is only worth representing complex proactive behaviour if it occurs frequently in the real system (considering the relation between modelling effort and impact). The contribution made by this thesis to the body of knowledge is the comparison of DES and combined DES/ABS for modelling human reactive and different level of detail of human proactive behaviour in service systems. This comparison will assist modellers who are new to the field of service systems modelling to make an informed decision on the method they should use for their own modelling, based on the level of proactiveness inherent in the real system and on the levels of difficulties they should expect for each method.

Algorithmic problem solving provides a radically new way of approaching and solving problems in general by using the advances that have been made in the basic principles of correct-by-construction algorithm design. The aim of this thesis is to provide educational material that shows how these advances can be used to support the teaching of mathematics and computing. We rewrite material on elementary number theory and we show how the focus on the algorithmic content of the theory allows the systematisation of existing proofs and, more importantly, the construction of new knowledge in a practical and elegant way. For example, based on Euclid’s algorithm, we derive a new and efficient algorithm to enumerate the positive rational numbers in two different ways, and we develop a new and constructive proof of the two-squares theorem. Because the teaching of any subject can only be effective if the teacher has access to abundant and sufficiently varied educational material, we also include a catalogue of teaching scenarios. Teaching scenarios are fully worked out solutions to algorithmic problems together with detailed guidelines on the principles captured by the problem, how the problem is tackled, and how it is solved. Most of the scenarios have a recreational flavour and are designed to promote self-discovery by the students. Based on the material developed, we are convinced that goal-oriented, calculational algorithmic skills can be used to enrich and reinvigorate the teaching of mathematics and computing.