Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates

Agent-based management of clinical guidelines

Les guies de pràctica clínica (GPC) contenen un conjunt d'accions i dades que ajuden a un metge a prendre decisions sobre el diagnòstic, tractament o qualsevol altre procediment a un pacient i sobre una determinada malaltia. És conegut que l'adopció d'aquestes guies en la vida diària pot millorar l'assistència mèdica als pacients, pel fet que s'estandarditzen les pràctiques. Sistemes computeritzats que utilitzen GPC poden constituir part de sistemes d'ajut a la presa de decisions més complexos amb la finalitat de proporcionar el coneixement adequat a la persona adequada, en un format correcte i en el moment precís. L'automatització de l'execució de les GPC és el primer pas per la seva implantació en els centres mèdics.Per aconseguir aquesta implantació final, hi ha diferents passos que cal solucionar com per exemple, l'adquisició i representació de les GPC, la seva verificació formal, i finalment la seva execució. Aquesta Tesi està dirigida en l'execució de GPC i proposa la implementació d'un sistema multi-agent. En aquest sistema els diferents actors dels centres mèdics coordinen les seves activitats seguint un pla global determinat per una GPC. Un dels principals problemes de qualsevol sistema que treballa en l'àmbit mèdic és el tractament del coneixement. En aquest cas s'han hagut de tractar termes mèdics i organitzatius, que s'ha resolt amb la implementació de diferents ontologies. La separació de la representació del coneixement del seu ús és intencionada i permet que el sistema d'execució de GPC sigui fàcilment adaptable a les circumstàncies concretes dels centres, on varien el personal i els recursos disponibles.En paral·lel a l'execució de GPC, el sistema proposat manega preferències del pacient per tal d'implementar serveis adaptats al pacient. En aquesta àrea concretament, a) s'han definit un conjunt de criteris, b) aquesta informació forma part del perfil de l'usuari i serveix per ordenar les propostes que el sistema li proposa, i c) un algoritme no supervisat d'aprenentatge permet adaptar les preferències del pacient segons triï.Finalment, algunes idees d'aquesta Tesi actualment s'estan aplicant en dos projectes de recerca. Per una banda, l'execució distribuïda de GPC, i per altra banda, la representació del coneixement mèdic i organitzatiu utilitzant ontologies.Clinical guidelines (CGs) contain a set of directions or principles to assist the health care practitioner with patient care decisions about appropriate diagnostic, therapeutic, or other clinical procedures for specific clinical circumstances. It is widely accepted that the adoption of guideline-execution engines in daily practice would improve the patient care, by standardising the care procedures. Guideline-based systems can constitute part of a knowledge-based decision support system in order to deliver the right knowledge to the right people in the right form at the right time. The automation of the guideline execution process is a basic step towards its widespread use in medical centres.To achieve this general goal, different topics should be tackled, such as the acquisition of clinical guidelines, its formal verification, and finally its execution. This dissertation focuses on the execution of CGs and proposes the implementation of an agent-based platform in which the actors involved in health care coordinate their activities to perform the complex task of guideline enactment. The management of medical and organizational knowledge, and the formal representation of the CGs, are two knowledge-related topics addressed in this dissertation and tackled through the design of several application ontologies. The separation of the knowledge from its use is fully intentioned, and allows the CG execution engine to be easily customisable to different medical centres with varying personnel and resources.In parallel with the execution of CGs, the system handles citizen's preferences and uses them to implement patient-centred services. With respect this issue, the following tasks have been developed: a) definition of the user's criteria, b) use of the patient's profile to rank the alternatives presented to him, c) implementation of an unsupervised learning method to adapt dynamically and automatically the user's profile.Finally, several ideas of this dissertation are being directly applied in two ongoing funded research projects, including the agent-based execution of CGs and the ontological management of medical and organizational knowledge

Application of data analytics for predictive maintenance in aerospace: an approach to imbalanced learning.

The use of aircraft operational logs to predict potential failure that may lead to disruption poses many challenges and has yet to be fully explored. These logs are captured during each flight and contain streamed data from various aircraft subsystems relating to status and warning indicators. They may, therefore, be regarded as complex multivariate time-series data. Given that aircraft are high-integrity assets, failures are extremely rare, and hence the distribution of relevant data containing prior indicators will be highly skewed to the normal (healthy) case. This will present a significant challenge in using data-driven techniques to 'learning' relationships/patterns that depict fault scenarios since the model will be biased to the heavily weighted no-fault outcomes. This thesis aims to develop a predictive model for aircraft component failure utilising data from the aircraft central maintenance system (ACMS). The initial objective is to determine the suitability of the ACMS data for predictive maintenance modelling. An exploratory analysis of the data revealed several inherent irregularities, including an extreme data imbalance problem, irregular patterns and trends, class overlapping, and small class disjunct, all of which are significant drawbacks for traditional machine learning algorithms, resulting in low-performance models. Four novel advanced imbalanced classification techniques are developed to handle the identified data irregularities. The first algorithm focuses on pattern extraction and uses bootstrapping to oversample the minority class; the second algorithm employs the balanced calibrated hybrid ensemble technique to overcome class overlapping and small class disjunct; the third algorithm uses a derived loss function and new network architecture to handle extremely imbalanced ratios in deep neural networks; and finally, a deep reinforcement learning approach for imbalanced classification problems in log- based datasets is developed. An ACMS dataset and its accompanying maintenance records were used to validate the proposed algorithms. The research's overall finding indicates that an advanced method for handling extremely imbalanced problems using the log-based ACMS datasets is viable for developing robust data-driven predictive maintenance models for aircraft component failure. When the four implementations were compared, deep reinforcement learning (DRL) strategies, specifically the proposed double deep State-action-reward-state-action with prioritised experience reply memory (DDSARSA+PER), outperformed other methods in terms of false-positive and false-negative rates for all the components considered. The validation result further suggests that the DDSARSA+PER model is capable of predicting around 90% of aircraft component replacements with a 0.005 false-negative rate in both A330 and A320 aircraft families studied in this researchPhD in Transport System

Enhancing the Communication of Law: a cross-disciplinary investigation applying information technology

Law is pervasive in culture. It is a form of communication between government and citizens. When effective, it is a tool of government policy. If poorly designed,law results in unnecessary costs to society. Impediments to understanding of the law limits and distorts democratic participation. Yet, historically, the law has been inaccessible to most. Thus enhancing the communication of law is an important and standing problem. Much work has been done (for example through the plain language movement) to improve the communication of law. Nonetheless, the law remains largely unreadable to non-legal users. This thesis applies information technology to investigate and enhance the communication of law. To this end, this thesis focusses on four main areas.To improve the readability of law, it must be better described as a form of language. Corpus linguistics is applied for this purpose. A linguistic description of contract language arose from this work, which, along with the corpus itself, has been made available to the research community. The thesis also describes work for the automatic classification of text in legal contracts by legal function.Reliable measures for the readability of law are needed, but they do not exist. To develop such measures, gold standard data is needed to evaluate possible measures.To create this gold standard data, the research engaged citizen scientists, in the form of the online “crowd”. However, methods for creating and using such user assessments for readability are rudimentary. The research therefore investigated,developed and applied a number of methods for collecting user ratings of readability in an online environment. Also, the research applied machine learning to investigate and identify linguistic factors that are specifically associated with language difficulty of legislative sentences. This resulted in recommendations for improving legislative readability. A parallel line of investigation concerned the application of visualization to enhance the communication of law. Visualization engages human visual perception and its parallel processing capacities for the communication of law. The research applied computational tools: natural language processing, graph characteristics and data driven algorithms. It resulted in prototype tools for automatically visualizing definition networks and automating the visualization of selected contract clauses. Also, the work has fostered an investigation of the nature of law itself. A “law as” framework is used to query the nature of law and illuminate law in new ways. The framework is re-assessed as a tool for the experimental investigation of law. This results in an enhanced description of law, applying a number of investigatory frames:law; communication; document; information; computation; design and complex systems theory. It also provides a contrastive study with traditional theories of law - demonstrating how traditional theories can be extended in the light of these multidisciplinary results. In sum, this thesis reports a body of work advancing the existing knowledge base and state of the art in respect of application of computational techniques to enhancing the communication of law

Care robots in residential homes for elderly people: an ethical examination of deception, care, and consent

We are facing a dire social problem: although life expectancy is increasing, time spent living independently is not, meaning that the eldercare sector is experiencing a worrying shortfall of nursing staff - a problem which is only getting worse. Robots designed for caring purposes – carebots – present a possible solution: they can perform some of the work which has been hitherto undertaken by human nurses. But their introduction is not without problems. This thesis examines some pertinent questions relating to the introduction of carebots into residential homes for elderly people. Chapter 1 examines what robots are, and provides a way in which we can differentiate between robots of different types, helping us to understand what ethical issues are at stake for different types of robot. Chapter 2 focuses on what deception consists of, and discusses why deception and lying are often seen as impermissible. Chapter 3 discusses different types of robo-deception, and analyses both the likelihood and the normative significance of their occurring. Chapter 4 is a study of a particular form of robo-deception, which I call fake compassion. This is when robots appear to care for patients when in fact they do not: I examine the extent to which this is morally problematic. Chapter 5 examines dignity: what it is, and why it is important. Chapter 6 focuses on consent: its importance in different spheres, and how consent-seeking can promote autonomy, bodily integrity, dignity, and trust. Chapter 7 builds on the previous two chapters, and demonstrates that it is ethically essential that carebots (and human nurses) obtain patients' consent prior to providing care, because failing to do so can reduce their dignity, and these reductions can be cumulative and devastating. This thesis is not merely an interesting thought experiment or a work of science fiction; rather, it is a real-world necessity that carebots take appropriate actions which promote the dignity and best interests of patients: our grandparents, parents, and in time, us and our descendants

Care robots in residential homes for elderly people: an ethical examination of deception, care, and consent

We are facing a dire social problem: although life expectancy is increasing, time spent living independently is not, meaning that the eldercare sector is experiencing a worrying shortfall of nursing staff - a problem which is only getting worse. Robots designed for caring purposes – carebots – present a possible solution: they can perform some of the work which has been hitherto undertaken by human nurses. But their introduction is not without problems. This thesis examines some pertinent questions relating to the introduction of carebots into residential homes for elderly people. Chapter 1 examines what robots are, and provides a way in which we can differentiate between robots of different types, helping us to understand what ethical issues are at stake for different types of robot. Chapter 2 focuses on what deception consists of, and discusses why deception and lying are often seen as impermissible. Chapter 3 discusses different types of robo-deception, and analyses both the likelihood and the normative significance of their occurring. Chapter 4 is a study of a particular form of robo-deception, which I call fake compassion. This is when robots appear to care for patients when in fact they do not: I examine the extent to which this is morally problematic. Chapter 5 examines dignity: what it is, and why it is important. Chapter 6 focuses on consent: its importance in different spheres, and how consent-seeking can promote autonomy, bodily integrity, dignity, and trust. Chapter 7 builds on the previous two chapters, and demonstrates that it is ethically essential that carebots (and human nurses) obtain patients' consent prior to providing care, because failing to do so can reduce their dignity, and these reductions can be cumulative and devastating. This thesis is not merely an interesting thought experiment or a work of science fiction; rather, it is a real-world necessity that carebots take appropriate actions which promote the dignity and best interests of patients: our grandparents, parents, and in time, us and our descendants