Raisonnement sur les modèles : détection et isolation d'anomalies dans les systèmes de diagnostic

Dans le cadre du diagnostic à base de Modèle, un ensemble de règles d'inférence est typiquement exploité pour calculer des diagnostics, ceci en utilisant une théorie scientifique et mathématique sur le système à diagnostiquer, ainsi qu'un ensemble d'observations. Contrairement aux hypothèses classiques, les Modèles sont souvent anormaux vis-à-vis d'un ensemble de propriétés requises. Naturellement, cela affecte la qualité des diagnostics [à Airbus]. Une théorie sur la réalité, l'information et la cognition est créé pour redéfinir, dans une perspective basée sur la théorie des modèles, le cadre classique de diagnostic à base de Modèle. Ceci rend possible la formalisation des anomalies et de leur relation avec des propriétés des diagnostics. Avec ce travail et avec l'idée qu'un système de diagnostic implémenté peut être vu comme un objet à diagnostiquer, une théorie de méta-diagnostic est développée, permettant la détection et isolation d'anomalies dans les Modèles des systèmes de diagnostic. Cette théorie est mise en pratique à travers d'un outil, MEDITO; et est testée avec succès à travers un ensemble de problèmes industriels, à Airbus. Comme des différents systèmes de diagnostic Airbus, souffrant d'anomalies variées, peuvent calculer des diagnostics différents, un ensemble de méthodes et outils et développé pour: 1) déterminer la cohérence entre diagnostics et 2) valider et comparer la performance de ces systèmes de diagnostic. Ce travail dépend d'un pont original entre le cadre de diagnostic Airbus et son équivalent académique. Finalement, la théorie de méta-diagnostic est généralisée pour prendre en compte des méta-systèmes autres que des systèmes de diagnostic implémentés.In Model-Based Diagnosis, a set of inference rules is typically used to compute diagnoses using a scientific and mathematical theory about a system under study and some observations. Contrary to the classical hypothesis, it is often the case that these Models are abnormal with respect to a series of required properties, hence affecting the quality of the computed diagnoses with possibly huge economical consequences, in particular at Airbus. A thesis on reality and cognition is firstly used to redefine the classic framework of model-based diagnosis from a formal model-theoretic perspective. This, in turn, enables the formalisation of abnormalities and of their relation with the properties diagnoses. With such material and the idea that an implemented diagnostic system can be seen a real-world artefact to be diagnosed, a theory of meta-diagnosis is developed, enabling the detection and isolation of abnormalities in Models of diagnostic systems and explanation in general. Such theory is then encoded in a tool, called MEDITO, and successfuly tested against Airbus real-world industrial problems. Moreover, as different heterogeneous implemented Airbus diagnostic systems, suffering from distinct abnormalities, may compute different diagnoses, methods and tools are developed for: 1) checking the consistency between subsystem-level diagnoses and 2) validating and comparing the performance of these diagnostic systems. Such work relies on an original bridge between the Airbus framework of diagnosis and its academic counterpart. Finally, meta-diagnosis is generalised to handle meta-systems other than implemented diagnostic systems

Diagnosing runtime violations of security and dependability properties

Monitoring the preservation of security and dependability (S&D) properties of complex software systems is widely accepted as a necessity. Basic monitoring can detect violations but does not always provide sufficient information for deciding what the appropriate response to a violation is. Such decisions often require additional diagnostic information that explains why a violation has occurred and can, therefore, indicate what would be an appropriate response action to it. In this thesis, we describe a diagnostic procedure for generating explanations of violations of S&D properties developed as extension of a runtime monitoring framewoek, called EVEREST. The procedure is based on a combination of abductive and evidential reasoning about violations of S&D properties which are expressed in Event Calculus

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Diagnosing runtime violations of security and dependability properties

Monitoring the preservation of security and dependability (S&D) properties of complex software systems is widely accepted as a necessity. Basic monitoring can detect violations but does not always provide sufficient information for deciding what the appropriate response to a violation is. Such decisions often require additional diagnostic information that explains why a violation has occurred and can, therefore, indicate what would be an appropriate response action to it. In this thesis, we describe a diagnostic procedure for generating explanations of violations of S&D properties developed as extension of a runtime monitoring framewoek, called EVEREST. The procedure is based on a combination of abductive and evidential reasoning about violations of S&D properties which are expressed in Event Calculus.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The Road to General Intelligence

Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory. • Details the pragmatic requirements for real-world General Intelligence. • Describes how machine learning fails to meet these requirements. • Provides a philosophical basis for the proposed approach. • Provides mathematical detail for a reference architecture. • Describes a research program intended to address issues of concern in contemporary AI. The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book

Towards a mobile application to aid law enforcement in diagnosing and preventing mobile bully-victim behaviour in Eastern Free State High Schools of South Africa

Mobile bully-victim behaviour is one cyber aggression that is escalating worldwide. Bully-victims are people who bully others but are also victimised by peers. The behaviour of bully-victims therefore swings between that of pure bullies and pure victims, making it difficult to identify and prevent. Prevention measures require the involvement of a number of stakeholders, including communities. However, there has been a lack of whole-community participation in the fight against cyberbullying and the roles of stakeholders are often unclear. We expect the law enforcement in particular, the police, to play a key role in curbing all forms of bullying. This is a challenging task in South Africa as these law enforcement agents often lack the skills and appropriate legislation to address particularly cyber-related bullying. Literature shows that law enforcement agents need to advance their technological skills and also be equipped with digital interventions if they are to diagnose and prevent mobile bully-victim behaviour effectively. This is particularly important in South Africa, where the rate of crime remains one of the highest in the world. The aim of this study was to develop a mobile application that can aid law enforcement in diagnosing and preventing mobile bully-victim behaviour in high schools. As part of requirements to the application development, it identified the impediments to the law enforcement effectiveness in combating mobile bully-victim behaviour. Extensive literature review on the factors influencing mobile bullying and mobile bully-victim behaviour was conducted and an integrative framework for understanding this behaviour and its prevention was developed. In so doing, the dominant behavioural theories were consulted, including the social-ecological theory, social learning theory, social information processing theories, and the theory of planned behaviour, as well as the general strain theory, and the role theory. The conceptual framework developed in this study extended and tailored the “Cyberbullying Continuum of Harm”, enabling inclusive and moderated diagnosis of bullying categories and severity assessment. That is, instead of focusing on mobile bully-victims only, bullies, victims, and those uninvolved were also identified. Also the physical moderation of the identification process by the police helped to minimise dishonest reporting. This framework informed the design, development and evaluation of a mobile application for the law enforcement agents. The Design Science Research (DSR) methodology within pragmatic paradigm and literature guided the development of the mobile application named mobile bullyvictims response system (M-BRS) and its evaluation for utility. The M-BRS features included functions to enable anonymous reporting and confidential assessments of mobile bully-victims effects in school classrooms. Findings from this study confirmed the utility of the M-BRS to identify learners' involvement in mobile bully-victims behaviour through peer nomination and self-nomination. This study also showed that use of the M-BRS has enabled empowerment of marginalised learners, and mitigation of learners' fear to report, providing them with control over mobile bully-victim reporting. In addition, learners using the M-BRS were inclined to report perpetrators through a safe (anonymous and confidential) reporting platform. With the M-BRS, it was much easier to identify categories of bullies, i.e. mobile bully-victims, bullies, victims, and uninvolved. The practical contributions of this study were skills enhancements in reducing the mobile bully-victims behaviour. These included improvement of the police's technical skills to safely identify mobile bully-victims and their characterisation as propagators and retaliators that enabled targeted interventions. This was particularly helpful in response to courts' reluctance to prosecute teenagers for cyberbullying and the South African lack of legislation thereon so that the police are enabled to restoratively address this behaviour in schools. Also, the identification information was helpful to strengthen evidence for reported cases, which was remarkable because sometimes perpetrators cannot be found due to their concealed online identities. Furthermore, this study made possible the surveillance of mobile bully-victims through the M-BRS, which provided the police some control to reducing the mobile bully-victim behaviour. This study provided a practical way for implementing targeted prevention and interventions programmes using relevant resources towards a most efficient solution for mobile bully-victims problem. Since there are not many mobile-based interventions for mobile bully-victim behaviour, this study provided a way in which artefacts' development could be informed by theory, as a new, innovative and practical contribution in research. In so doing, this study contributed to technology applications' ability to modify desired behaviour