Avec le développement et la multiplication des appareils connectés dans tous les domaines, de nouvelles solutions pour le traitement de flux de données ont vu le jour. Cette thèse s'inscrit dans ce contexte: elle a été réalisée dans le cadre du projet FUI Waves, une plateforme de traitement de flux distribués. Le cas d'usage pour le développement a été la gestion des données provenant d'un réseau de distribution d'eau potable, plus précisément la détection d'anomalie dans les mesures de qualité et leur contextualisation par rapport à des données extérieures. Plusieurs contributions ont été réalisées et intégrées à différentes étapes du projet, leur évaluation et les publications liées témoignant de leur pertinence. Celles-ci se basent sur une ontologie que j'ai spécifiée depuis des échanges avec les experts du domaine travaillant dans chez le partenaire métier du projet. L'utilisation de données géographiques a permis de réaliser un système de profilage visant à améliorer le processus de contextualisation des erreurs. Un encodage de l'ontologie adapté au traitement de flux de données RDF a été développé pour supporter les inférences de RDFS enrichis de owl : sameAs. Conjointement, un formalisme compressé de représentation des flux (PatBin) a été conçu et implanté dans la plateforme. Il se base sur la régularité des motifs des flux entrants. Enfin, un langage de requêtage a été développé à partir de ce formalisme. Il intègre une stratégie de raisonnement se basant sur la matérialisation et la réécriture de requêtes. Enfin, à partir de déductions provenant d'un d'apprentissage automatique, un outil de génération de requêtes a été implanté. Ces différentes contributions ont été évaluées sur des jeux de données concrets du domaine ainsi que sur des jeux d'essais synthétiques / With the developpement and the expansion of connected devices in every domain, several projects on stream processing have been developped. This thesis has been realized as part of the FUI Waves, a reasoning stream processing engine distributed. The use case for the developement was the processing of data streamed from a potable water distribution network, more specifically the detection of anomalies in the quality measures and their contextualisation using external data. Several contributions have been realized and integrated in different stages of the project, wih evaluations and publications witnessing their relevance. These contributions use an ontology that has been designed thanks to collaboration with domain experts working for our water data management project partner. The use of geographical data allowed to realize a profiling system aiming at improving the anomaly contextualisation process. An ontology encoding approach, adapted to RDF stream processing, has been developped to support RDFS inferences enriched with owl : sameAs. Conjointly, a compressed formalism (PatBin) has been designed to represent streams. PatBin is based on the regularity of patterns found in incoming streams. Moreover, a query language has been conceived from PatBin, namely PatBinQL. It integrates a reasoning strategy that combines both materialization and query rewritting. Finally, given deductions coming from a Waves machine learning component, a query generation tool has been developped. These diferent contributions have been evaluated on both real-world and synthetic datasets

by Ying Kit Wong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 144-146). / Acknowledgments / Abstract / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Characteristics of Human Commonsense Reasoning --- p.4 / Chapter 1.2 --- Neural-Logic Belief Network as the Basic Inconsistency Rea- soning System --- p.7 / Chapter 1.3 --- Consistency of Knowledge --- p.8 / Chapter 1.4 --- Update Sequence Independence in Belief States --- p.10 / Chapter 1.5 --- Lazy Consistency Reasoning --- p.12 / Chapter 1.6 --- Comparison of W-Consistency with Other Systems --- p.14 / Chapter 1.7 --- Integration of Different Methods in One Formalization --- p.16 / Chapter 2 --- Neural-Logic Belief Network (NLBN) --- p.17 / Chapter 2.1 --- Definitions --- p.17 / Chapter 2.2 --- Computation Functions --- p.20 / Chapter 3 --- W-Consistency Reasoning --- p.29 / Chapter 3.1 --- W-Consistency --- p.30 / Chapter 3.2 --- Logical Suppression --- p.33 / Chapter 3.3 --- Consistency Check --- p.35 / Chapter 3.4 --- Consistency Maintenance --- p.35 / Chapter 3.5 --- The W-Consistency Reasoning Process --- p.41 / Chapter 3.6 --- Proof of Consistency Reasoning Process Terminates Finitely and Consistent --- p.42 / Chapter 4 --- Implementation --- p.46 / Chapter 4.1 --- Introduction --- p.46 / Chapter 4.2 --- New Features in Phase Two --- p.48 / Chapter 4.2.1 --- Consistency Reasoning Function --- p.48 / Chapter 4.2.2 --- Knowledge File --- p.49 / Chapter 4.3 --- Inference Engine for Consistency Reasoning --- p.54 / Chapter 4.4 --- Examples of using XHOPES --- p.56 / Chapter 5 --- Comparison between NLBN with W-Consistency and AGM Logic --- p.63 / Chapter 5.1 --- AGM Logic with Epistemic Entrenchment --- p.64 / Chapter 5.1.1 --- Three Forms of Belief Change --- p.64 / Chapter 5.1.2 --- Epistemic Entrenchment --- p.67 / Chapter 5.2 --- Network Update Operators in NLBN vs. Belief Changesin AGM --- p.68 / Chapter 5.3 --- Epistemic Entrenchment vs. Degree-of-Belief --- p.77 / Chapter 5.4 --- Consistency Preservation --- p.80 / Chapter 5.5 --- Classical vs. Non-classical Logical Consistency --- p.82 / Chapter 5.6 --- Retraction vs. Suppression --- p.83 / Chapter 5.7 --- Foundation vs. Coherence Theories --- p.84 / Chapter 6 --- Comparison of W-Consistency with other Systems --- p.86 / Chapter 6.1 --- G-Consistency --- p.87 / Chapter 6.1.1 --- Overview of G-Consistency --- p.87 / Chapter 6.1.2 --- Comparison of W-Consistency with G-Consistency --- p.88 / Chapter 6.2 --- S-Consistency --- p.94 / Chapter 6.2.1 --- Overview of S-Consistency --- p.94 / Chapter 6.2.2 --- Comparison of W-Consistency with S-Consistency --- p.95 / Chapter 6.3 --- Truth Maintenance Systems --- p.97 / Chapter 6.3.1 --- Introduction of Truth Maintenance Systems --- p.97 / Chapter 6.3.2 --- Comparison of TMS between W-Consistency with NLBN --- p.99 / Chapter 7 --- Lazy Consistency Reasoning using W-Consistency --- p.102 / Chapter 7.1 --- Proof of Lazy Characteristic of W-Consistency --- p.104 / Chapter 7.2 --- Example of Lazy Consistency Reasoning --- p.112 / Chapter 7.3 --- Discussion and Application --- p.117 / Chapter 8 --- Integration of Different Consistency Reasoning Methods --- p.120 / Chapter 8.1 --- Mixing W-Consistency and G-Consistency into a NLBN --- p.121 / Chapter 8.2 --- Using a NLBN for Truth Maintenance --- p.129 / Chapter 8.2.1 --- TMS's Truth Maintenance Strategy --- p.129 / Chapter 8.2.2 --- Consistency Reasoning style of NLBN --- p.134 / Chapter 8.2.3 --- Using NLBN for TMS-style Truth Maintenance --- p.136 / Chapter 8.2.4 --- Discussion --- p.140 / Chapter 9 --- Conclusion --- p.143 / Chapter A --- Test Case for Merging Knowledge Bases Using XHOPES --- p.150

The current research project aimed to investigate how various degrees of psychosis and autism traits were associated with different styles of reasoning. Therefore, a series of five studies were conducted that recruited participants who were considered to reside along different points of the psychosis and autism continua. Measures of intuitive and deliberative reasoning style were employed and were used to ascertain whether differing degrees of psychosis and autism reflected different profiles of reasoning style. In addition, a composite score was devised using the raw scores of measures of psychosis and autism traits to test Crespi and Badcocks (2008) diametric disorders hypothesis and to further explore the relationship between the two measures. Overall, the results revealed some evidence that psychosis traits were associated with a more intuitive relative to deliberative style of reasoning, whereas autism traits were reflective of the reverse profile. The findings were also able to shed further light on the intricate relationship between autism and psychotic spectrum disorders.

This thesis focuses on the application of case based reasoning (CBR) to welding fixtures in a computer aided design (CAD) environment. Modular fixtures have become more popular in previous years due to the creation of flexible manufacturing systems. Modular fixtures, since they are composed of many standardized parts, require much iteration to produce a full fixture design. This process is made more complicated when it is applied to more complex parts such as welding assemblies. In an effort to simplify fixture design for such complicated parts, researchers have been working on integrating fixture design into CAD packages. These efforts, generally known as computer aided fixture design (CAFD), do not focus on the transition of experience from more experienced designers but only provide a structure and a virtual environment to create fixtures. The research presented in this thesis will apply to this area. Case based reasoning (CBR) is a method of using previous cases to help aid the development of solutions to new problems. Applied to CAFD, this method is reduced to the application of a database and a retrieval and adaptation system. Current research on CAFD and CBR is limited to only proposing systems for machining fixtures. This thesis presents a methodology of a CAFD and CBR system that is dedicated to welding assemblies and fixtures. The focus is on creating an indexing system that adequately represents the workpiece and fixture, a retrieval system that accurately recovers the previous cases, and a method that integrates designer feedback in each process. The results of this thesis will be shown in a case study using an automobile muffler fixture assembly to define each idea of the methodology and to provide an example.

We investigate principles of rationality based on symmetry in Polyadic Pure Inductive Logic. The aim of Pure Inductive Logic (PIL) is to determine how to assign probabilities to sentences of a language being true in some structure on the basis of rational considerations. This thesis centres on principles arising from instances of symmetry for sentences of first-order polyadic languages. We begin with the recently introduced Permutation Invariance Principle (PIP), and find that it is determined by a finite number of permutations on a finite set of formulae. We test the consistency of PIP with established principles of the subject and show, in particular, that it is consistent with Super Regularity. We then investigate the relationship between PIP and the two main polyadic principles thus far, Spectrum Exchangeability and Language Invariance, and discover there are close connections. In addition, we define the key notion of polyadic atoms as the building blocks of polyadic languages. We explore polyadic generalisations of the unary principle of Atom Exchangeability and prove that PIP is a natural extension of Atom Exchangeability to polyadic languages. In the second half of the thesis we investigate polyadic approaches to the unary version of Constant Exchangeability as invariance under signatures. We first provide a theory built on polyadic atoms (for binary and then general languages). We introduce the notion of a signature for non-unary languages, and principles of invariance under signatures, independence, and instantial relevance for this context, as well as a binary representation theorem. We then develop a second approach to these concepts using elements as alternative building blocks for polyadic languages. Finally, we introduce the concepts of homomorphisms and degenerate probability functions in Pure Inductive Logic. We examine which of the established principles of PIL are preserved by these notions, and present a method for reducing probability functions on general polyadic languages to functions on binary languages.

嚴淑儀. / "2002年6月" / 論文 (哲學碩士)--香港中文大學, 2002. / 參考文獻 (leaves 197-205) / 附中英文摘要. / "2002 nian 6 yue" / Yan Shuyi. / Lun wen (zhe xue shuo shi)--Xianggang Zhong wen da xue, 2002. / Can kao wen xian (leaves 197-205) / Fu Zhong Ying wen zhai yao. / 麥金太爾著作縮寫表 --- p.VIII / 引言 --- p.IX / Chapter 第一章 --- 當代倫理學困境 --- p.1 / Chapter 第一節 --- 麥金太爾對當代道德困境的描述 --- p.1 / Chapter 第二節 --- 不可共量性與不相容性 --- p.10 / Chapter 第三節 --- 啓蒙運動以來的單一理性觀 --- p.24 / Chapter 第四節 --- 情感主義、相對主義與觀點主義 --- p.42 / Chapter 第二章 --- 麥金太爾對傳統之合理性的說明 --- p.55 / Chapter 第一節 --- 由傳統建構之理性觀的特色 --- p.55 / Chapter 第二節 --- 在傳統中體現的理性探究 --- p.71 / Chapter 第三節 --- 知識論危機 --- p.86 / Chapter 第四節 --- 與啓蒙運動理性觀的對比 --- p.100 / Chapter 第五節 --- 真理和理性證立 --- p.108 / Chapter 第六節 --- 理性探究傳統的理性證立 --- p.116 / Chapter 第七節 --- 道德困境的理性出路 --- p.124 / Chapter 第三章 --- 「傳統之合理性」觀點的理性證立 --- p.128 / Chapter 第一節 --- 對麥金太爾的批評(1) -傳統的理性比較涵蘊普遍主義？ --- p.133 / Chapter 第二節 --- 對麥金太爾的批評(2)- 歷史證立的原則是否自我指涉地不融貫？ --- p.138 / Chapter 第三節 --- 對麥金太爾的批評(3）- 跨傳統的解釋是否可能？ --- p.142 / Chapter 第四節 --- 對麥金太爾的批評(4）- ¯‘ة未效忠任何傳統的個人？ --- p.153 / Chapter 第五節 --- 對麥金太爾的批評(5)- 傳統之間的比較是否解決道德爭議的唯一方法？ --- p.161 / Chapter 第六節 --- 對麥金太爾的批評(6）- 多瑪斯主義包含不容質疑的信仰？ --- p.170 / Chapter 第七節 --- 對啓蒙運動理性探究觀與相對主義的批評 --- p.178 / 結語 --- p.191 / 參考書目 --- p.197

This project looks at using diagrammatic reasoning to prove mathematical theorems. The work is motivated by a need for theorem provers whose reasoning is readily intelligible to human beings. It should also have practical applications in mathematics teaching. We focus on the continuous domain of analysis - a geometric subject, but one which is taught using a dry algebraic formalism which many students find hard. The geometric nature of the domain makes it suitable for a diagram-based approach. However it is a difficult domain, and there are several problems, including handling alternating quantifiers, sequences and generalisation. We developed representations and reasoning methods to solve these. Our diagram logic isn't complete, but does cover a reasonable range of theorems. It utilises computers to extend diagrammatic reasoning in new directions – including using animation. This work is tested for soundness, and evaluated empirically for ease of use. We demonstrate that computerised diagrammatic theorem proving is not only possible in the domain of real analysis, but that students perform better using it than with an equivalent algebraic computer system.

Case-Based Reasoning (CBR) is an appealing technique for developing intelligent systems. Besides its psycho- logical plausibility and a substantial body of research during recent years, building a good CBR system remains still a difficult task. The main problems remaining are the development of suitable case retrieval and adaptation mechanisms for CBR. The major issues are how and when to capture the necessary knowledge for both of the above aspects. As a contribution to knowledge this thesis proposes a new approach to address the experienced difficulties. The basic framework of Ripple Down Rules (RDR) is extended to allow the incremental development of a knowledge base for each of the two functions: case retrieval and case adaptation, during the use of the system while solving actual problems. The proposed approach allows an expert-user to provide explanations of why, for a given problem, certain actions should be taken. Incrementally knowledge is acquired from the expert-user in which the expert refines a rule which performs unsatisfactorily for a current given problem. The approach facilitates both, the rule acquisition as well as its validation. As a result the knowledge maintenance task of a knowledge engineer is overcome. This approach is effective with respect to both, the development of highly tailored and complex retrieval and adaptation functions for CBR as well as the provision of an intuitive and feasible approach for the expert. The approach has been implemented in a CBR system named MIKAS (Menu Construction using Incre- mental Knowledge Acquisition Systems) for the design of menus (diets) according to dietary requirements. The experimental evidence indicates the suitability of the approach to address the retrieval and adaptation problems of the menu construction domain. The experimental evidence also indicates that the difficulties of developing retrieval and adaptation functions for CBR can be effectively overcome by the proposed new approach. It is expected that the approach is likely to be useful in other problem solving domains where expert intervention is Required to modify a solution.

Providing a logical characterisation of rational agent reasoning has been a long standing challenge in artificial intelligence (AI) research. It is a challenge that is not only of interest for the construction of AI agents, but is of equal importance in the modelling of agent behaviour. The goal of this thesis is to contribute to the formalisation of agent reasoning by showing that the computational limitations of agents is a vital component of modelling rational behaviour. To achieve this aim, both motivational and formal aspects of resource-bounded agents are examined. It is a central argument of this thesis that accounting for computational limitations is critical to the success of agent reasoning, yet has received only limited attention from the broader research community. Consequently, an important contribution of this thesis is in its advancing of motivational arguments in support of the need to account for computational limitations in agent reasoning research. As a natural progression from the motivational arguments, the majority of this thesis is devoted to an examination of propositional approximate logics. These logics represent a step towards the development of resource-bounded agents, but are also applicable to other areas of automated reasoning. This thesis makes a number of contributions in mapping the space of approximate logics. In particular, it draws a connection between approximate logics and knowledge compilation, by developing an approximate knowledge compilation method based on Cadoli and Schaerf??s S-3 family of approximate logics. This method allows for the incremental compilation of a knowledge base, thus reducing the need for a costly recompilation process. Furthermore, each approximate compilation has well-defined logical properties due to its correspondence to a particular S-3 logic. Important contributions are also made in the examination of approximate logics for clausal reasoning. Clausal reasoning is of particular interest due to the efficiency of modern clausal satisfiability solvers and the related research into problem hardness. In particular, Finger's Logics of Limited Bivalence are shown to be applicable to clausal reasoning. This is subsequently shown to logically characterise the behaviour of the well-known DPLL algorithm for determining boolean satisfiability, when subjected to restricted branching.

Doctor of Philosophy (PhD) / Effective clinical reasoning and its communication are essential to health professional practice, especially in the current health care climate. Increasing litigation leading to legal requirements for comprehensive, relevant and appropriate information exchange between health professionals and patients (including their caregivers) and the drive for active consumer involvement are two key factors that underline the importance of clear communication and collaborative decision making. Health professionals are accountable for their decisions and service provision to various stakeholders, including patients, health sector managers, policy-makers and colleagues. An important aspect of this accountability is the ability to clearly articulate and justify management decisions. Considerable research across the health disciplines has investigated the nature of clinical reasoning and its relationship with knowledge and expertise. However, physiotherapy research literature to date has not specifically addressed the interaction between communication and clinical reasoning in practice, neither has it explored modes and patterns of learning that facilitate the acquisition of this complex skill. The purpose of this research was to contribute to the profession’s knowledge base a greater understanding of how experienced physiotherapists having learned to reason, then learn to communicate their clinical reasoning with patients and with novice physiotherapists. Informed by the interpretive paradigm, a hermeneutic phenomenological research study was conducted using multiple methods of data collection including observation, written reflective exercises and repeated semi-structured interviews. Data were analysed using phenomenological and hermeneutic strategies involving in-depth, iterative reading and interpretation to identify themes in the data. Twelve physiotherapists with clinical and supervisory experience were recruited from the areas of cardiopulmonary, musculoskeletal and neurological physiotherapy to participate in this study. Participants’ learning journeys were diverse, although certain factors and episodes of learning were common or similar. Participation with colleagues, peers and students, where the participants felt supported and guided in their learning, was a powerful way to learn to reason and to communicate reasoning. Experiential learning strategies, such as guidance, observation, discussion and feedback were found to be effective in enhancing learning of clinical reasoning and its communication. The cultural and environmental context created and supported by the practice community (which includes health professionals, patients and caregivers) was found to influence the participants’ learning of clinical reasoning and its communication. Participants reported various incidents that raised their awareness of their reasoning and communication abilities, such as teaching students on clinical placements, and informal discussions with peers about patients; these were linked with periods of steep learning of both abilities. Findings from this research present learning to reason and to communicate reasoning as journeys of professional socialisation that evolve through higher education and in the workplace. A key finding that supports this view is that clinical reasoning and its communication are embedded in the context of professional practice and therefore are best learned in this context of becoming, and developing as, a member of the profession. Communication of clinical reasoning was found to be both an inherent part of reasoning and an essential and complementary skill necessary for sound reasoning, that was embedded in the contextual demands of the task and situation. In this way clinical reasoning and its communication are intertwined and should be learned concurrently. The learning and teaching of clinical reasoning and its communication should be synergistic and integrated; contextual, meaningful and reflexive.