Thesis (Ph.D.)--Boston University / The problem of this dissertation is to present a critical exposition of the place of reason in Paul Tillich's conception of God. A discussion of the definition of reason as well as the place of reason in man and in his knowledge of God is a prerequisite to the consideration of the central problem of the dissertation. Reason is defined in terms of its ontological and technical functions. Ontological reason is active in the awareness or intuition of God and the ideal norms of goodness, beauty and truth. Ontological reason functions to relate man to that which is ultimately real. Technical reason, on the other hand, functions to appropriate all knowledge, to organize all experience into a consistent unity. But it is the same reason which is active in each case. Man is a composite unity of form (reason) and vitality (power). In essence man is in unity with God, man's logos is united with God's logos. In his essential nature, then, man is united with God and there is no distinction between reason and revelation. But man is free as well as rational, and he exercises his freedom to act by acting partially against his logos. In so doing man comes into existence. Thus existential man is in partial separation from and partial union with God. In existence man's reason is "fallen," it does not perceive God with absolute clarity. But existential reason is not wholly depraved; it still has the capacity to apprehend the world meaningfully and to be aware of God. Indeed, reason is the common basis upon which communication between God and man is possible. Though reason cannot produce the experience of unity with God, reason performs the important functions of receiving, judging and appropriating revelation. [TRUNCATED]

Ontological database management systems are a powerful tool that combine traditional database techniques with ontological reasoning methods. In this setting, a classical extensional database is enriched with an ontology, or a set of logical assertions, that describe how new, intensional knowledge can be derived from the extensional data. Conjunctive queries are therefore answered against this combined knowledge base of extensional and intensional data. Many languages that represent ontologies have been introduced in the literature. In this thesis we will focus on existential rules (also called tuple-generating dependencies or Datalog^± rules), and three established languages in this area, namely guarded-based rules, sticky rules and weakly-acyclic rules. The main goal of the thesis is to enrich these languages with non-deterministic constructs (i.e. disjunctions) and investigate the complexity of the answering conjunctive queries under these extended languages. As is common in the literature, we will distinguish between combined complexity, where the database, the ontology and the query are considered as input, and data complexity, where only the database is considered as input. The latter case is relevant in practice, as usually the ontology and the query can be considered as fixed, and are usually much smaller than the database itself. After giving appropriate definitions to extend the considered languages to disjunctive existential rules, we establish a series of complexity results, completing the complexity picture for each of the above languages, and four different query languages: arbitrary conjunctive queries, bounded (hyper-)treewidth queries, acyclic queries and atomic queries. For the guarded-based languages, we show a strong 2EXPTIME lower bound for general queries that holds even for fixed ontologies, and establishes 2EXPTIME-completeness of the query answering problem in this case. For acyclic queries, the complexity can be reduced to EXPTIME, if the predicate arity is bounded, and the problem even becomes tractable for certain restricted languages, if only atomic queries are used. For ontologies represented by sticky disjunctive rules, we show that the problem becomes undecidable, even in the case of data complexity and atomic queries. Finally, for weakly-acyclic rules, we show that the complexity increases from 2EXPTIME to coN2EXPTIME in general, and from tractable to coNP in case of the data complexity, independent of which query language is used. After answering the open complexity questions, we investigate applications and relevant consequences of our results for description logics and give two generic complexity statements, respectively, for acyclic and general conjunctive query answering over description logic knowledge bases. These generic results allow for an easy determination of the complexity of this reasoning task, based on the expressivity of the considered description logic.

Conformément aux principes de la médecine factuelle, les guides de bonne pratique clinique (GBPC) sont élaborés dans un but d'amélioration de la qualité des soins. Pourtant, le suivi des recommandations par les médecins reste faible, même lorsqu'elles sont intégrées dans des systèmes informatisés d'aide à la décision. En effet, elles sont souvent critiquées pour leur manque de flexibilité, et leur incapacité à gérer la singularité des patients rencontrés en pratique clinique. En particulier, leur orientation monopathologique est en inadéquation avec la réalité de patients bien souvent polypathologiques. Nos travaux portent sur la proposition d'une méthode basée sur un raisonnement ontologique pour permettre la conciliation de GBPC pour la prise en charge flexible de patients polypathologiques au sein d'un système d'aide à la décision. Les bases de connaissances reposent sur des règles construites par formalisation des recommandations, dont les critères patients sont organisés par une ontologie du domaine, permettant de produire un graphe des profils cliniques structuré par généralisation. Le raisonnement ontologique permet une juste adaptation des connaissances aux niveaux d'abstraction variables de la description du patient. Cette méthode a été implémentée dans un système d'aide à la décision, appelé GO-DSS, et appliquée à la prise en charge de patients diabétiques et hypertendus, à partir des GBPC produits par la société VIDAL (VIDAL Recos). Le prototype et ses interfaces ont été évalués qualitativement par un échantillon d'utilisateurs comprenant à la fois des informaticiens avec des connaissances médicales et des médecins avec des compétences en informatique. / Clinical practice guidelines (CPGs) are elaborated according to evidence-based medicine principles in order to improve healthcare quality. However, even when they are integrated into clinical decision support systems, recommendations are poorly implemented by physicians. Indeed, CPGs are often criticized for their lack of flexibility, and their inability to handle the singularity of patients encountered in clinical practice. In particular, CPGs are usually elaborated for a single pathology whereas patients usually suffer from multiple pathologies and comorbidities. We have proposed a method based on an ontological reasoning to enable the reconciliation of single-pathology CPGs to support the flexible management of patients with multiple pathologies. Knowledge bases are made of decision rules that formalize the content of single-pathology CPGs. Patient criteria are organized by a domain ontology, which allows the generation of a generalization-ordered graph of clinical patient profiles. The ontological reasoning allows to reason at different levels of abstraction to process clinical cases described with different levels of completeness. This method has been implemented in a decision support system called GO-DSS, and applied to the management of patients suffering from both arterial hypertension and type 2 diabetes, on the basis of CPGs produced by the VIDAL company (VIDAL Recos). The prototype and its user interfaces have been qualitatively evaluated by a sample of users including both computer scientists with medical knowledge and physicians with computer skills.

Cette thèse vise à définir des techniques pour mieux exploiter les connaissances du domaine dans l’objectif de rendre compte de la réalité de systèmes qualifiés de complexes et critiques. La modélisation est une étape indispensable pour effectuer des vérifications et exprimer des propriétés qu’un système doit satisfaire. La modélisation est une représentation simplificatrice, mais réductionniste de la réalité d’un système. Or, un système complexe ne peut se réduire à un modèle. Un modèle doit s’intégrer dans sa théorie observationnelle pour rendre compte des anomalies qu’il peut y contenir. Notre étude montre clairement que le contexte est la première problématique à traiter car principale source de conflits dans le processus de conception d’un système. L’approche retenue dans cette thèse est celle d’intégrer des connaissances du domaine en associant le système à concevoir à des formalismes déclaratifs qualifiés de descriptifs appelés ontologies. Notre attention est portée au formalisme Event-B dont l’approche correct-par-construction appelée raffinement est le principal mécanisme dans ce formalisme qui permet de faire des preuves sur des représentations abstraites de systèmes pour exprimer/vérifier des propriétés de sûreté et d’invariance. Le premier problème traité concerne la représentation et la modélisation des connaissances du contexte en V&V de modèles. Suite à l’étude des sources de conflits, nous avons établi de nouvelles règles pour une extraction de connaissances liées au contexte par raffinement pour la V&V. Une étude des formalismes de représentation et d’interprétation logiques du contexte a permis de définir un nouveau mécanisme pour mieux structurer les modèles Event-B. Une deuxième étude concerne l’apport des connaissances du domaine pour la V&V. Nous définissons une logique pour le formalisme Event-B avec contraintes du domaine fondées sur les logiques de description, établissons des règles à exploiter pour l’intégration de ces connaissances à des fins de V&V. L’évaluation des propositions faites portent sur des études de cas très complexes telles que les systèmes de vote dont des patrons de conception sont aussi développés dans cette thèse. Nous soulevons des problématiques fondamentales sur la complémentarité que peut avoir l’intégration par raffinement des connaissances du domaine à des modèles en exploitant les raisonnements ontologiques, proposons de définir de nouvelles structures pour une extraction partiellement automatisée / This thesis aims at defining techniques to better exploit the knowledge provided from the domain in order to account for the reality of systems described as complex and critical. Modeling is an essential step in performing verifications and expressing properties that a system must satisfy according to the needs and requirements established in the specifications. Modeling is a representation that simplifies the reality of a system. However, a complex system can not be reduced to a model. A model that represents a system must always fit into its observational theory to account for any anomalies that it may contain. Our study clearly shows that the context is the first issue to deal with as the main source of conflict in the design process of a system. The approach adopted in this thesis is that of integrating knowledge of the domain by associating the system to design with declarative formalisms qualified of descriptive ones that we call ontologies. We pay a particular attention to the Event-B formalism, whose correct-by-construction approach called refinement is the main mechanism at the heart of this formalism, which makes it possible to make proofs on abstract representations of systems for expressing and verifying properties of safety and invariance. The first problem treated is the representation and modeling of contextual knowledge in V&V of models. Following to the study looked at the different sources of conflict, we established new definitions and rules for a refinement context knowledge extraction for Event-B V&V. A study of logical formalisms that represent and interpret the context allowed us to define a new mechanism for better structuring Event-B models. A second study concerns the contribution that domain knowledge can make to the V&V of models. We define a logic for the Event-B formalism with domain constraints based on the description logic, and we define rules to integrate domain knowledge for model V&V. The evaluation of the proposals made deal with very complex case studies such as voting systems whose design patterns are also developed in this thesis. We raise fundamental issues about the complementarity that the integration of domain knowledge can bring to Event-B models by refinement using ontological reasoning, and we propose to define a new structures for a partially automated extraction on both levels, namely the V&V