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Modeling context-dependent systems for their analysis is challenging as verification tools usually rely on an input language close to imperative programming languages which need not support description of contexts well. We introduce the concept of contextualized programs where operational behaviors and context knowledge are modeled separately using domain-specific formalisms. For behaviors specified in stochastic guarded-command language and contextual knowledge given by OWL description logic ontologies, we develop a technique to efficiently incorporate contextual information into behavioral descriptions by reasoning about the ontology. We show how our presented concepts support and facilitate the quantitative analysis of context-dependent systems using probabilistic model checking. For this, we evaluate our implementation on a case study issuing a multi-server system.

The Golog action programming language is a powerful means to express high-level behaviours in terms of programs over actions defined in a Situation Calculus theory. In particular for physical systems, verifying that the program satisfies certain desired temporal properties is often crucial, but undecidable in general, the latter being due to the language’s high expressiveness in terms of first-order quantification and program constructs. So far, approaches to achieve decidability involved restrictions where action effects either had to be contextfree (i.e. not depend on the current state), local (i.e. only affect objects mentioned in the action’s parameters), or at least bounded (i.e. only affect a finite number of objects). In this paper, we present a new, more general class of action theories (called acyclic) that allows for context-sensitive, non-local, unbounded effects, i.e. actions that may affect an unbounded number of possibly unnamed objects in a state-dependent fashion. We contribute to the further exploration of the boundary between decidability and undecidability for Golog, showing that for acyclic theories in the two-variable fragment of first-order logic, verification of CTL properties of programs over ground actions is decidable.

The modal satisfiability problem has to date been solved using either a specifically designed algorithm, or by translating the modal logic formula into a different class of problem, such as a first-order logic, a propositional satisfiability problem or a constraint satisfaction problem. These approaches and the solvers developed to support them are surveyed and a synthesis thereof is presented. The translation of a modal K formula into a constraint satisfaction problem, as developed by Brand et al. [18], is further enhanced. The modal formula, which must be in conjunctive normal form, is translated into layered propositional formulae. Each of these layers is translated into a constraint satisfaction problem and solved using the constraint solver ECLiPSe. I extend this translation to deal with reflexive and transitive accessibility relations, thereby providing for the modal logics KT and S4. Two of the difficulties that arise when these accessibility relations are added are that the resultant formula increases considerably in complexity, and that it is no longer in conjunctive normal form (CNF). I eliminate the need for the conversion of the formula to CNF and deal instead with formulae that are in negation normal form (NNF). I apply a number of enhancements to the formula at each modal layer before it is translated into a constraint satisfaction problem. These include extensive simplification, the assignment of a single value to propositional variables that occur only positively or only negatively, and caching the status of the formula at each node of the search tree. All of these significantly prune the search space. The final results I achieve compare favorably with those obtained by other solvers. / Computing / M.Sc. (Computer Science)

Usability aspects of programming languages are often overlooked, yet have a substantial effect on programmer productivity. These issues are even more acute in the field of Inductive Synthesis, where programs are automatically generated from sample expected input and output data, and the programmer needs to be able to comprehend, and confirm or reject the suggested programs. A promising method of Inductive Synthesis, CombInduce, which is particularly suitable for synthesizing recursive programs, is a candidate for improvements in usability as the target language Combilog is not user-friendly. The method requires the target language to be strictly compositional, hence devoid of variables, yet have the expressiveness of definite clause programs. This sets up a challenging problem for establishing a user-friendly but equally expressive target language. Alternatives to Combilog, such as Quine's Predicate-functor Logic and Schönfinkel and Curry's Combinatory Logic also do not offer a practical notation: finding a more usable representation is imperative. This thesis presents two distinct approaches towards more convenient representations which still maintain compositionality. The first is Visual Combilog (VC), a system for visualizing Combilog programs. In this approach Combilog remains as the target language for synthesis, but programs can be read and modified by interacting with the equivalent diagrams instead. VC is implemented as a split-view editor that maintains the equivalent Combilog and VC representations on-the-fly, automatically transforming them as necessary. The second approach is Combilog with Name Projection (CNP), a textual iteration of Combilog that replaces numeric argument positions with argument names. The result is a language where argument names make the notation more readable, yet compositionality is preserved by avoiding variables. Compositionality is demonstrated by implementing CombInduce with CNP as the target language, revealing that programs with the same level of recursive complexity can be synthesized in CNP equally well, and establishing the underlying method of synthesis can also work with CNP. Our evaluations of the user-friendliness of both representations are supported by a range of methods from Information Visualization, Cognitive Modelling, and Human-Computer Interaction. The increased usability of both representations are confirmed by empirical user studies: an often neglected aspect of language design.

The modal satisfiability problem has to date been solved using either a specifically designed algorithm, or by translating the modal logic formula into a different class of problem, such as a first-order logic, a propositional satisfiability problem or a constraint satisfaction problem. These approaches and the solvers developed to support them are surveyed and a synthesis thereof is presented. The translation of a modal K formula into a constraint satisfaction problem, as developed by Brand et al. [18], is further enhanced. The modal formula, which must be in conjunctive normal form, is translated into layered propositional formulae. Each of these layers is translated into a constraint satisfaction problem and solved using the constraint solver ECLiPSe. I extend this translation to deal with reflexive and transitive accessibility relations, thereby providing for the modal logics KT and S4. Two of the difficulties that arise when these accessibility relations are added are that the resultant formula increases considerably in complexity, and that it is no longer in conjunctive normal form (CNF). I eliminate the need for the conversion of the formula to CNF and deal instead with formulae that are in negation normal form (NNF). I apply a number of enhancements to the formula at each modal layer before it is translated into a constraint satisfaction problem. These include extensive simplification, the assignment of a single value to propositional variables that occur only positively or only negatively, and caching the status of the formula at each node of the search tree. All of these significantly prune the search space. The final results I achieve compare favorably with those obtained by other solvers. / Computing / M.Sc. (Computer Science)

The inadequacy of the usual possible world semantics of modal languages when the meaning of 'belief' is attached to the modal operator is discussed. Three other approaches are then investigated. In the case of Moore's autoepistemic logic it becomes possible to compare an agent's beliefs to 'reality', which cannot be done directly in the possible world semantics. Levesque's semantics makes explicit in the object language the notion of 'this is all the information the agent has', which plays an important role in nonmonotonic reasoning. Both of these approaches deal with ideal reasoners. The third approach, Konolige's deduction model, is based on a semantics capable of describing the beliefs of one or more resourcebounded agents. Finally, the AGM postulates for belief revision are discussed. / Computer Science / M.Sc. (Computer Science)

Este trabalho introduz uma técnica chamada Answer Set Programming Probabilístico (PASP), que permite a modelagem de teorias complexas e a verificação de sua consistência em relação a um conjunto de dados estatísticos. Propomos métodos de resolução baseados em uma redução para o problema da satisfazibilidade probabilística (PSAT) e um método de redução de Turing ao ASP. / This dissertation introduces a technique called Probabilistic Answer Set Programming (PASP), that allows modeling complex theories and check its consistence with respect to a set of statistical data. We propose a method of resolution based in the reduction to the probabilistic satisfiability problem (PSAT) and a Turing reduction method to ASP.

Apesar de sua inerente indecidibilidade e do problema da negação, extensões da lógica de primeira ordem tem se mostrado capazes de superar a questão da monotonicidade, vindo a constituir esquemas de representação de conhecimento de expressividade virtualmente universal. Resta entretanto solucionar ou pelo menos amenizar as conseqüências do problema do controle, que limitam o seu emprego a aplicações de pequeno a médio porte. Investigações nesse sentido [BOW 85] [MON 88] indicam que a chave para superar a explosão inferencial passa obrigatoriamente pela estruturação do conhecimento, de modo a permitir o exercício de algum controle sobre as possíveis derivações dele decorrentes. O modelo das hiperredes [GEO 85] parece atingir tal objetivo, dado o seu elevado potencial de estruturação e o instrumental que oferece para o tratamento de construções descritivas, operacionais e organizacionais. Além disso, a simplicidade e uniformidade sintática de suas entidades primitivas possibilita uma interpretação semântica bastante clara do modelo original, por exemplo, baseada em grafos. O presente trabalho representa uma tentativa de associar a programação em lógica ao formalismo das hiperredes, visando obter um novo modelo capaz de preservar as expressividade da primeira, beneficiando-se simultaneamente do potencial heurístico e estrutura do segundo. Inicialmente procura-se obter uma noção clara da natureza do conhecimento e de seus mecanismos com o objetivo de caracterizar o problema da representação de conhecimento. Diferentes esquemas correntemente empregados para esse fim (sistemas de produções, redes semânticas, sistemas de frames, programação em lógica e a linguagem Krypton) são estudados e caracterizados do ponto de vista de sua expressividade, potencial heurístico e conveniência notacional. A programação em lógica é objeto de um estudo em maior profundidade, sob os enfoques modelo-teorético e prova-teorético. Sistemas de programação em lógica - particularmente a linguagem Prolog e extensões em nível meta - são investigados como esquemas de representação de conhecimento, considerando seus aspectos sintáticos e semânticos e a sua retação com Sistemas Gerenciadores de Bases de Dados. O modelo das hiperredes é apresentado introduzindo-se, entre outros, os conceitos de hipernodo, hiperrelação e protótipo, assim como as propriedades particutares de tais entidades. A linguagem Hyper, para o tratamento de hiperredes, é formalmente especificada. Emprega-se a linguagem Prolog como formalismo para a representação de Bases de Conhecimento estruturadas segundo o modelo das hiperredes. Sob tal abordagem uma Base de Conhecimento é vista como um conjunto (possivelmente vazio) de objetos estruturados ou peças de conhecimento, que por sua vez são classificados como hipernodos, hiperrelações ou protótipos. Um mecanismo top-down para a produção de inferências em hiperredes é proposto, introduzindo-se os conceitos de aspecto e visão sobre hiperredes, os quais são tomados como objetos de primeira classe, no sentido de poderem ser valores atribuídos a variáveis. Estuda-se os requisitos que um Sistema Gerenciador de Bases de Conhecimento deve apresentar, do ponto de vista da aplicação, da engenharia de conhecimento e da implementação, para suportar efetivamente os conceitos e abstrações (classificação, generalização, associação e agregação) associadas ao modelo proposto. Com base nas conclusões assim obtidas, um Sistema Gerenciador de Bases de Conhecimento (denominado Rhesus em alusão à sua finalidade experimental é proposto e especificado, objetivando confirmar a viabilidade técnica do desenvolvimento de aplicações baseadas em lógica e hiperredes. / In spite of its inherent undecidability and the negation problem, extensions of first-order logic have been shown to be able to overcome the question of the monotonicity, establishing knowledge representation schemata with virtuatLy universal expressiviness. However, one still has to solve, or at Least to reduce the consequences of the control problem, which constrains the use of Logic-based systems to either small or medium-sized applications. Investigations in this direction [BOW 85] [MON 88] indicate that the key to overcome the inferential explosion resides in the proper knowledge structure representation, in order to have some control over possible derivations. The Hypernets Model [GEO 85] seems to reach such goat, considering its high structural power and the features that it offers to deal with descriptive, operational and organizational knowledge. Besides, the simplicity and syntactical uniformity of its primitive notions allows a very clear definition for its semantics, based, for instance, on graphs. This work is an attempt to associate logic programming with the hypernets formalism, in order to get a new model, preserving the expressiveness of the former and the heuristic and structural power of the latter. First we try to get a clear notion of the nature of knowledge and its main aspects, intending to characterize the knowledge representation problem. Some knowledge representation schemata (production systems, semantic networks, frame systems, Logic programming and the Krypton Language) are studied and characterized from the point of view of their expressiveness, heuristic power and notational convenience. Logic programming is the subject of a deeper study, under the model-theoretic and proof-theoretic approaches. Logic programming systems - in particular the Prolog Language and metateuel extensions- - are investigated as knowledge representation schemata, considering its syntactic and semantic aspects and its relations with Data Base Management Systems. The hypernets model is presented, introducing the concepts of hypernode, hyperrelation and prototype, as well as the particular properties of those entities. The Hyper language, for the handling of h y pernets, is formally specified. Prolog is used as a formalism for the representation of Knowledge Bases which are structured as hypernets. Under this approach a Knowledge Brie is seen rrG a (possibly empty) set of structured objects, which are classified as hypernodes, hyperreLations or prototypes. A mechanism for top-down reasoning on hypernets is proposed, introducing the concepts of aspect and vision, which are taken as first-class objects in the sense that they could be (-Ysigned as values to variables. We study the requirements for the construction of a Knowledge Base Management System from the point of view of the user's need-1', knowledge engineering support and implementation issues, actually supporting the concepts and abstractions (classification, generalization, association and aggregation) rYsociated with the proposed model. Based on the conclusions of this study, a Knowledge Base Management System (called Rhesus, refering to its experimental objectives) is proposed, intending to confirm the technical viability of the development of applications based on logic and hypernets.

This thesis introduces a new methodology for robust form parameter design of complex hull form geometry via constraint programming, automatic differentiation, interval arithmetic, and truncated hierarchical B- splines. To date, there has been no clearly stated methodology for assuring consistency of general (equality and inequality) constraints across an entire geometric form parameter ship hull design space. In contrast, the method to be given here can be used to produce guaranteed narrowing of the design space, such that infeasible portions are eliminated. Furthermore, we can guarantee that any set of form parameters generated by our method will be self consistent. It is for this reason that we use the title feasible form parameter design. In form parameter design, a design space is represented by a tuple of design parameters which are extended in each design space dimension. In this representation, a single feasible design is a consistent set of real valued parameters, one for every component of the design space tuple. Using the methodology to be given here, we pick out designs which consist of consistent parameters, narrowed to any desired precision up to that of the machine, even for equality constraints. Furthermore, the method is developed to enable the generation of complex hull forms using an extension of the basic rules idea to allow for automated generation of rules networks, plus the use of the truncated hierarchical B-splines, a wavelet-adaptive extension of standard B-splines and hierarchical B-splines. The adaptive resolution methods are employed in order to allow an automated program the freedom to generate complex B-spline representations of the geometry in a robust manner across multiple levels of detail. Thus two complementary objectives are pursued: ensuring feasible starting sets of form parameters, and enabling the generation of complex hull form geometry.