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This project is part of the Graduate Program in Educational Technology, Development of Educational Technologies and it aims at developing, as a final product, a Serious Game named Super Mario Logic in order to help in the teaching and learning process of logic programming which is essential to the professional future of the area. It is through logic programming that students learn to develop algorithms, which are sequences of steps used to reach a specific result. From the development of algorithms there are the programming stages, in which a significant study of logic programming and algorithms plays a key role for the programmer. This project aims at developing a serious game that challenges students into solving problems in logic programming. Serious games are becoming popular as they help students learn, making them interact and learn in an educational and playful way beyond the traditional teaching pattern. The game is being developed through a methodology called INTERAD, which is used for the development of Educational Interfaces. / Esta dissertação faz parte do Programa de Pós-Graduação Stricto Sensu em Tecnologias Educacionais em Rede, linha de Desenvolvimento de Tecnologias Educacionais em Rede e tem como produto final um Jogo Sério chamado Super Mário Logic, para Lógica de Programação, disciplina esta essencial ao futuro profissional da área. Por meio dela, o estudante aprende a desenvolver algoritmos, que são sequências de passos para chegar a um determinado resultado. A partir do desenvolvimento de algoritmos tem-se a etapa da programação, na qual um significante estudo da Lógica de Programação e de Algoritmos desempenham papel fundamental para o programador. Este trabalho foi elaborado com o objetivo de desenvolver um Jogo Sério para desafiar o aluno a resolver problemas de lógica de programação. Os Jogos Sérios estão se popularizando, pois ajudam na aprendizagem do aluno, envolvendo-o, fazendo-o interagir e gerar resultados de uma forma educativa e lúdica, saindo do padrão de ensino tradicional. Os Jogos Sérios têm por finalidade melhorar aspectos específicos da aprendizagem, com o intuito de reforçar um aprendizado específico. O jogo foi desenvolvido por meio da metodologia INTERAD, utilizada para desenvolvimento de Interfaces Educacionais.

abstract: Different logic-based knowledge representation formalisms have different limitations either with respect to expressivity or with respect to computational efficiency. First-order logic, which is the basis of Description Logics (DLs), is not suitable for defeasible reasoning due to its monotonic nature. The nonmonotonic formalisms that extend first-order logic, such as circumscription and default logic, are expressive but lack efficient implementations. The nonmonotonic formalisms that are based on the declarative logic programming approach, such as Answer Set Programming (ASP), have efficient implementations but are not expressive enough for representing and reasoning with open domains. This dissertation uses the first-order stable model semantics, which extends both first-order logic and ASP, to relate circumscription to ASP, and to integrate DLs and ASP, thereby partially overcoming the limitations of the formalisms. By exploiting the relationship between circumscription and ASP, well-known action formalisms, such as the situation calculus, the event calculus, and Temporal Action Logics, are reformulated in ASP. The advantages of these reformulations are shown with respect to the generality of the reasoning tasks that can be handled and with respect to the computational efficiency. The integration of DLs and ASP presented in this dissertation provides a framework for integrating rules and ontologies for the semantic web. This framework enables us to perform nonmonotonic reasoning with DL knowledge bases. Observing the need to integrate action theories and ontologies, the above results are used to reformulate the problem of integrating action theories and ontologies as a problem of integrating rules and ontologies, thus enabling us to use the computational tools developed in the context of the latter for the former. / Dissertation/Thesis / Ph.D. Computer Science 2012

Nous nous intéressons aux approches formelles pour le développement de systèmes réactifs critiques. Le langage synchrone Lustre pour la spécification de tels systèmes a subit des évolutions majeurs au cours des dernières années en intégrant dans sa sémantique à base flots de données synchrones des constructions de plus haut-niveau appelées automates de modes (dans le langage Scade 6). Ceux-ci mettent en œuvre l’activation de modes de calculs en fonction des états et des transitions de l’automate, et reposent pour cela sur la sémantique des horloges du langage Lustre. En particulier, nous étudiions la prise en compte des horloges et des automates de modes dans l’outil de génération de tests GATeL dédié à l’origine au langage Lustre mono-horloge (flots de données purs). GATeL génère automatiquement des séquences de tests pour un modèle à partir d’un objectif de test décrit en Lustre à travers une exploration en arrière des dépendances entre flots et selon des teniques de résolution de contraintes. Nous présentons ces différents domaines et la mise en oeuvre des modifications apportées à l’outil pour prendre en compte les automates de modes. Enfin, nous définissons des critères de couverture structurelle pour les automates de modes et montrons alors comment, en les traduisant de manière automatique sous forme d’objectifs de tests, GATeL permet de générer des séquences couvrant ces critères. / Lustre is a synchronous dataflow-oriented language for the specification of reactive systems. Since its definition, it has been extended to support mode automata, a formalism in which computation modes are activated according to an extended state-machine. The semantics of mode-automata is heavily based on an appropriate use of the clock sampling features of Lustre. We present the modifications made in GATeL, an automatic test sequences generator originally designed for a mono-rate subset of Lustre. GATeL performs a lazy goal-oriented test sequences generation, based on constraint logic programming. We modify it so that it can handle the temporal constraints of clocks internally and efficiently generate tests sequences from state-maines specifications. We also present some existing structural test criteria for state-machines and adapt them to the specific case of mode-automata.

Este trabalho investiga Aprendizado Indutivo de Máquina como função das linguagens de descrição, utilizadas para expressar instancias, conceitos e teoria do domínio. A ampliação do poder de representação do aprendizado proporcional e abordada no contexto de indução construtiva, no domínio de funções booleanas, com a proposta de uma estratégia de composição de atributos denominada root-fringe. Avaliações experimentais dessa e de outras estratégias de construção de novos atributos foram conduzidas e os resultados analisados. Dois métodos de poda, para tratamento de ruídos, em aprendizado de arvores de decisão, foram avaliados num ambiente de indução construtiva e os resultados discutidos. Devido a limitação do aprendizado proposicional, foram investigadas formas de ampliação dos limites do aprendizado, através da ampliação do poder representacional das linguagens de descrição. Foi escolhida Programação Lógica Indutiva - PLI - que e um paradigma de aprendizado indutivo que usa restrições de Lógica de Primeira Ordem como linguagens de descrição. O aprendizado em PLI só é factível quando as linguagens utilizadas estão restritas e é fortemente controlado, caso contrário, o aprendizado em PLI se torna indecidível. A pesquisa em PLI se direcionou a formas de restrição das linguagens de descrição da teoria do domínio e de hipóteses. Três algoritmos que \"traduzem\" a teoria do domínio de sua forma intencional, para extensional, são apresentados. As implementações de dois deles são discutidas. As implementações realizadas deram origem a dois ambientes experimentais de aprendizado: o ambiente proposicional experimental, do qual fazem parte o ambiente experimental construtivo, e o ambiente experimental relacional. / This work investigates Inductive Machine Learning as a function of the description languages employed to express instances, concepts and domain theory. The enlargement of the representational power of propositional learning methods is approached via constructive induction, in the domain of boolean functions, through the proposal of a bias for composing attributes, namely, the bias root-fringe. Experimental evaluation of root-fringe, as well as other biases for constructing new attributes was conducted and the results analyzed. Two pruning methods for decision trees were evaluated in an environment of constructive induction and the results discussed. Due to the limitations of propositional learning, ways of enlarging the limits of the learning process were investigated through enlarging the representational power of the description languages. It was chosen Inductive Logic Programming - ILP - that is an inductive learning paradigm that uses restrictions of First Order Logic as description languages. Learning using ILP is only feasible when the languages are restricted and are strongly controlled; otherwise, learning in ILP becomes undecidible. Research work in ILP was directed towards restricting domain theory and hypotheses description languages. Three algorithms that \"translate\" the intentional expression of a domain theory into its extensional expression are presented. The implementations of two of them are discussed. The implementations gave rise to two experimental learning environments: the propositional environment, which includes the constructive environment, and the relational environment.

[pt] Esta dissertação apresenta uma integração entre a programação funcional e a programação em lógica, obtida pela definição e implementação da Linguagem LispLog. Nesta nova linguagem, o resultado de uma resolução pode ser utilizado como argumento de uma função (pelo operador metalisp) e o resultado da avaliação de uma função pode ser ligado a uma variável lógica (pelo operador avalia). A construção desta linguagem foi realizada a partir da simulação, em microcomputador similar ao IBM-PC, de uma máquina com arquitetura de pilhas, chamada Máquina LispLog, e de seu compilador. A utilização desta linguagem é possível através do Sistema LispLog, que fornece um ambiente de programação orientado por menus. / [en] This dissertation shows an integration between the function programming and logic programming, achieved through LispLog Language’s definition and implementation. In this new language the resultant of a resolution may be used as an argument of a function (through metalisp operator) and the result of a function’s avaliation may be linked to a logic variable (through avalia operator). The LispLog Language was constructed by a simulation of stack architecture machine, named LispLog Machine, and its compiler, in a microcomputer similar similar to IBM-PC. The LispLog System provides a programming environment oriented by menus, wich makes possible the use of this language

Model checking is a formal verification method where one tries to prove or disprove properties of a formal system. Typical systems one might want to prove properties within are network protocols and digital circuits. Typical properties to check for are safety (nothing bad ever happens) and liveness (something good eventually happens). This thesis describes an implementation of a sound and complete model checker for Computation Tree Logic (CTL) using Constraint Logic Programming over Finite Domains (CLP(FD)). The implementation described uses tabled resolution to remember earlier computations, is parameterised by choices of computation strategies and can with slight modification support different constraint domains. Soundness under negation is maintained through a restricted form of constructive negation. The computation process amounts to a fixpoint search, where a fixpoint is reached when no more extension operations has any effect. As results show, the choice of strategies does influence the efficiency of the computation. Soundness and completeness are of course independent of the choice of strategies. Strategies include how to choose the extension operation for the next step and whether to perform global or local rule instantiations, resulting in bottom-up or top-down computations respectively.

There are two symmetrical resolution rules applicable to logic programs - SL-resolution which yields a top-down refutation and unit-resolution which yields a bottom-up refutation. Both resolution principles need to be coupled with a search rule before they can be used in practice. The search rule determines in which order program clauses are used in the refutation and affects both performance, completeness and quality of solutions. The thesis surveys exhaustive and heuristic search rules for SL-resolution and transformation techniques for (general) logic programs that makes unit-resolution goal oriented. The search rules were implemented as meta-interpreters for Prolog and were benchmarked on a suite of programs incorporating both deterministic and nondeterministic code. Whenever deemed applicable benchmark programs were permuted with respect to clause and goal ordering to see if it affected the interpreters performance and termination. With the help of the evaluation the conclusion was that alternative search rules for SL-resolution should not be used for performance gains but can in some cases greatly improve the quality of solutions, e.g. in planning or other applications where the quality of an answer correlates with the length of the refutation. It was also established that A* is more flexible than exhaustive search rules since its behavior can be fine-tuned with weighting, and can in some cases be more efficient than both iterative deepening and breadth-first search. The bottom-up interpreter based on unit-resolution and magic transformation had several advantages over the top-down interpreters. Notably for programs where subgoals are recomputed many times. The great disparity in implementation techniques made direct performance comparisons hard however, and it is not clear if even an optimized bottom-up interpreter is competitive against a top-down interpreter with tabling of answers.

In an ever faster changing environment, software developers not only need agile methods, but also agile programming paradigms and tools. A paradigm shift towards declarative programming has begun; a clear indication of this is Microsoft's substantial investment in functional programming. Moreover, several attempts have been made to enable visual programming. We believe that software development is ready for a new paradigm which goes beyond any existing declarative paradigm: visual compositional-relational programming. Compositional-relational programming (CRP) is a purely declarative paradigm -- making it suitable for a visual representation. All procedural aspects -- including the increasingly important issue of parallelization -- are removed from the programmer's consideration and handled in the underlying implementation. The foundation for CRP is a theory of higher-order combinatory logic programming developed by Hamfelt and Nilsson in the 1990's. This thesis proposes a model for visualizing compositional-relational programming. We show that the diagrams are isomorphic with the programs represented in textual form. Furthermore, we show that the model can be used to automatically generate code from diagrams, thus paving the way for a visual integrated development environment for CRP, where programming is performed by combining visual objects in a drag-and-drop fashion. At present, we implement CRP using Prolog. However, in future we foresee an implementation directly on one of the major object-oriented frameworks, e.g. the .NET platform, with the aim to finally launch relational programming into large-scale systems development.

PrologPF is a parallelising compiler targeting a distributed system of general purpose workstations connected by a relatively low performance network. The source language extends standard Prolog with the integration of higher-order functions. The execution of a compiled PrologPF program proceeds in a similar manner to standard Prolog, but uses oracles in one of two modes. An oracle represents the sequence of clauses used to reach a given point in the problem search tree, and the same PrologPF executable can be used to build oracles, or follow oracles previously generated. The parallelisation strategy used by PrologPF proceeds in two phases, which this research shows can be interleaved. An initial phase searches the problem tree to a limited depth, recording the discovered incomplete paths. In the second phase these paths are allocated to the available processors in the network. Each processor follows its assigned paths and fully searches the referenced subtree, sending solutions back to a control processor. This research investigates the use of the technique with a one-time partitioning of the problem and no further scheduling communication, and with the recursive application of the partitioning technique to effect dynamic work reassignment. For a problem requiring all solutions to be found, execution completes when all the distributed processors have completed the search of their assigned subtrees. If one solution is required, the execution of all the path processors is terminated when the control processor receives the first solution. The presence of the extra-logical Prolog predicate cut in the user program conflicts with the use of oracles to represent valid open subtrees. PrologPF promotes the use of higher-order functional programming as an alternative to the use of cut. The combined language shows that functional support can be added as a consistent extension to standard Prolog.