Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 163-169). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph.D.)--Aberdeen University, 2009. / Title from web page (viewed on June 11, 2009). Includes bibliographical references.

<p class="Abstract">The work proposed in this thesis continues the research into qualitative model learning (QML), a branch of qualitative reasoning.&nbsp; After the investigation of all existing qualitative model learning systems, especially the state-of-the-art system ILP-QSI, a novel system named QML-Morven is presented. <p class="Abstract">QML-Morven inherits many essential features of the existing QML systems: it can learn models from positive only data, make use of the well-posed model constraints, process hidden variables, learn models from incomplete data, and perform systematic experiments to verify the hypotheses being made by researchers. <p class="Abstract">The development of QML-Morven allows us to further investigate some interesting yet unsolved questions in the QML research.&nbsp; As a result, four significant hypotheses are tested and validated by performing a series of systematic experiments with QML-Morven:&nbsp; 1. The information of state variables and the number of hidden variables are two important actors that can influence the learning, and the different combination of these two factors may give a different learning result in terms of the kernel subset (minimal data for a successful learning) and learning precision; 2. The scalability of QML may be improved by the use of an evolutionary algorithm; 3. For some models, the kernel subsets can be constructed by combining several sets of qualitative states, and the states in a kernel subset tend to scatter over the solution space; 4. The integration of domain-specific knowledge makes QML more applicable for learning the qualitative models of the real-world dynamic systems of high complexity. <p class="Abstract">The results and analysis of these experiments with respect to QML-Morven also raise many questions and indicates several new research directions.&nbsp; In the final part of this thesis, several possible future directions are explored.

A mechanical design "compiler" has been developed which, given an appropriate schematic, specifications, and utility function for a mechanical design, returns catalog numbers for an optimal implementation. The compiler has been successfully tested on a variety of mechanical and hydraulic power transmission designs and a few temperature sensing designs. Times required have been at worst proportional to the logarithm of the number of possible combinations of catalog numbers.

This report describes MM, a computer program that can model a variety of mechanical and fluid systems. Given a system's structure and qualitative behavior, MM searches for models using an energy-based modeling framework. MM uses general facts about physical systems to relate behavioral and model properties. These facts enable a more focussed search for models than would be obtained by mere comparison of desired and predicted behaviors. When these facts do not apply, MM uses behavior-constrained qualitative simulation to verify candidate models efficiently. MM can also design experiments to distinguish among multiple candidate models.

I describe an approach to forming hypotheses about hidden mechanism configurations within devices given external observations and a vocabulary of primitive mechanisms. An implemented causal modelling system called JACK constructs explanations for why a second piece of toast comes out lighter, why the slide in a tire gauge does not slip back inside when the gauge is removed from the tire, and how in a refrigerator a single substance can serve as a heat sink for the interior and a heat source for the exterior. I report the number of hypotheses admitted for each device example, and provide empirical results which isolate the pruning power due to different constraint sources.

No description available.

abstract: One of the measures to determine the intelligence of a system is through Question Answering, as it requires a system to comprehend a question and reason using its knowledge base to accurately answer it. Qualitative word problems are an important subset of such problems, as they require a system to recognize and reason with qualitative knowledge expressed in natural language. Traditional approaches in this domain include multiple modules to parse a given problem and to perform the required reasoning. Recent approaches involve using large pre-trained Language models like the Bidirection Encoder Representations from Transformers for downstream question answering tasks through supervision. These approaches however either suffer from errors between multiple modules, or are not interpretable with respect to the reasoning process employed. The proposed solution in this work aims to overcome these drawbacks through a single end-to-end trainable model that performs both the required parsing and reasoning. The parsing is achieved through an attention mechanism, whereas the reasoning is performed in vector space using soft logic operations. The model also enforces constraints in the form of auxiliary loss terms to increase the interpretability of the underlying reasoning process. The work achieves state of the art accuracy on the QuaRel dataset and matches that of the QuaRTz dataset with additional interpretability. / Dissertation/Thesis / Masters Thesis Computer Science 2020

This paper explores automating the qualitative analysis of physical systems. It describes a program, called PLR, that takes parameterized ordinary differential equations as input and produces a qualitative description of the solutions for all initial values. PLR approximates intractable nonlinear systems with piecewise linear ones, analyzes the approximations, and draws conclusions about the original systems. It chooses approximations that are accurate enough to reproduce the essential properties of their nonlinear prototypes, yet simple enough to be analyzed completely and efficiently. It derives additional properties, such as boundedness or periodicity, by theoretical methods. I demonstrate PLR on several common nonlinear systems and on published examples from mechanical engineering.

A partir da promulgação da Resolução CNE/CEB Nº 2, de fevereiro de 2001, indivíduos surdos obtiveram a oportunidade de ser integrados à escola básica ao receberem acesso aos conteúdos curriculares presentes no Plano Nacional de Educação (PNE). Desde então vem se buscando metodologias que ofereçam uma educação que atenda a esses alunos de forma adequada, alicerçada não somente na linguagem verbal e escrita, mas também na primeira língua do surdo, a Língua Brasileira de Sinais (LIBRAS). Diante do desafio de propiciar o ensino, principalmente em ciências, algumas alternativas foram selecionadas a luz da Pedagogia Visual, que tem como principal alicerce o argumento de que indivíduos surdos apresentam uma capacidade visual muito além daquela possuída pelo indivíduo ouvinte. A primeira alternativa, denominada \"Mapa Conceitual\", se adéqua a Pedagogia Visual por sua estrutura em moldes de diagrama, porém ainda possui uma base muito ligada a linguagem escrita, o que dificulta o aprendizado em alunos que ainda não possuem uma fluência na língua portuguesa, ou seja, ainda não são bilíngues. Outra dificuldade se encontra nos primeiros anos do ensino fundamental, em que alunos surdos ingressantes não apresentam fluência nem mesmo em LIBRAS, mas exibem um sistema particular de sinais apoiados na visão. Esse déficit pode ser contornado pela segunda alternativa, denominada de \"Modelo Qualitativo\" baseado em Raciocínio Qualitativo (RQ). O modelo qualitativo além de apresentar uma base gráfica que atende a pedagogia visual, trabalha com modelos de causalidade, emulando um sistema da forma mais real possível para que o aluno o compreenda. Para a construção do modelo foi usado um simulador denominado de DynaLearn, desenvolvido com o objetivo de integrar o aprendizado do aluno por meio de modelos qualitativos. Para que isso aconteça foram (I) desenvolvidos modelos qualitativos sobre Poluição Humana baseados em RQ, por meio do software DynaLearn, que atendessem aos Parâmetros Curriculares Nacionais (PCN) do 6º Ano do Ensino Fundamental, especificamente em relação ao ensino de ciências. Em seguida (II) o modelo foi aplicado no ensino de Ciências Naturais, em regime de contra turno, para uma turma de alunos surdos proficientes em LIBRAS, porém deficientes em Língua Portuguesa do Ensino Fundamental I, que posteriormente (III) teve seu aprendizado avaliado por meio de questionários e transcrições das aulas. Conclui-se que a aplicação do modelo qualitativo atingiu seus objetivos ao levar os alunos a desenvolverem o raciocínio qualitativo por meio da compreensão das relações causais, da mesma maneira que o software DynaLearn satisfaz os requisitos visualização requeridos pela Pedagogia Visual, destacando alguns pontos que podem melhorar devido ao público-alvo. Também foi observado que a aquisição de conceitos científicos pelos alunos apresenta relação íntima com seus sinais correspondentes. / Since the enactment of Resolution CNE/CEB No. 2, February 2001, deaf individuals had the opportunity to be integrated into the basic school to receive access to curriculum content present in the Plano Nacional de Educação (PNE). Since then has been seeking methodologies that provide an education that attends these students adequately grounded not only in verbal and written language, but also in the first language of the deaf, the Brazilian Sign Language (known as \"Libras\"). Faced with the challenge of providing education, especially in science, some alternatives were selected in view of Visual Education, whose main foundation the argument that deaf people have a visual capacity beyond that possessed by the individual listener. The first alternative, called \"Concept Map\" fits the Visual Pedagogy by your diagram templates structure, however still has a very connected based written language, which hinders learning in students who do not have fluency in Portuguese, that is, they are not bilingual. Another difficulty is in the early years of elementary school, where new deaf students do not have fluency even in \"Libras\", but show a particular system of signs supported in the vision. This deficit can be overcome for the second alternative, called \"Qualitative Model\" based on Qualitative Reasoning (QR). The qualitative model besides presenting a graphical basis that meets the visual pedagogy, works with causal models, emulating a system more real as possible so that the student understands. For the construction of the model was used a simulator called DynaLearn developed with the aim of integrating student learning through qualitative models. To make it happen were (I) developed qualitative models on Human Pollution based in RQ, through the DynaLearn software, which met the National Curriculum Parameters (NCP) of the 6th year of elementary school, specifically in relation to science teaching. Then (II) the model was applied in the teaching of Natural Sciences, in counter-shift system, to a group of proficient deaf students in \"Libras\" but deficient in Portuguese of the elementary school, which later (III) had their learning assessed by through questionnaires and transcripts lessons. It is concluded that the application of qualitative model reached these objectives by bringing students to develop the qualitative reasoning by understanding the causal relationships in the same way that the DynaLearn software meets the requirements of view required by Visual Education, highlighting some points that can improve due to the target audience. It was also noted that the acquisition of scientific concepts by students presents a close relationship with their corresponding signals.