Automated Reasoning About Classical Mechanics

In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

How to improve the formal analytic reasoning and scientific motivation in the intellectual training of medical students

A review article of the The New England Journal of Medicine refers that almost a century ago, Abraham Flexner, a research scholar at the Carnegie Foundation for the Advancement of Teaching, undertook an assessment of medical education in 155 medical schools in operation in the United States and Canada. Flexner’s report emphasized the nonscientific approach of American medical schools to preparation for the profession, which contrasted with the university-based system of medical education in Germany. At the core of Flexner’s view was the notion that formal analytic reasoning, the kind of thinking integral to the natural sciences, should hold pride of place in the intellectual training of physicians. This idea was pioneered at Harvard University, the University of Michigan, and the University of Pennsylvania in the 1880s, but was most fully expressed in the educational program at Johns Hopkins University, which Flexner regarded as the ideal for medical education. (...)

Effectiveness of 'Reasoning and rehabilitation' in reducing reoffending. 'La eficacia del programa 'Razonamiento y Rehabilitaci??n' en la reducci??n de la reincidencia'

Resumen tomado de la publicaci??n

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

Automated Reasoning II

Resolution over FOPL

Stream Reasoning with Linked Data

Slides describing streaming data, data stream processing systems and stream reasoning Also we have some description of CSPARQL

Evolution of analogical reasoning in children: follow-up from six to eleven years old

The aim of this study is to establish the time and period of development of Analogical Reasoning (AR) and evaluate its independence and performance with respect to the age. We performed a longitudinal cohort study of two age groups and six annual follow-up phases from each one (2000-2005, 2001-2006) in six to eleven years-old children in the city of Huanuco (Peru) with a sample of 167 children (first stage), and N=121 (sixth stage). The Raven’s progressive matrices test, coloured version, was applied individually without time limits. Results indicate that AR development occurs in a constant and late way from seven to eleven years-old children, and also that there is independence between the ability of AR and the children age. We discuss the importance of knowledge in the relationships between analogies topics, adjusted to the age, as a mediating factor in the development of AR.

Verbal reasoning : multiple choice : 11 + practice papers.

Son pruebas de inteligencia objetivas para evaluar las habilidades verbales de los alumnos en un sentido más amplio que el que proporciona el contenido específico de un programa de estudios. Su objetivo es tratar de que identifiquen modelos, similitudes y diferencias entre palabras, y demostrar, además, su comprensión de las reglas y del significado específico del lenguaje en diferentes contextos.

Non-verbal reasoning : multiple choice : 11 + practice papers.

Son pruebas de inteligencia cuyas preguntas no tienen una solución que puede ser aprendida de antemano.Son utilizadas, entre otras finalidades, para conocer de los escolares de ocho a catorce años, sus capacidades para comprender y asimilar información novedosa, independientemente de sus habilidades lingüísticas.