The Bifurcation Interpreter is a computer program that autonomously explores the steady-state orbits of one-parameter families of periodically- driven oscillators. To report its findings, the Interpreter generates schematic diagrams and English text descriptions similar to those appearing in the science…

This paper describes a natural language system START. The system analyzes English text and automatically transforms it into an appropriate representation, the knowledge base, which incorporates the information found in the text. The user gains access to information stored in…

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express…

To determine why something has stopped working, it is useful to know how it was supposed to work in the first place. That simple observation underlies some of the considerable interest generated in recent years on the topic of model-based…

Combining numerical techniques with ideas from symbolic computation and with methods incorporating knowledge of science and mathematics leads to a new category of intelligent computational tools for scientists and engineers. These tools autonomously prepare simulation experiments from high-level specifications of…

This paper describes a method for limiting vibration in flexible systems by shaping the system inputs. Unlike most previous attempts at input shaping, this method does not require an extensive system model or lengthy numerical computation; only knowledge of the…

Explanation-based learning occurs when something useful is retained from an explanation, usually an account of how some particular problem can be solved given a sound theory. Many real-world explanations are not based on sound theory, however, and wrong things may…

In this paper, we present an approach to student's evaluation in a well-defined domain based on a semantic network. A similarity matrix based on the semantic memory structure of humans is used to build a semantic distance model in order…

Currently, mathematics instruction in U.S. classrooms is far from achieving equity for African American students. This qualitative study reports the results of eight successful elementary mathematics teachers’ knowledge of equity pedagogy, specifically their knowledge of culturally relevant pedagogy, cultural competence,…

Artificial neural networks (ANN) are very efficient in solving various kinds of problems But Lack of explanation capability (Black box nature of Neural Networks) is one of the most important reasons why artificial neural networks do not get necessary interest…