Nhon V. Do

Designing an intelligent problems solving system based on knowledge about sample problems

In computer science and information technology, ontology has been researched and developed in application for knowledge representation. COKB model (Computational Object Knowledge Base) is an ontology was researched and applied in designing knowledge base systems, such as domain of knowledge about analytic geometry, linear algebra. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. In this paper, the extension model of ontology COKB has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking about finding solution of problem. Besides that, the architect of Intelligent Problem Solving system has been researched and applied. Using this architect and extension COKB model is applied to construct the system for automatic solving problems on knowledge about plane geometry.

Building a model of an intelligent multi-agent system based on distributed knowledge bases for solving problems automatically

In this paper, we propose a model of an Intelligent Multi-Agent System based on three distributed knowledge bases for solving problems automatically. Besides, we present architectures of agents in the system. We also illustrate an application of this model in three fields: plane geometry, 2D analytic geometry, and algebra. In our application, we use JADE platform, Maple, MathML, XML, …Finally, we show a method to test effects of the system developed from the model of MAS proposed.

Knowledge representation and algorithms for automatic solving integral problems

Integral of single variable functions is an important issue in calculus. This problem is widely applied in many fields such as physics, economics, etc. Systems for automatic solving integral problems are necessary tools in education. They support students and teachers in learning and teaching mathematics. Current computer algebra systems such as Maple, Mathematica, etc can solve integral problems. However, they output the result only or are limited to give the complete solution. This paper presents a model for representing knowledge about single variable functions and proposes some algorithms for solving integral problem automatically. These algorithms mimic the human way of thinking and produce the solution that explains the calculus process.

An approach for translating mathematics problems in natural language to specification language COKB of intelligent education software

Nowadays the research on intelligent systems for Problem solving in education has had lots of practical applications. A system based on ECOKB model and a specification language can process and produce gradual guide ways for full problem solving explanation. However, these systems limit users because they require the data input and the result output both not in natural language but specification language, which few users knows how to use this language input to the systems. Therefore, to improve ability of interacting by natural language, this paper proposes a new approach for translating mathematics problems in natural language to specification language as well as bringing out the model of natural language translating method associated with knowledge base domain for effective translation. Besides, this paper shows the ability of this approach applied in different knowledge domains.

Reasoning Method on Knowledge about Functions and Operators

In artificial intelligence, there are many methods for knowledge representation. One of the effective models is the Computational Object Knowledge Base model (COKB model), which can be used to represent the total knowledge and to design the knowledge base component of practical intelligent systems. Besides, reasoning methods also play an important role in knowledge base systems. In fact, a popular form of knowledge domain is knowledge about function and operations. These knowledge domains have many practical applications, especially in educational applications, such as Solid Geometry, Analytic Geometry. However, the current methods cannot reason on knowledge about Function and Operators. In this paper, we will present a reasoning method to solve problems on COKB model. These problems are related to knowledge about Functions and Operators. Also, this method has been applied to design some intelligent systems in education. Using this reasoning method, systems can solve problems in some educational knowledge domains automatically with their solutions are step-by-step.

Cooperating and Sharing Knowledge in an Intelligent Multi-Agent System Based on Distributed Knowledge Bases for Solving Problems Automatically

In this paper, we present cooperating and sharing knowledge between agents in an Intelligent Multi-Agent System for solving problems automatically. This system is built on three distributed knowledge bases. We also illustrate developing the system based on JADE with three fields of Mathematics: plane geometry, 2D analytic geometry, and algebra. Finally, we show the effects of the Intelligent Multi-Agent System.

A functional knowledge model and application

In artificial intelligence, knowledge models play an important role in designing the knowledge base systems and the expert systems. The quality of the intelligent systems depends heavily on the knowledge base built on the models. This paper presents a model of knowledge called functional knowledge model (FKM). This model is used to represent knowledge domains about functions and computing relations between them in different real applications. Besides, this paper also proposes a technique for solving an important problem in functional knowledge domains - simplification of functional expressions. Functional knowledge model is applied to construct an automatic system for simplifying trigonometric expressions in high school. This system can reason automatically from knowledge and provides a step by step solution that similar to the way of human thinking.

Deductive method with Sample Problems on Computational Object Knowledge Base and construct to intelligent educational softwares

In computer science and information technology, ontology has been researched and developed in application for knowledge representation. Ontology COKB-ONT (Computational Object Knowledge Base) is an ontology was researched and applied in designing knowledge base systems, such as domain of knowledge about analytic geometry, linear algebra. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. In this paper, the extension model of ontology COKB-ONT has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking about finding solution of problem. This extension model is applied to construct a program for solving plane geometry problems in middle school.