Designing an Intelligent Problems Solving System Based on Knowledge about Sample Problems

Nhon, V.; Nguyen, Hien D.; Mai, Thanh T.

doi:10.1007/978-3-642-36546-1_48

Cited by 12 publications

(10 citation statements)

References 2 publications

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“…In the future, we will research and develop more methods and techniques of knowledge integration that are applicable in more complex real-world knowledge domains. Problems using heuristics and sample problems [21] for reasoning on the integrated structure will also be studied. Additionally, with the IPS in education, after finding the solution of a problem, the system will omit the redundant steps, which are unnatural for humans, and wrap the solution steps into tutoring steps.…”

Section: Discussionmentioning

confidence: 99%

“…The general algorithm for solving these problems was presented in [20]. It uses forward chaining reasoning for solving problems and applies heuristics rules as sample problems [21], arranging the priority to use inference rules. Each object a ends the reasoning process by solving problems on itself as Algorithm 1.…”

Section: General Problem With the Model Of The Kernelmentioning

confidence: 99%

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A Method of Ontology Integration for Designing Intelligent Problem Solvers

2019

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Nowadays, designing knowledge-based systems which involve knowledge from different domains requires deep research of methods and techniques for knowledge integration, and ontology integration has become the foundation for many recent knowledge integration methods. To meet the requirements of real-world applications, methods of ontology integration need to be studied and developed. In this paper, an ontology model used as the knowledge kernel is presented, consisting of concepts, relationships between concepts, and inference rules. Additionally, this kernel is also added to other knowledge, such as knowledge of operators and functions, to form an integrated knowledge-based system. The mechanism of this integration method works upon the integration of the knowledge components in the ontology structure. Besides this, problems and the reasoning method to solve them on the integrated knowledge domain are also studied. Many related problems in the integrated knowledge domain and the reasoning method for solving them are also studied. Such an integrated model can represent the real-world knowledge domain about operators and functions with high accuracy and effectiveness. The ontology model can also be applied to build knowledge bases for intelligent problem solvers (IPS) in many mathematical courses in college, such as linear algebra and graph theory. These IPSs have great potential in helping students perform better in those college courses.

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Section: Discussionmentioning

confidence: 99%

Section: General Problem With the Model Of The Kernelmentioning

confidence: 99%

A Method of Ontology Integration for Designing Intelligent Problem Solvers

2019

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“…If so, then the solution for the practical problem can be obtained effectively by using the results of the related problem. The related problems are called sample problems (Do et al, 2013).…”

Section: Heuristic Rule About Using Sample Problemsmentioning

confidence: 99%

Solving problems on a knowledge model of operators and application

Nguyen¹,

Nhon²,

Pham³

et al. 2018

IJDET

Self Cite

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Knowledge of operators is useful to build the intelligent problem solver for knowledge domains about computing. In this paper, we present a mathematical approach for building a knowledge model of operators, called Ops-model. The foundation of this model includes: concepts, operators, and inference rules. Each concept of this model is a class of objects with the behaviours for solving problems on themselves. General problems on this model are also studied, such as: reducing an expression, prove an equality of expressions. The algorithms for solving these problems are also designed. Ops-model has been applied to specify a part of knowledge domain about vector algebra in high school. It is used to construct a program for solving some problems on this knowledge domain. The solutions of this program are step-by-step, readable and suitable with the learners' level. It is useful for supporting students to learn this subject.

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“…The tutoring chatbot is an Intelligent Problem Solver (IPS). There are many methods for building IPS systems, such as ontology, frames, scripts, logic [5,6,7], and deductive methods: forward chaining, backward chaining, reasoning with heuristic rules [8,9]. However, those methods have not yet been applied to tutor the method for solving problems in practice, such as: the system supports to learn how to solve exercises in mathematics, and another system instructs the work in public administration.…”

Section: Introductionmentioning

confidence: 99%

“…Hint questions are tips for instructing the solving method [11]. Sample problems are problems related to the current problem [9]. Using sample problems, the chatbot can find the solution quickly.…”

Section: Introductionmentioning

confidence: 99%

Design an Intelligent System to automatically Tutor the Method for Solving Problems

Nguyen

Tran

Huan

et al. 2020

IJIE

Self Cite

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Nowadays, intelligent systems have been applied in many real-word domains. The Intelligent chatbot is an intelligent system, it can interact with the human to tutor how to work some activities. In this work, we design an architecture to build an intelligent chatbot, which can tutor to solve problems, and construct scripts for automatically tutoring. The knowledge base of the intelligent tutoring chatbot is designed by using the requirements of an Intelligent Problem Solver. It is the combination between the knowledge model of relations and operators, and the structures of hint questions and sample problems, which are practical cases. Based on the knowledge base and tutoring scripts, a tutoring engine is designed. The tutoring chatbot plays as an instructor for solving real-world problems. It simulates the working of the instructor to tutor the user for solving problems. By utilizing the knowledge base and reasoning, the architecture of the intelligent chatbot are emerging to apply in the real-world. It is used to build an intelligent chatbot to support the learning of high-school mathematics and a consultant system in public administration. The experimental results show the effectiveness of the proposed method in comparison with the existing systems.

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Designing an Intelligent Problems Solving System Based on Knowledge about Sample Problems

Cited by 12 publications

References 2 publications

A Method of Ontology Integration for Designing Intelligent Problem Solvers

A Method of Ontology Integration for Designing Intelligent Problem Solvers

Solving problems on a knowledge model of operators and application

Design an Intelligent System to automatically Tutor the Method for Solving Problems

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