M. Afshar Alam

Work place: Department of Computer Science, Hamdard University, New Delhi, India

E-mail: mailtoafshar@rediffmail.com


Research Interests: Computational Science and Engineering, Computational Engineering, Software Engineering, Computer Architecture and Organization, Logic Calculi, Logic Circuit Theory, Engineering


M. Afshar Alam is a Professor in Computer Science, he was Head of Computer Science Department, Faculty of Management and Information Technology, at the Hamdard University, New Delhi, India. In 1997-2000, he founded the Department of Computer Science, Hamdard University. He was also founder of Computer Centre at Hamdard University. He received his Master degree in Computer Science from the Aligarh Muslim University, Aligarh and Ph.D. from Jamia Millia Islamia University, New Delhi. His research interests include Fuzzy logic, Software engineering and Bioinformatics. He is the author of a book on Software re-engineering and over 50 publications in International/ National journals, conference and chapter in an edited book. He is a member of expert committee AICTE, DST, UGC and Ministry of Human Resource Development (MHRD), New Delhi, India.

Author Articles
A Multi-intelligent Agent System for Automatic Construction of Rule-based Expert System

By Mohammed Abbas Kadhim M. Afshar Alam Harleen Kaur

DOI: https://doi.org/10.5815/ijisa.2016.09.08, Pub. Date: 8 Sep. 2016

The main general purpose of this research is the automatic construction of rule-based expert system in diagnosis domain based on an expert system tool and a multi-intelligent agent system. The first goal is used an expert system tool (shell) which is called Diagnosis Domain Tool for Rule-based Expert System (DDTRES) [1]. The second goal is used a multi-intelligent agent architecture for knowledge extraction to elicit knowledge from its resources (domain experts, text documents, databases) for automatic construction of a knowledge base. That means, instead of using traditional methods for knowledge base construction, we used automatic way for that job. In order to achieve second objective, the following agents have been used: The Expert Mining Intelligent Agent (EMIA), The Text Mining Intelligent Agent (TMIA) [2], and The Multi-Intelligent Agent for Knowledge Discovery in Database (MIAKDD) [3]. We are aim to produce an effective final knowledge base by cooperation between EMIA, TMIA, and MIAKDD approaches and integrated with the diagnosis domain tool (DDTRES) to produce a complete rule-based expert system in diagnosis domain. We applied the captured rule-based expert system on heart diseases diagnosis, we found system performance is between a good and a very good range.

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