HYBRID REASONING MODEL FOR STRENGTHENING THE PROBLEM SOLVING CAPABILITY OF EXPERT SYSTEMS
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 10
Abstract
In this paper, we briefly outlined popular case-based reasoning combinations. More specifically, we focus on combinations of case-based reasoning with rule based reasoning, and model based reasoning. Further we examined the strengths and weaknesses of various reasoning models, case-based reasoning, rule-based reasoning and model-based reasoning, and discuss how they can be combined to form a more robust and better-performing hybrid. In a decision support system to address the variety of tasks a user performs, a single type of knowledge and reasoning method is often not sufficient. It is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. In this study CBR was mixed with other RBR and MBR approaches to promote synergies and benefits beyond those achievable using CBR or other individual reasoning approaches alone. Each approach has advantages and disadvantages, which are proved to be complementary in a large degree. So, it is well-justified to combine these to produce effective hybrid approaches, surpassing the disadvantages of each component method. “KNAPS-CR” model integrates problem solving with learning from experience within an extensive model of different knowledge types. “KNAPS-CR” has a reasoning strategy which first attempts case-based reasoning, then rule-based reasoning, and, finally, model-based reasoning. It learns from each problem solving session by updating its collection of cases, irrespective of which reasoning method that succeeded in solving the problem.
Authors and Affiliations
Kapil Khandelwal, Durga Sharma
Keywords
Related Articles
- EP ID EP157101
- DOI 10.14569/IJACSA.2013.041014
- Views 65
- Downloads 0
Teaching Programming to Students in other Fields
It is a fact that programming is difficult to learn. On the other hand, programming skills are essential for each program in the field of computing and must be covered in the curriculum, regardless of the profile. Our ex...
Blind Image Quality Evaluation of Stitched Image using Novel Hybrid Warping Technique
Image stitching is collection of sequential images captured at fixed camera center having considerable amount of overlap and produces aesthetically pleasing seamless panoramic view. But, practically it is very difficult...
Applications of Multi-criteria Decision Making in Software Engineering
Every complex problem now days require multicriteria decision making to get to the desired solution. Numerous Multi-criteria decision making (MCDM) approaches have evolved over recent time to accommodate various applicat...
An Approach for Analyzing ISO / IEC 25010 Product Quality Requirements based on Fuzzy Logic and Likert Scale for Decision Support Systems
Decision Support Systems (DSS) are collaborative software systems that are built to support controlling of an organization in decision making process when faced with non-routine problems in a specific application domain....
A Comparative Study of Stereovision Algorithms
Stereo vision has been and continues to be one of the most researched domains of computer vision, having many applications, among them, allowing the depth extraction of a scene. This paper provides a comparative study of...