EXPERT SYSTEM SHELLS
WHAT IS EXPERT SYSTEM SHELLS ?
Definition :
An Expert system shell is a software development environment. It provides a framework that is used for the development of Expert System. It contains the basic components of expert systems. A shell is associated with a prescribed method for building applications by configuring and instantiating these components. In a simple way we can say that it is a ready-made Expert System without knowledge base.
Architecture :
The basic architecture of the expert system shell and its relationship to Knowledge base is shown in the figure.
Merits :
1. There is no need to build shell again and again for new expert system. Hence, the time required in building user interface and inference engine is not needed.
2. Development of an expert system becomes faster, cheaper and more efficient.
3. It doesn't require more experience programmer because there is no need to develop the system from scratch.
Demerits :
1. If the base is weak then developed product may not be reliable. It means if the shell is not matching the system requirement then the developed system will not represent expertise of a domain expert.
2. Some expert systems require different look and fill, security level and user guide. This is not possible in a single expert system shell. It needs customization depending on expert system requirement.
SHELL COMPONENTS :
1. The Knowledge Acquisition
2. The Explanation Subsystem
3. The User Interface
4. The Knowledge Base
5. Reasoning Engine
Here Knowledge Acquisition, Explanation Subsystem, User Interface are called generic components of a shell. And Knowledge, Base Reasoning Engine are called core components.
DESCRITION OF SHELL COMPONENTS :
1. User Interface :
A means of communication with the user. The user interface is generally not a part of the expert system technology. It was not given much attention in the past. However, the user interface can make a critical difference in the pe-eived utility of an Expert system.
2. The Explanation Subsystem :
A subsystem that explains the system’s actions. The explanation can range from how the final or intermediate solutions were arrived at justifying the need for additional data.
3. Reasoning Engine :
Inference mechanisms for manipulating the symbolic information and knowledge in the knowledge base form a line of reasoning in solving a problem. The inference mechanism can range from simple modus ponens backward chaining of IF-THEN rules to Case-Based reasoning.
4. The Knowledge Acquisition :
A subsystem to help experts in build knowledge bases. However, collecting knowledge, needed to solve problems and build the knowledge base, is the biggest bottleneck in building expert systems.
5. The Knowledge Base :
A store of factual and heuristic knowledge. Expert system tool provides one or more knowledge representation schemes for expressing knowledge about the application domain. Some tools use both Frames (objects) and IF-THEN rules. In PROLOG the knowledge is represented as logical statements.
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