Architecture of expert expert system?

Expert system architecture need to act like the process expert attempt to do for reasoning based on the given facts. Architecture comprise of interface, explanation system, inference engine and knowledge editor as a shell,which can be configured on different knowledge area without changing the whole structure of expert system, and the removable part constitute of domain-specific and general knowledge section. In general knowledge section refer to those knowledge representation(usually in the form of ruled-based) symbols which is needed for expert system to running.

Domain-specific refer to those facts that entered by user or is the conclusion of the last operation in inference part. Resemble it to individual experts, general knowledge section have a role of long-terms memory and domain specific have role of working memory which is manipulated or updated by inference engine. In fact inference engine use both of this storage for reasoning and making inference about the problem.

Generally inference engines use recognize-act chain in order to solve the problem. Process of problem solving in forward chaining method for inference start with typing of problem from GUI by user, the facts go into domain specific storage,in this part the first action on recognition-action cycle of inference engine take place. All of the facts in domain-specific storage being compared with rules in general knowledge storage.

This part is called matching, after that inference engine need choose the most appropriate one from conflict set(set of rules in matched in first step). For this purpose it may use conflict resolution strategy which is the job of interpreter. Interpreter is part of the inference engine that execute selected agenda based on the given criteria.

What will happen then is selection of rule based on namely three main category of strategy:1-in the case of two or more condition use the one that are more specific 2-if two or more rule have appropriate condition for selection use the one used in facts 3-if system match the same condition for two different role the latest rule need to be eliminated because iteration may take place. After selection of rule execution part start if executed result is the one desired problem is solved if not, result store in domain-specific section and cycle renewed. The process of inference engine is the same for back-ward and forward chaining what make difference is the load and reload of working memory and other things.(and this is the thing that you need to find out!).

Explanation system which is part of the shell(you can see more about shell by searching on wikianswer ;)). Explanation system provide description about why expert system decide on particular course of action and how it conclude to this result. Mechanism counterintutivelly simple.

Explanation system just exploit the knowledge pattern it followed during the work of inference engine. It track back use storage to find out what have been decided and how inference engine imply based on th rules.(just like it's human counter part) I don't know much about the detailed flow of work in explanation systems but I really love to. Knowledge editor as its name imply manipulate the general knowledge storage, adding , deleting and changing undertake by knowledge engineer but knowledge editor written by professional programmer.

Hope this would help but again check other places because there s lot more you need to know. Good luck have fun!

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