Expert system

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Again classroom presentation March 2012.

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  • As the rule base is in everyday language (the engine is untouchable), expert system can be written much faster than a conventional program, by users or experts, bypassing professional developers and avoiding the need to explain the subject.
  • Expert system

    1. 1. Expert SystemPresented by:Mukul, Pankaj & Divya
    2. 2. Expert System: Meaning An expert system is a computer system that competes with the decision-making ability of a human expert. Designed to solve complex problems by reasoning about knowledge, like an expert, and not by following the procedure of a developer as is the case in conventional programming.
    3. 3. Meaning Continued It is a computer program that represents and reasons with knowledge of some specialist subject with a view to solving problems or giving advice It is divided into two parts. Fixed, independent of the expert system: the inference engine. Variable: the knowledge base. Conversational: A dialog interface to communicate with users.
    4. 4. Software architecture The rule base or knowledge base In expert system technology, the knowledge base is expressed with natural language rules IF ... THEN ... For examples :"IF it is living THEN it is mortal" "IF his age = known THEN his year of birth = date of today - his age in years.
    5. 5. The inference engine The inference engine is a computer program designed to produce a reasoning on rules. In order to produce a reasoning, it is based on logic. With logic, the engine is able to generate new information from the knowledge contained in the rule base and data to be processed.
    6. 6. Advantages Evolving an expert system is to add, modify or delete rules. Since the rules are written in plain language, it is easy to identify those to be removed or modified. Quick availability and opportunity to program itself. The reliability of an expert system is the same as the reliability of a database, i.e. good, higher than that of a classical program.
    7. 7. Disadvantages Knowledge collection and interpretation into rules, the knowledge engineering. Expert knowledge is not well understood: there is a lack of rules, rules are contradictory, and some are poorly written and unusable. Expert systems most often use an engine incapable of reasoning. Therefore, oftentimes the expert system works poorly and the project is abandoned
    8. 8. On a lighter side
    9. 9. Application field Highly interactive or conversational applications, IVR, voice server. Fault diagnosis, medical diagnosis Decision support in complex systems, process control, interactive user guide. Educational and tutorial software. Logic simulation of machines or systems Knowledge management. Constantly changing software.
    10. 10. Thank You IF= Nerds are bad, THEN = Politicians are… error !

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