Expert Systems

Expert Systems

1. 1. Solve complex problems with the same (or greater) solvency as human experts 2. Perform heuristic reasoning. 3. Work with data containing errors. 4. Consider multiple hypotheses simultaneously. 5. Perform at the level of a human expert. 6. Respond in a reasonable amount of time. 7. Maintain reliability and should not crash. 8. Explain the steps of the reasoning process. It should justify how it arrived at a particular conclusion.

2. Components of Expert Systems : 1. Knowledge base 2. Inference engine 3. User interface 4. Explanation facility 5. Knowledge acquisition facility 6. External interface 7. Database

   • A knowledge base contains a collection of information in a given field. The knowledge base of an expert system stores both factual and heuristic knowledge. • Factual knowledge – based on facts • Heuristic knowledge – based on practice, evaluation, experiences, and the ability to guess