Bottleneck — key challenge?
Rule creation and problem representation
Expert systems — purpose?
Simulate human decision-making using rules and facts.
Inference types — mechanisms?
Forward, backward, mixed (graph traversal)
Core components of expert system?
Rules base, facts base, inference engine, user interface.
Expert system components?
Rules base, facts base, inference engine, UI
Main inference methods?
Forward chaining, backward chaining, mixed chaining.
Inference algorithms — similarity?
Graph traversal techniques.
Problem modeling — importance?
Key for effective reasoning, affects performance.
Uncertainty handling?
Probabilistic rules and facts.
Expert system applications?
Diagnosis, risk estimation, planning, knowledge transfer.
Testez vos connaissances avec un QCM de 9 questions sur Expert System Inference Techniques.
1. What is the primary function of system experts in knowledge-based systems?
2. What are the core components of an expert system as outlined in the revision sheet?
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