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problem 1) prepare briefly:

(a) What do you mean by Possibility Theory.

(b) Define Conditional Probability with a appropriate ex.

(c) describe meta rules and their use in detail.

(d) describe vagueness with an ex.

(e) Distinguish between semantic nets and frames for representing knowledge.

(f) prepare a detailed note on Knowledge Engineering Environment.

(g) Distinguish between learning by induction and learning by deduction with an appropriate ex.

(h) What is the risk of Associative Networks?

(i) Give suitable ex of the use of metaknowledge in expert system inference.

(j) What are difficulties in domain exploration?

problem 2) Describe in detail the architecture of an Expert System.

problem 3) Describe how does the behaviour of an interpreter can be controlled.

problem 4) What is the requirement for storing general data from case specific data in memory?

problem 5) What are the different categories of tasks performed by expert systems? Give suitable exs.

problem 6) Give an ex of a Fuzzy Expert System.

problem 7) How is procedural knowledge different from declarative knowledge?

problem 8) Describe how uncertainty is handled in expert system MYCIN.

problem 9) prepare down the characteristics of a real time expert system along with an ex of a real time expert system.

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