Question 1) Write briefly:
(a) What do you mean by Possibility Theory.
(b) Define Conditional Probability with a appropriate example.
(c) Explain meta rules and their use in detail.
(d) Explain vagueness with an example.
(e) Distinguish between semantic nets and frames for representing knowledge.
(f) Write a detailed note on Knowledge Engineering Environment.
(g) Distinguish between learning by induction and learning by deduction with an appropriate example.
(h) What is the risk of Associative Networks?
(i) Give suitable example of the use of metaknowledge in expert system inference.
(j) What are difficulties in domain exploration?
Question 2) Describe in detail the architecture of an Expert System.
Question 3) Describe how does the behaviour of an interpreter can be controlled.
Question 4) What is the requirement for storing general data from case specific data in memory?
Question 5) What are the different categories of tasks performed by expert systems? Give suitable examples.
Question 6) Give an example of a Fuzzy Expert System.
Question 7) How is procedural knowledge different from declarative knowledge?
Question 8) Describe how uncertainty is handled in expert system MYCIN.
Question 9) Write down the characteristics of a real time expert system along with an example of a real time expert system.