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Unit 9: Weak Slot and Filler Structures

3. Pick a problem area and represent the knowledge in frame based system. Notes
4. Devise algorithms that enable reasoning with frames. Discuss how:
(a) Inference through inheritance can be achieved.
(b) Matching can be achieved.

5. What are the benefits of a frame based knowledge representation?
6. What problems do you predict that a frame based knowledge representation having?
Give examples of knowledge hard to symbolize in a frame. How could some difficulties
be conquer?
7. What programming languages would be matched to put into practice a semantic network
and frames?
8. Weak Slot and Filler Structures permits ease of deliberation as it embraces features of
object oriented programming. Comment.

9. Illustrate the inference methods used in semantic nets.
10. Make distinction between sets and instances with examples.

Answers: Self Assessment

1. Slot 2. Filler
3. Content 4. Intersection Search
5. Partitioned 6. Weak Slot and Filler

7. Semantic Nets 8. Frame
9. Information 10. Structured
11. Class 12. Metaclass

13. Relation 14. Inheritance
15. Range

9.6 Further Readings

Books Antonelli, D. 1983. The application of artificial intelligence to a maintenance and diagnostic
information system (MDIS). Proceedings of the Joint Services Workshop on Artificial
Intelligence in Maintenance. Boulder, CO.
Boose, J.H. 1984. Personal construct theory and the transfer of human expertise.
Proceedings of the National Conference on Artificial Intelligence (AAAI-84),
p. 27-33, Austin, Texas.
Boose, J.H. 1985. A knowledge acquisition program for expert systems based on personal
construct psychology. International Journal of Man-Machine Studies, 23, 495-525.
Boose, J.H. 1986a. Expertise Transfer for Expert System Design, New York; Elsevier.
Boose, J.H. 1986b. Rapid acquisition and combination of knowledge from multiple experts
in the same domain. Future Computing Systems Journal, 1, 191-216.

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