CS 536-3
Artificial Intelligence II
Catalog Description
Theorem proving, the Resolution Principle, strategies, and achievements. Program verification. Natural language processing. Other selected topics.
Prerequisite:
CS 436.
Objectives
1. To describe in depth current work in a wide variety of application areas and theoretical approaches.
2. To present advanced Lisp and Prolog programming techniques.
Course Outline
| Since the set of topics covered is likely to vary as a result both of new developments in the field of A.I. and of the interests of the instuctor, this outline is intended to be only suggestive. | ||
| 1. | Languages and architectures for problem solving
blackboards, production systems, connection networks, constraint propagation |
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| 2. | Default reasoning, uncertainty
nonmonotonic logic, belief revision, certainty factors |
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| 3. | Natural langage understanding
parsers, anaphora, plan recognition, schema application, focus, speech acts |
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| 4. | Expert systems
MYCIN, XCON, shells, knowledge engineering |
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| 5. | Advanced knowledge representation
intensional objects, naive physics, analogical representations |
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| 6. | Programming techniques
agendas, streams, controling backtracking in Prolog |
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| 7. | AI research at SIU | |
| 8. | Learning
version spaces, concept learning, Automated Mathmetition |
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| 9. | Planning
STRIPS, NOAH, metaplanning |
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