CS 436-3
Artificial Intelligence I
Catalog Description
Search and heuristics, problem reduction. Predicate calculus, automated theorem proving. Knowledge representation. Applications of artificial intelligence. Parallel processing in artificial intelligence.
Prerequisite:
311 and 330 each with a grade of C or better.
Objectives
1. To introduce the basic concepts and techniques of artificial intelligence and provide some insights into active research areas and applications.
2. The course should emphasize the concepts of heuristic search and knowledge, and the relevance of AI research to cognitive science.
3. Lisp programming should be covered, and Prolog should be introduced.
Course Outline
| Lectures | ||
| 1. | Overview of knowledge representation
predicate, calculus, frames, semantic networks. |
8 |
| 2. | Search and heuristics
search spaces, breadth, first, depth-first, best-first search. |
6 |
| 3. | Theorem proving
forward-chaining, backward-chaining, resolution. |
9 |
| 4. | Structured knowledge representation
schemata, context layered data bases, truth maintenance, procedural attachment. |
6 |
| 5. | Applications
Natural language understanding, planning and problem solving. |
3 |
| 6. | Programming techniques
Lisp, Prolog. |
8 |
| Total | 40 | |