| Section | Type | Times | Days | Location | Instructor |
|---|---|---|---|---|---|
| Q3 | LCD | 1230 - 1345 | T R | 1404 Siebel Center for Comp Sci | Gerald Dejong |
| Q4 | LCD | 1230 - 1345 | T R | 1404 Siebel Center for Comp Sci | Gerald Dejong |
| Official Description | Same as CS 440. See CS 440. |
|---|---|
| Hours | 3 or 4 hours. |
| Course Prerequisites | Credit in ECE 390 or CS 225 |
| Course Directors |
Department of Computer Science
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| Description | Introductory description of the major subjects and directions of research in artificial intelligence; topics include AI languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. |
| Notes | Same as: CS 440 |
| Credit | 3 or 4 hours |
| Goals | This course is designed to give students an overview of major results and current research directions in artificial intelligence, along with an in-depth treatment of a member of representative systems, through programming exercises and class discussions. |
| Topics |
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| Lab Projects | Design and implementation of LISP programs for: (1) recursive algorithms; (2) a problem solving system; (3) means-ends analysis; (4) pattern matching; (5) interactive natural language processing; (6) syntactic parsing of a natural language; (7) interactive frame-based dialog; (8) inference on a semantic network database. |
| Course Prerequisites | ECE 390 or CS 225. |
| Topical Prerequisities |
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| Texts |
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| ABET Category | Engineering Science: 2 credits or 67% Engineering Design: 1 credit or 33% |