ECE 448 - Introduction to Artificial Intelligence

Semesters Offered

TitleRubricSectionCRNTypeTimesDaysLocationInstructor
Artificial IntelligenceCS440ONL63671ONL -    Svetlana Lazebnik
Artificial IntelligenceCS440Q336047LCD1530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceCS440Q436053LCD1530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceECE448ONL63709ONL -    Svetlana Lazebnik
Artificial IntelligenceECE448Q336055LCD1530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceECE448Q436059LCD1530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik

Official Description

Course Information: Same as CS 440. See CS 440.

Prerequisites

Credit in CS 225 or ECE 391

Subject Area

Computer Engineering

Course Directors

Department of Computer Science

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

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

  • Introduction
  • AI languages and formalisms
  • Problem solving
  • Knowledge representation
  • Deductive inference
  • Inductive inference and machine learning
  • Natural language understanding
  • Computer vision
  • Robotics
  • Societal impacts
  • Exams

Detailed Description and Outline

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:

  • Introduction
  • AI languages and formalisms
  • Problem solving
  • Knowledge representation
  • Deductive inference
  • Inductive inference and machine learning
  • Natural language understanding
  • Computer vision
  • Robotics
  • Societal impacts
  • Exams

Same as: CS 440

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.

Topical Prerequisities

  • Stored-program concepts
  • data structures
  • high-level programming languages
  • interpretation vs. Compilation
  • editing
  • debugging and break packages

Texts

  • P. Winston, Artificial Intelligence, 2nd ed., Addison-Wesley, 1992.
  • P. Winston and B. K. Horn, LISP, 3rd ed., Addison-Wesley.
  • G. Steele, Jr., Common LISP, Digital, 1994.

ABET Category

Engineering Science: 2 credits or 67%
Engineering Design: 1 credit or 33%

Last updated

2/13/2013