ECE 448 - Introduction to Artificial Intelligence

Semesters Offered

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Artificial IntelligenceCS440ONL63671ONL -    Svetlana Lazebnik
Artificial IntelligenceCS440Q336047LCD31530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceCS440Q436053LCD41530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceECE448ONL63709ONL -    Svetlana Lazebnik
Artificial IntelligenceECE448Q336055LCD31530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik
Artificial IntelligenceECE448Q436059LCD41530 - 1645 T R  1404 Siebel Center for Comp Sci Svetlana Lazebnik

Official Description

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

Subject Area

Computer Engineering

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 Prerequisites

  • 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