Date: Wed, 20 Nov 1996 22:24:26 GMT Server: NCSA/1.5 Content-type: text/html Last-modified: Mon, 18 Nov 1996 19:18:37 GMT Content-length: 5267 CS182

DIVISION OF ENGINEERING AND APPLIED SCIENCES
HARVARD UNIVERSITY

CS182. Intelligent Machines:
Reasoning, Actions, and Plans


Fall '96: Mondays and Wednesdays, 1-2:30 PM
Aiken Computation Laboratory, Room 101

Instructor:  Prof. Barbara J. Grosz

Teaching Fellows:   Luke Hunsberger and Wheeler Ruml

Prerequisites:  Computer Science 51; Computer Science 121 (may be taken concurrently).

CS182 is an introduction to Artificial Intelligence (AI) intended for undergraduates and graduate students with little or no previous exposure to AI. There are many ways to approach the study of AI; CS182 will emphasize the basic techniques and mechanisms that have been developed for the construction of intelligent systems with a focus on reasoning and actions. Major topics to be covered include search, representation formalisms, strategies for reasoning using them, and planning. Applications to language, vision, and robotics will also be studied.

If you have any questions about the course or its prerequisites, please feel free to contact one of the Teaching Fellows. More information about the course can be found in the Course Description and Syllabus.


The links in this section refer to pages in PostScript format.

Course Materials

Course Description
Syllabus
Mid-Semester Questionnaire

Assignments

Assignment 0: Back to Lisp
Assignment 1: Problem Encoding and Search
Assignment 2: Game Trees & Alpha-Beta Pruning
Assignment 3: Knowledge Representation and Theorem Proving
Assignment 4: Inheritance Networks
Assignment 5: London Explorer (Map of the London Underground)

Course Notes

09/16 Lecture 1. Introduction and Overview
09/18 Lecture 2. Basic Search #1
09/25 Lecture 3. Basic Search #2
09/27 Lecture 4. Basic Search #3
09/30 Lecture 5. Basic Search #4-Games
10/02 Lecture 6. Agent Architectures
10/07 Lecture 7. Knowledge Representation
10/09 Lecture 8. Predicate Calculus
10/18 Lecture 9. Guest Lecture- Notes Not Available
10/21 Lecture 10. Logical Inference
10/23 Lecture 11. Automated Inference
10/28 Lecture 12. Resolution Strategies, Prolog, and Network Systems
10/30 Lecture 13. Frame Systems and Classification Logics
11/04- 11/06 Lecture 14. and 15. Planning: The Basics
11/13 No lecture today- MIDTERM
11/18 Lecture 16. Partial-Order Planning: The Basics

A Sampling of AI on the WWW

Course Tools

Some Interesting Sites

General Information


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