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6.825 Techniques in Artificial Intelligence (SMA 5504), Fall 2002

Agent and environment dichotomy. A robot taking actions that affect the state of the environment then receiving percepts with new information on the environment.
An example of the agent and environment dichotomy. This figure illustrates a robot taking actions that affect the state of the environment then receiving percepts with new information on the environment. (Image courtesy of Beryl Simon.)

Highlights of this Course

The calendar for this course provides the topics for the course, along with direct links to lecture notes, homework assignments, and exams.

Course Description

6.825 is a graduate-level introduction to artificial intelligence. Topics covered include: representation and inference in first-order logic, modern deterministic and decision-theoretic planning techniques, basic supervised learning methods, and Bayesian network inference and learning.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5504 (Techniques in Artificial Intelligence).

Technical Requirements

Any text editor can be used to view the .cnf files found on this course site. Please refer to the course materials for any specific instructions or recommendations. Java® plug-in software is required to run the Java® files found on this course site. File decompression software, such as Winzip® or StuffIt® , is required to open the .gz files found on this course site.


Java® is a trademark or registered trademark of Sun Microsystems, Inc. in the United States and other countries.
StuffIt® is a trademark of Aladdin Systems, Inc.
WinZip® is a registered trademark of WinZip Computing, Inc.

 

Staff

Instructor:
Prof. Leslie Kaelbling

Contributor:
Prof. Tomás Lozano-Pérez

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / session

Level

Graduate

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