MIT OpenCourseWare

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.)

課程重點

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

課程描述

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.

師資

講師:
Prof. Leslie Kaelbling

教材提供:
Prof. Tomás Lozano-Pérez

上課時數

教師授課:
每週2節
每節1.5小時

程度

研究所

回應

告訴我們您對本課程或「開放式課程網頁」的建議。

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原文聲明