15-381 Home Page: Intro to Artificial Intelligence
- Nov 15, 1994: Change in Lectures
Dr. Mauldin and Mr. Redish will exchange lectures, and several lectures
- Nov 3, 1994: Correction to Assignment II
A correction was made to the on-line handout (see the response to
Norwood on cmu.andrew.academic.cs.15-381 dated Nov. 3 for
- Oct. 28, 1994:
Assignment Two On-Line
The handout for homework two is now available in HTML form.
- Oct. 27, 1994: Change in Lectures
Dr. Mauldin and Mr. Ng will exchange lectures. The November 10th
lecture will now be given by Mr. Ng on Planning (chapter 13),
and the December 1st lecture will be given by Dr. Mauldin on
Parallel and Distributed AI (chapter 16).
- Oct. 18, 1994: Sample Solutions HW1
All sample solutions for homework 1 are now available.
- Sept 19, 1994: Instructor Switch
Dr. Mauldin will now give the lecture on Oct-6, and Dr.
Nyberg will give the lecture on Oct-18.
- Sept 8, 1994: Task I
The first homework task on problem spaces and search is now available.
- Sept 7, 1994: the Lectures
The Lectures section contains brief notes about what has been
covered in class so far.
- Sept 1, 1994: New syllabus
to a overzealous scheduling error by Dr. Mauldin, two lectures were
omitted from the syllabus handed out on the first day of class.
- Class meets in Hammerschlag B131
- 10:30 am -- 11:50 am, Tuesday and Thursday
- See-Kiong Ng
Wean 4114, x83075, firstname.lastname@example.org
Office hours: Thursday 5-6pm
- David Redish
Wean 8301, x83074, email@example.com
Office hours: Tuesday 1-2pm
- Eric Krotkov
Wean 1321, x83058, firstname.lastname@example.org
Office hours: by appointment
The text for this course is Artificial Intelligence, 2nd Edition, by
Elaine Rich and Kevin Knight, McGraw-Hill, Inc., 1991. Copies are
available for purchase in the CMU Bookstore. (The same text was used last
semester, so you may be able to buy a used copy from another student.) A
copy has been placed on reserve in the E&S Library.
The general schedule for the class is as follows (see the
syllabus for details):
The course will be team-taught by Dr. Mauldin and Dr. Nyberg. Each of the
teaching assistants will teach two of the Advanced Topics classes, and
there will be two sessions devoted to Robotics taught by Eric Krotkov.
- September --- Problem Spaces, Search, Game Playing, and Predicate Logic
- October --- Knowledge Representation and Reasoning
- November/December --- Advanced Topics
Your efforts on the midterm, final, and assignments will be graded.
The grades provide you with feedback on your work, as well as provide
the Registrar with a letter grade. The grading breakdown will be
- Task I: Search
- Task II: Knowledge Representation
- Task III: Robotics Lab
- Midterm (Problem Spaces, Search, Game Playing, and Predicate Logic)
- Final (half on Knowledge Representation and Reasoning and half
on Advanced Topics)
Your assignments will involve the design and implementation of
computer programs in the Common Lisp programming language. We assume
that you are already familiar with Lisp. If you are unfamiliar with
Lisp, you should either (1) obtain Dave Touretzky's book ``LISP: A
Gentle Introduction to Symbolic Computation'' and complete it in the
next week, or (2) drop the course.
Official announcements will be made in class, when possible.
Between classes, announcements will be posted on the Andrew bboard
Day Chapter Topic Instructor Assignments
30-aug 1 What is AI? All
01-sep 2 Problem Spaces Mauldin
06-sep 2 Problem Spaces Mauldin
08-sep 3 Heuristic Search Mauldin Task 1 Out
13-sep 3 Heuristic Search Mauldin
15-sep 3 Genetic Search Mauldin
20-sep 12 Game Playing Mauldin
22-sep 4/5 Predicate Logic Nyberg Task 1 Due
27-sep 5 Using Predicate Logic Nyberg
29-sep 5 Using Predicate Logic Nyberg
04-oct ******** MIDTERM EXAM ********
06-oct 6 Knowledge Representation w/ Rules Mauldin
11-oct 6 Knowledge Representation w/ Rules Nyberg
13-oct 7 Symbolic Reasoning w/Uncertainty Mauldin
18-oct 8 Statistical Reasoning Nyberg
20-oct Guest Lecture TBA
25-oct 9 Weak Slot-and-Filler Structures Nyberg Task 2 Out
27-oct 10 Strong Slot-and-Filler Structures Nyberg
01-nov 11 Knowledge Representation Summary Nyberg
03-nov 15 Natural Language Processing Nyberg
08-nov 14 Understanding Ng Task 2 Due
10-nov 13 Planning Ng
15-nov 17 Learning TBA
17-dec 16 Parallel and Distributed AI Mauldin
22-nov 18 Connectionist Models Redish
24-nov ****** Thanksgiving day ******
29-nov 21 Perception and Action Krotkov Task 3 TBA
01-dec 21 Robotics Lab Krotkov
06-dec 19 Common Sense Redish
08-dec 20 Expert Systems Mauldin
As the course progresses, some of the lecture slides and other notes
will be archived here.
- 30-Aug: What is AI? (Mauldin and Nyberg)
- 01-Sep: Problem Spaces (Mauldin)
- Water Jug problem as example of problem space
- Breadth-first search
- Depth-first search
- Unified model of search
- Generate and test
- Dr. Mauldin recommended that each student write a Lisp program
to use DFS and BFS to solve the water jug problem, and hinted that this
would help greatly with task I.
- 6-Sep: Problem Spaces (Mauldin)
- Introduced hill-climbing and best-first search.
- Discussed potential problems with difficult spaces for
- Search-graph as alternative to search-trees.
- Noted that any AI problem solver must be able to solve the
- 8-Sep: Heuristic Search (Mauldin)
- First home work task handed out
- Hill climbing
- Simulated annealing
- Best-first search with underestimate heuristic
- Agenda-driven search
- Introduced AND-OR graphs
- Discussed search in Rog-O-Matic
- 13-Sep: Heuristic Search (Mauldin)
- Problem reduction and Futility search
- Back-propagation of costs during search
- Described A* search algorithm (attributes of this search will be
on the mid-term)
- Constraint satisfaction and Cryptarithmetic
- Robot planning and Means-Ends analysis
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Last updated 07-Sep-94 by email@example.com