Artificial Intelligence
CS 441/541
Artificial Intelligence
Fall Quarter 2007
Time : Mondays and Wednesdays, 12:00-1:50pm
Location: Ondine (CH), Room 220.
Instructor:
Melanie Mitchell,
FAB 120-24, (503) 725-2412, mm-AT-cs.pdx.edu.
Office hours: Mondays and Wednesdays, 2:00-3:00pm, or by appointment.
TA:
Ralf Juengling,
Dean's Suite, 5th floor, Engineering Building, juenglin-AT-cs.pdx.edu.
Office hours: Mondays 10:00am-12:00 noon, or by appointment.
Course Website: :
http://www.cs.pdx.edu/~mm/ArtificialIntelligenceFall2007/index.html
Prerequisites: CS 202, 311, or equivalent.
Required reading: There will be no textbook. Students
should purchase the book
Vehicles by Valentino Braitenberg, which we will read over the
first few weeks. Other readings as well as class notes will be
available on the course web page.
Reading materials on reserve in the library:
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach
V. Braitenberg, Vehicles: Experiments in Synthetic Psychology
Major Topics: Components of intelligent agents, problem-solving and
game-playing as search, knowledge repesentation, logical reasoning,
learning and reasoning under uncertainty, natural-language processing,
vision, analogy-making, philosophy of AI.
Exams: There will be no exams.
Grading: To be announced.
Academic integrity: Students will be responsible for
following the PSU
Student Conduct Code, and in particular, the policy concerning
academic honesty.
Students with disabilities: If you are a student with a
disability in need of academic accommodations, you should register
with Disability Services for Students and notify the instructor
immediately to arrange for support services.
Neural Network slides
Syllabus (subject to change):
|
Date |
Topics |
Homework
|
Monday Sept. 24
|
Class overview
Intellligent programs 1
Projects overview
Class slides
|
Homework:
Reading for next class:
Alan Turing,
Computing
Machinery and Intelligence.
Answer reading questions.
Due: Wednesday September 26.
|
Wednesday Sept. 26
|
Intellligent programs 2
Problem-solving as search.
Class slides
|
Homework:
Read:
John Searle, Minds, Brains, and Programs.
Vehicles, pp. 1-19
Answer:
Reading questions.
Exercises on problem-solving as search.
Due: Monday October 1.
|
Monday Oct. 1
|
Heuristic search.
Reinforcement learning 1
Class slides (October 1-3)
|
Homework:
Read:
(1) Vehicles, pp. 20-32
(2) M. Gasser, Introduction to reinforcement learning.
Due: Wednesday October 3.
|
Wednesday Oct. 3
|
Vehicles
Reinforcement Learning 2
|
Homework:
Read:
Vehicles, pp. 33-54
Answer:
Reading questions and exercises
Due: Monday October 8.
|
Monday Oct. 8
|
The role of representation in AI
Genetic algorithms
Guest lecturers: Ralf Juengling and Martin Cenek
Ralf's slides (pdf)
Martin's slides (ppt)
|
Homework: : None
|
Wednesday Oct. 10
|
Adversarial search and games
Guest lecturer: Bart Massey
Bart Massey's slides (pdf)
|
Homework: : None
|
Monday Oct. 15
|
Knowledge representation
Class slides
Student presentations:
Steven Glazer: A world championship caliber checkers program
Will Newell: Temporal difference learning and TD-gammon
Eliseo Hernandez: Reinforcement learning in the multi-robot domain
|
Homework:
Read:
Vehicles, pp. 55-61
S. C. Shapiro, Knowedge representation,
Answer:
Reading questions and exercises
Due: Monday, Oct. 22.
Optional reading: N. Shadbolt and W. Hall, The semantic web revisited
|
Wednesday Oct. 17
|
Logic and planning
Class slides
Student presentations:
Hal Brodigan:
The uses of fuzzy logic in autonomous robot navigation
Aaron Altman:
Neural networks in clinical medicine (Tutorial)
Aaron Fellin:
Statistics and the war on spam
|
...
|
Monday Oct. 22
|
Natural language processing 1
Class slides
Final paper format
Student presentations:
Joseph Jess: Shrdlu
Clark Wachsmuth: Active vision for sociable robots
|
Homework: :
Read:
Vehicles, pp. 62-69.
Chapter 1 from Jurafsky and Martin, Speech and language
Processing: An introduction to natural language processing,
computational linguistics, and speech recognition.
Optional reading:
Chapter 4
("N-grams"), up to section 4.5.2, from the same book.
Chapter 23 (Question answering and summarization), from the same
book.
Answer: Reading questions and exercises.
|
Wednesday Oct. 24
|
Natural language processing 2
Vision 1
Class slides
|
Optional reading:
An analysis of the AskMSR question-answering system
Face recogntion using eigenfaces (article available if you're on a PSU nework)
|
Monday Oct. 29
|
Vision 2: Face recognition with neural networks
Class slides
Student presentations:
Chris Herz: Grace: An autonomous robot for the AAAI Robot Challenge
Thanh Dang: Content-Based Image Retrieval
Lanfranco Muzi: Phaeaco
James Murphy: Mental imagery for a conversational robot
|
Homework: :
Read:
For students who are relatively new to neural
networks:
Artificial Neural Networks: A Tutorial pp. 1-22 (up to, but not
including, "Boltzmann Learning" section), pp. 30-32 (Section 4) and
pp. 42-49 ("Applications" section).
For students who are familiar with neural networks: Same article, pp. 22-49 (starting with "Boltzmann Learning" section).
For all students:
Answer: Reading questions and exercises.
Here is the gzipped tarball with the code and data for the exercises.
Due: Monday, Nov. 5.
Optional Reading: Finish Vehicles.
|
Wednesday Oct. 31
|
Biologically inspired AI
Class slides
Student presentations:
Jennifer Meneghin: GAs applied to microarrays
Scott Fletcher: Lifemapper
Anthony Kautz: Co-Evolution in the Successful Learning of Backgammon Strategy
David Rosenbaum: Neural Network-Based Face Detection
|
...
|
Monday Nov. 5
|
Genetic algorithms
Class slides
Student presentations:
Cong Hoang: CMAssist: A RoboCup@Home Team
Tyson Mahuna: Mars rovers
Dan Coates: Genetic programming
|
Homework: :
Read:
Evolving cellular automata to perform computations: A review of recent work.
Computer immunology.
Exercises:
HW 7
Here is the
Guide to GA Code
Here is the gzipped tarball with the code.
Due: Monday, Nov. 19.
|
Wednesday Nov. 7
|
Computer immunology
Analogy
Class slides
Student presentations:
Ian Billington: Swarm intelligence
Scott Wespi Analogy as the core of cognition
Nish A. : Structure-Mapping Engine
|
...
|
Monday Nov. 12
|
No class (PSU holiday)
|
...
|
Wednesday Nov. 14
|
Reasoning under uncertainty 1
Class slides
Student presentations:
Alex Ross: Stanley
Zigmund Rosinski: DARPA Challenge vehicles
Steve Grover: Programming methodology for biologically-inspired self-assembling
systems
|
...
|
Monday Nov. 19
|
Reasoning under uncertainty 2
Class slides
Student presentations:
Michael Mooney: Lisa (a medical decision support system)
David Camarillo: Swarmbots
Rajesh V.: KARMA
|
Homework:
Reading:
S. Wooldridge, Bayesian Belief Networks
|
Wednesday Nov. 21
|
Reasoning under uncertainty 3.
Class slides
Student presentations:
Justin Bailey: Neuroevolution
Matthew Hedman: Privacy Intrusion Detection Using Dynamic Bayesian Networks
Vidyanath Vedantam: CLARION (Cognitive Architecture): Connectionist
Learning with Adaptive Rule Induction
|
HW 8,
due Wednesday, Nov. 28.
|
Monday Nov. 26
|
AI Future and Ethics 1
Ray Kurzweil slides
Other class slides
Project presentations:
Tank Wars
Vision
Massive
Twixt
|
...
|
Wednesday Nov. 28
|
AI Future and Ethics 2
AI review
Class slides
Project presentations:
Source code analysis
Spam filtering
Navigation
Checkers
|
...
|
Monday Dec. 3 and Wednesday Dec. 5
|
No class (finals week).
|
...
|
Thursday December 6
|
12:30pm - 2:20pm:
Project presentations:
Natural Language Processing
Analogy/Reasoning
Game player (Matthew Hedman)
Texas Hold 'em
Network Traffic Analysis
|
Final paper due Friday Dec. 7
|
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