CS 561: Foundations of Artificial Intelligence

Fall 2010

Course Information and Syllabus
(tentative schedule - subject to change)
Meeting Time MW 5:00pm - 6:20pm
Meeting LocationZHS-159
CommunicationUSC's Blackboard service, email and class web-page
Textbook[AIMA] Artificial Intelligence: A Modern Approach (3rd Edition), by Russel and Norvig, Prentice Hall, 2009
Instructor Sofus A. Macskassy
Office: SAL 216 / ISI 946
Email: macskass@usc.edu
Office hours: By appointment
Teaching Assistants
TAHarris Chiu
OfficePHE 328
Emailchichiu at usc dot edu
Office HourseWed, 2:45pm-4:45pm
TAPenny Pan
OfficePHE 328
Emailbeipan at usc dot edu
Office HourseFri, 10am-noon

Course Overview

Artificial Intelligence (AI) seeks to understand the mechanisms underlying thought and intelligent behavior, and their embodiment in machines. This course approaches AI by using Intelligent Agents as an integrating perspective on the key topics in intelligent behavior.


Planned Schedule (tentative)
TENTATIVE
Date Description Readings Slides Work
8/23 Overview AIMA Ch. 1 Lecture-01-Intro.pdf  
8/25 Intelligent Agents AIMA Ch. 2 Lecture-02-Intelligent_Agents.pdf
(updated midterm date on slide 3 to Oct 18.)
 
8/30 Problem Solving and search AIMA Ch. 3 Lecture-03-04-Uninformed_Search.pdf  
9/1 Problem Solving and search AIMA Ch. 3   HW-1 passed out: hw1.pdf
Updated image in Q3: 9/3/10 @ 4:40pm
clarification for those using 2nd edition books.
9/6 No class - Labor day
9/8 Heuristic Search AIMA Ch. 3 Lecture-05-06-Heuristic_Search.pdf Project 1 passed out: Project1-v2.pdf
(UPDATED 9/20/10 @ 9:40am)
example input files
9/13 Beyond Search
AIMA Ch. 4    
9/15 Adversarial Game Search AIMA Ch. 5 Lecture-07-08-Adversarial_Search-v2.pdf
(UPDATED 9/20/10 @ 9:40am)
HW-1 due
HW-2 passed out: hw2.pdf
9/20 Adversarial Game Search AIMA Ch. 5   Updated project 1 description (see above)
9/22 Constraint Satisfaction Problems AIMA Ch. 6 Lecture-09-Constraint_Satisfaction.pdf Project1_Supporting_Slides.pdf (UPLOADED 9/23/10 @ 8:45pm))
9/27 Logical Agents AIMA Ch. 7 Lecture-10-11-Logical_Agents.pdf  
9/29 Logical Agents AIMA Ch. 7   HW-2 due
10/4 First-order Logic AIMA Ch. 8 Lecture-12-13-First-order_Logic.pdf  
10/6 First-order Logic AIMA Ch. 8    
10/11 Inference in First-order Logic AIMA Ch. 9 Lecture-14-15-Inference_in_FOL.pdf Project 1 due
10/13 Inference in First-order Logic AIMA Ch. 9    
10/18 Midterm (Example midterms available from AIMA site. These are similar to the types of questions I will ask.)
10/20 CLASS CANCELLED
10/25 Planning AIMA Ch. 10 Lecture-16-Planning.pdf HW-3 passed out: hw3.pdf
Project 2 passed out: Project2.pdf, project2_puzzle.zip
(puzzles added 10/30/10 @ 10:20pm)
10/27 Knowledge Representation AIMA Ch. 12 Lecture-17-Knowledge_Representation.pdf  
11/1 Uncertainty AIMA Ch. 13 Lecture-18-Uncertainty.pdf  
11/3 Uncertainty
Probablistic Reasoning
AIMA Ch. 13 & 14 Lecture-19-Probabilistic_Reasoning.pdf
(Updated 11/1/10 @ 10:20pm)
HW-3 due
HW-4 passed out: hw4.pdf, hw4_puzzles.zip
(puzzles added 11/9/10 @ 10:10pm)
11/8 Probabilistic Reasoning and Inference AIMA Ch. 14 Lecture-20-Probabilistic_Inference.pdf  
11/10 Probabilistic Inference AIMA Ch. 14    
11/15 Probabilistic Reasoning over Time AIMA Ch. 15 Lecture-21-Probabilistic_Reasoning_over_Time.pdf  
11/17 Probabilistic Reasoning over Time AIMA Ch. 15   HW-4 due
11/22 Rational Decision-making
Learning from Observations
AIMA Ch. 16 & 18 Lecture-22-Rational_Decisions.pdf
Lecture-23-Learning.pdf
 
11/24 Learning from Observations
Statistical Learning
AIMA Ch. 18 & 20 Lecture-24-25-Statistical_Learning.pdf Project 2 due
11/29 Statistical Learning AIMA Ch. 20    
12/1 Communication and Language AIMA Ch. 22 Lecture-26-Communication_and_Language.pdf
Lecture-27-Review.pdf
 
12/8 FINAL EXAM (4:30pm-6:30pm in normal classroom)

Grading Policy:

Grades will be based on:

HANDING IN HOMEWORK + PROJECTS: All homeworks and projects need to be handed in using the turnitin service from the class blackboard page.

The midterms and final will be open book and notes, but must along with the programming projects reflect just the work of the individual student, with no outside help (except for questions asked of the instructor and TA).
No make up exams will be given.

Projects and homeworks handed in one day late will result in a 25% reduction in the total score, two days late will yield a 50% reduction, and no credit will be give for three or more days late.

NOTE ON REGRADING: Once you have gotten your graded work back (homework, project or midterm) you have one week to ask for a review of the grade if you think there was an error in the grade. After that, no regrading will be done. There will be no exceptions.

NOTE ON MATERIAL COVERED ON MIDTERM AND FINAL: The midterm and final will cover all the material which has been discussed in class up to that point. Readings in the book sometimes cover material not discussed in class. If a topic in the book has not been discussed in class or in the lecture notes, then it will not be on the midterm. Sometimes I will use a different terminology in class than what is given in the book. Unless stated otherwise in class, lecture notes and what has been discussed in class will take precedence over the book.


Prerequisites:

Ability to program in C++ or Java in a Unix/Linux environment. Knowledge of data structures. There will be programming projects and your programs will be run and evaluated on the CS servers.


Statement for Students with Disabilities:

Any student requesting academic accommodations based on a disability is required to register with Disability Services and Programs (DSP) each semester. A letter of verification for approved accommodations can be obtained from DSP. Please be sure the letter is delivered to me (or to the TA) as early in the semester as possible. DSP is located in STU 301 and is open 8:30 a.m.5:00 p.m., Monday through Friday. The phone number for DSP is (213) 740-0776.


Statement on Academic Integrity:

USC seeks to maintain an optimal learning environment. General principles of academic honesty include the concept of respect for the intellectual property of others, the expectation that individual work will be submitted unless otherwise allowed by an instructor, and the obligations both to protect one's own academic work from misuse by others as well as to avoid using another's work as one's own. All students are expected to understand and abide by these principles. Scampus, the Student Guidebook, contains the Student Conduct Code in Section 11.00, while the recommended sanctions are located in Appendix A: http://www.usc.edu/dept/publications/SCAMPUS/gov/. Students will be referred to the Office of Student Judicial Affairs and Community Standards for further review, should there be any suspicion of academic dishonesty. The Review process can be found at: http://www.usc.edu/student-affairs/SJACS/.