CS 561: Foundations of Artificial Intelligence

Spring 2011

Course Information and Syllabus
(tentative schedule - subject to change)
Meeting Time MW 5:00pm - 6:20pm
Meeting LocationSection 30079D: DEN / OFF CAMPUS
Section 30080D: OHE122
CommunicationUSC's DEN Blackboard Site, 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
TAHossein Tajalli (Farshad)
OfficeSAL 245
Emailtajalli at usc dot edu
Office HourseMon, 11am-1pm

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
1/10 Overview AIMA Ch. 1 Lecture-01-Intro.pdf  
1/12 Intelligent Agents AIMA Ch. 2 Lecture-02-Intelligent_Agents.pdf
(updated 1/12/11 @ 9:25pm)
 
1/17 NO CLASS - Martin Luther King's Birthday
1/19 Problem Solving and search AIMA Ch. 3 Lecture-03-04-Uninformed_Search.pdf  
1/24 Problem Solving and search AIMA Ch. 3   hw1.pdf
1/26 Heuristic Search AIMA Ch. 4 Lecture-05-06-Heuristic_Search.pdf  
1/31 Beyond Search
AIMA Ch. 4   project1-rev3.pdf (Feb 17 @ 5:45pm))
utilities.jar
data files: racetracks.zip
2/2 Adversarial Game Search AIMA Ch. 5 UPDATED 2/2/11 @ 11pm:
Lecture-07-08-Adversarial_Search-rev2.pdf
 
2/3 Pre-taping the Feb 9 class: Location and time: 2pm, OHE 100C
Constraint Satisfaction Problems
AIMA Ch. 6 Lecture-09-Constraint_Satisfaction.pdf  
2/7 Adversarial Game Search AIMA Ch. 5   HW-1 Due
hw2.pdf
2/9 NO CLASS: This class is pre-taped at 2pm on Feb 3, OHE 100C.
Constraint Satisfaction Problems
AIMA Ch. 6    
2/14 Guest Lecturer
Logical Agents
AIMA Ch. 7 Lecture-10-11-Logical_Agents.pdf  
2/16 Guest Lecturer
Logical Agents
AIMA Ch. 7   HW-2 Due
hw3.pdf
2/21 NO CLASS - President's Day
2/23 First-order Logic AIMA Ch. 8 Lecture-12-13-First-order_Logic.pdf  
2/28 First-order Logic AIMA Ch. 8   Project-1 Due (deadline now 3/7!)
3/2 Inference in First-order Logic AIMA Ch. 9 Lecture-14-15-Inference_in_FOL.pdf HW-3 Due
3/7 Inference in First-order Logic AIMA Ch. 9   Project-1 Due (NEW DEADLINE)
3/9 Midterm (LOCATION: THH 301) (Example midterms available from AIMA site. These are similar to the types of questions I will ask.)
3/14 No class - Spring Recess
3/16 No class - Spring Recess
3/21 Planning AIMA Ch. 10 Lecture-16-Planning.pdf project2-rev8.pdf (Updated 4/7/11 @ 4:10pm)
project2_racetracks.zip
3/23 Uncertainty AIMA Ch. 13 Lecture-17-Uncertainty.pdf hw4.pdf
3/28 Uncertainty
Probablistic Reasoning
AIMA Ch. 13 & 14 Lecture-18-Probabilistic_Reasoning.pdf  
3/30 Probabilistic Reasoning and Inference AIMA Ch. 14 Lecture-19-20-Probabilistic_Inference.pdf  
4/4 Probabilistic Inference AIMA Ch. 14   HW-4 Due
hw5.pdf (Updated 4/7/11 @ 10:05pm)
4/6 Probabilistic Reasoning over Time AIMA Ch. 15 Lecture-21-22-Probabilistic_Reasoning_over_Time.pdf  
4/7 Pre-taping the April 11 class: Location and time: 12:30pm, OHE 120
Probabilistic Reasoning over Time
AIMA Ch. 15    
4/11 NO CLASS: This class is pre-taped at 12:30pm on April 7, OHE 120.
Probabilistic Reasoning over Time
AIMA Ch. 15    
4/13 Probabilistic Reasoning over Time AIMA Ch. 15   HW-5 due
4/18 Rational Decision-making
Learning from Observations
AIMA Ch. 16 & 18 Lecture-23-Rational_Decisions.pdf
Lecture-23-24-Learning.pdf
 
4/20 Learning from Observations
Statistical Learning
AIMA Ch. 18 & 20 Lecture-24-25-Statistical_Learning.pdf Project 2 due (deadline now 4/25!)
4/25 Statistical Learning AIMA Ch. 20 Project-2 Due (NEW DEADLINE)
4/27 Communication and Language AIMA Ch. 22 Lecture-26-Communication_and_Language.pdf
Lecture-27-Review.pdf
 
5/4 FINAL EXAM (4:30pm-6:30pm - LOCATION: THH 301)

Grading Policy:

Grades will be based on:

HANDING IN HOMEWORK + PROJECTS: All homeworks and projects need to be handed in before 5pm on due date using DEN's turnitin service from the class blackboard page. Extensions must be requested at least 48 hours prior to due date. No exceptions.

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/.