CS2710  Foundations of Artificial Intelligence


Time:  TH 1:00pm-2:15pm,  5313 Sennott Square



Instructor:  Milos Hauskrecht
Computer Science Department
5329 Sennott Square
phone: x4-8845
e-mail: milos at cs pitt edu
office hours: Wednesday 10:30am-noon, Thursday 2:30-4:00pm


TA:  Yanbing Xue
Computer Science Department
6804 Sennot Square
phone: 4-8455
e-mail: yax14 at pitt edu
office hours: Monday 11:00am-2:00pm



Links

Course description
Lectures
Grading
Homeworks
 

Announcements (check often)



Course description

This course will provide an introduction to the fundamental concepts and techniques underlying the construction of intelligent computer systems. Topics covered in the course include: problem solving and search, logic and knowledge representation, planning, reasoning and decision-making in the presence of uncertainty, and machine learning.

Prerequisites:  undergraduate AI course (CS 1571 or equivalent) or the permission of the instructor.
 

Textbook:

Stuart Russell, Peter Norvig. Artificial Intelligence.  A modern approach. 3rd ed. Prentice Hall, 2009.
Note: The third edition of the book was published at the end of 2009. Multiple changes to the first (1995) and second (2002) editions of the book occured. Please make sure you get the new edition.
 



Lectures  
 
Lectures  Topic(s)  Readings  Assignments
August 29, 2017 Administrivia. Course overview. RN - chapters 1, 2
August 31, 2017 Problem solving by searching. RN - Chapter 3.1-3.
September 5, 2017 Uninformed search methods. RN - Chapter 3.3-4. Homework assignment 1 (Programs for Hw 1)
September 7, 2017 Uninformed search methods II. RN - Chapter 3.4. .
September 12, 2017 Informed search methods. RN - Chapter 3.4-5. Homework assignment 2 (Programs for Hw 2)
September 14, 2017 Constraint satisfaction search. RN - Chapter 6. .
September 19, 2017 Finding optimal configurations. RN - Chapter 4.1. Homework assignment 3 (Programs for Hw 3)
September 21, 2017 Finding optimal configurations. RN - Chapter 4.1-2. .
September 26, 2017 Adversarial search. RN - Chapter 5. Homework assignment 4 (Programs for Hw 4)
September 28, 2017 Knowledge representation: Propositional logic RN - Chapter 7. .
October 3, 2017 Propositional logic II RN - Chapter 7.5. Homework assignment 5
October 5, 2017 Propositional logic III RN - Chapter 7 .
October 12, 2017 First order logic RN - Chapter 8 Homework assignment 6 (Programs for Hw 6)
October 17, 2017 First order logic: Inference RN - Chapter 9 Homework assignment 7
October 19, 2017 First order logic: Inference RN - Chapter 9
October 24, 2017 Knowledge based systems, Planning RN - Chapter 10. Introduction and 10.4.
October 26, 2017 Midterm
October 31, 2017 Planning RN - Chapter 10. Homework assignment 8
November 2, 2017 Modeling uncertainty RN - Chapter 13,14
November 7, 2017 Bayesian belief networks RN - Chapter 14 Homework assignment 9
November 9, 2017 Bayesian belief networks
Decision making in the presence of uncertainty
RN - Chapter 14, 16
November 14, 2017 Decision making in the presence of uncertainty II RN - Chapter 16 Homework assignment 10
November 16, 2017 Machine Learning RN - Chapter 18
November 21, 2017 Density estimation
Linear regression
RN - Chapter 20.1-2., 18.6.1-2 no homework
November 28, 2017 Linear regression (cont). Logistic regression RN - Chapter 18.6.1-4 Homework assignment 11 ( Data for Hw 11)
November 30, 2017 Multilayer neural networks RN - Chapter 18.7.
December 5, 2017 Guest lecture: Image analysis and Vision RN - Chapter 24.
December 7, 2017 no lecture
December 12, 2017 Final exam



Grading

Homeworks

There will be weekly homework assignments. The homeworks will include a mix of both theoretical problems, and programming assignments. The assignments are due at the beginning of the class on the day specified on the assignment. In general, no extensions will be granted.

Collaborations. Collaborations on homeworks are not permitted. Cheating and any other antiintellectual behavior will be dealt with severely. If you feel you may have violated the rules speak to us as soon as possible.

Programming assignments. Knowledge of C/C++ language is neccessary for the programming part. C/C++ programs submitted by you should compile with g++ compiler under unix. Please see the rules for submitting programming assignments.


Students With Disabilities:
If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services, 216 William Pitt Union, (412) 648-7890/(412) 383-7355 (TTY), as early as possible in the term. DRS will verify your disability and determine reasonable accomodations for this course.
 



Last updated by milos on 08/28/17