CS 1571  Introduction to Artificial Intelligence


Time:  TH 4:00-5:15pm,  5129 Sennott Square



Instructor:  Milos Hauskrecht
5329 Sennott Square, x4-8845
e-mail: milos_at_cs_dot_pitt_dot_edu
office hours: Wednesday 10:30am - noon
 

TA: Peter Djalaliev
6503 Sennott Square, x4-7253
e-mail: peterdj_at_cs_dot_pitt_dot_edu
office hours: M: 1:00-3:00pm, W:2:00-4:00pm
 


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Course description
Lectures
Grading
Homeworks
 

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    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:  CS 1501, CS 1502
     

    Textbook:

    Stuart Russell, Peter Norvig. Artificial Intelligence.  A modern approach. 2ed. Prentice Hall, 2002.
    Note: The second edition of the book was published at the end of 2002. There are significant changes as compared to the first (1995) edition of the book. Please make sure you get the new (green color cover) edition.
     


    Lectures  
     
    Lectures  Topic(s)  Readings  Assignments
    September 1 Administrivia and course overview. RN - chapters 1, 2 . 
    September 3 Solving problems by searching. RN - Sections 3.1.-3.3. . 
    September 8 Solving problems by searching II. RN - Sections 3.3.-3.4. . 
    September 10 Uninformed search I. RN - Sections 3.3.-3.4. Homework assignment 1 . ( Programs for HW-1. )
    September 15 Uninformed search II. RN - Sections 3.3.-3.4.
    September 17 Informed search methods RN - Section 4 Homework assignment 2 . ( Programs for HW-2. )
    September 17 Informed search methods: IDA* Constraint satisfaction search. RN - Section 4,5
    September 29 Constraint satisfaction search. RN - Section 5
    October 1 Finding optimal configurations. RN - Section 5 Homework assignment 3 . ( Programs for HW-3. )
    October 6 Parametric optimization. Adversarial search. RN - Section 6
    October 8 Knowledge Representation. Propositional Logic. RN - Section 7 Homework assignment 4 . ( Programs for HW-4. )
    October 15 Knowledge Representation. Propositional Logic. RN - Section 7 Homework assignment 5 .
    October 20 Propositional Logic. RN - Section 7
    October 22 First-order logic. RN - Section 7-8
    October 27 First-order logic. Inference RN - Section 9
    October 29 Midterm exam Midterm review RN - Sections 1- 8 Homework assignment 6
    November 3, 2009 First-order logic. Inference RN - Section 9
    November 5, 2009 Inferences in the Horn-normal form. Production systems. Situation calculus. RN - Sections 9. and 10. Homework assignment 7
    November 10, 2009 Planning. STRIPS. RN - Chapter 11.
    November 12, 2009 Planning. Partial order planners.
    Uncertainty.     		RN - Chapter 11. Homework assignment 8
    November 17, 2009 Reasoning in the presence of uncertainty. RN - Chapters 13-14.
    November 19, 2009 Bayesian belief networks. RN - Chapter 14. Homework assignment 9
    November 24, 2009 Inference in Bayesian belief networks. RN - Chapter 14.
    December 1, 2009 Decision-making in the presence of uncertainty. RN - Chapter 16.
    December 3, 2009 Decision-making in the presence of uncertainty II. RN - Chapter 16,17. Homework assignment 10
    December 8, 2009 Introduction to Machine Learning. RN - Sections 18.1-2. and 20.1-2.
    December 10, 2009 Course review

    You may want to peruse lecture notes from last year. They can be accessed here.


    Grading

    Homeworks

    There will be weekly homework assignments. The homeworks will include a mix of paper and pencil 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 08/27/07