CS 1571  Introduction to Artificial Intelligence


Time:  TH 11:00am-12:15pm,  5129 Sennott Square



Instructor:  Milos Hauskrecht
5329 Sennott Square, x4-8845
e-mail: milos_at_cs_dot_pitt_dot_edu
office hours: Tuesday 2:00-4:00pm
 

TA: Dave Krebs
5324 Sennott Square, x4-8455
e-mail: djk37_at_cs_dot_pitt_dot_edu
office hours: Monday 2:30pm - 4:00pm, Tuesday 4:30pm - 6:00pm
 

TA: George Boulous
6150 Sennott Square
e-mail: gwf5_at_cs_dot_pitt_dot_edu
office hours: MW 12:45-2:15 pm
 



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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. 3rd ed. Prentice Hall, 2009.
    Note: The third edition of the book was published at the end of 2009. There were multiple changes as compared to the first (1995) and second (2002) editions of the book. Please make sure you get the new edition.
     



    Lectures  
     
    Lectures  Topic(s)  Readings  Assignments
    August 31 Administrivia and course overview. RN - chapters 1, 2
    September 2 Problem solving by searching. RN - chapter 3.1-3.3.
    September 7 Problem solving by searching. Search methods. RN - chapters 3.3.-3.4.
    September 9 Uninformed Search Mehods I. RN - chapters 3.3.-3.4. Homework assignment 1
    September 14 Uninformed Search Mehods II. RN - chapters 3.3.-3.4.
    September 16 Informed Search Methods: IDA*. Constraint Satisfaction Search. RN - chapter 3.5, 6.1. Homework assignment 2 ( Programs for assignment 2 )
    September 21 Constraint satisfaction. Optimal configuration search. RN - chapters: 6.1.-6.5.,4.1.
    September 23 Optimal configuration search. RN - chapters: 4.1. Homework assignment 3 ( Programs for assignment 3 )
    September 28 Parametric optimization. Adversarial search. RN - chapters: 4.2. and 5.
    September 23 Knowledge representation. Propositional logic. RN - chapters: 7.1.-7.4. Homework assignment 4 ( Programs for assignment 4 )
    October 5 Propositional logic. RN - chapters: 7.1-7.5.
    October 7 Propositional logic. Horn normal form. RN - chapters: 7.1.-7.6 Homework assignment 5 ( Programs for assignment 5 )
    October 14 First-order logic. RN - chapter: 8 Homework assignment 6
    October 19 Inference in First order logic. RN - chapter: 9
    October 21 Inference in First order logic. Knowledge based systems RN - chapters: 9, 12
    October 26 Planning RN - chapters: 10
    October 28 Midterm exam RN - chapters: 1-9 Homework assignment 7
    November 2 Planning: STRIPS RN - chapters: 10
    November 4 Planning: POP planners
    Uncertainty
    RN - chapters: 10, 13.1. Homework assignment 8
    November 9 Uncertainty RN - chapters: 13
    November 11 Bayesian belief networks RN - chapters: 14.1-3. Homework assignment 9
    November 16 Inference in BBNs. RN - chapters: 13
    November 18 Decision making in the presence of uncertainty RN - chapters: 14.1-3. Homework assignment 10
    November 23 Decision making in the presence of uncertainty
    Machine learning
    RN - chapters: 14,18.1-4.
    November 30 Machine learning RN - chapters: 18.1-4, 20.1-2.
    December 2 Machine learning: linear regression RN - chapters: 20.1-2., 18.6. Homework assignment 11
    December 7 Machine learning: logistic regression RN - chapters: 18.6.
    December 9 Machine learning: support vector machines RN - chapters: 18.9.



    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 08/30/10