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: Monday 1:30-3:00pm
 

TA: Zitao Liu
5324 Sennott Square, x4-8455
e-mail: ztliu_at_cs_dot_pitt_dot_edu
office hours: Tuesday 4:00-6:00pm, Wednesday 4:00-6:00pm
 


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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. 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 29, 2012 Administrivia and course overview. RN - chapters 1, 2 . 
    August 31, 2012 Problem solving by searching. RN - chapter 3.1-3.3. . 
    September 4, 2012 Search methods. RN - chapters 3.3.-3.4. . 
    September 6, 2012 Uninformed search methods RN - chapters 3.3.-3.4. Homework 1 ( Programs )
    September 11, 2012 Uninformed and informed search methods RN - chapters 3.3.-3.4.
    September 13, 2012 Informed search methods. Constraint satisfaction. RN - chapter 3.5, 6.1. Homework 2 ( Programs )
    September 18, 2012 Constrained satisfaction search. Finding optimal configrations. RN - chapters 6.1.-6.5.,4.1.
    September 20, 2012 Methods for finding optimal configurations. RN - chapters: 4.1. Homework 3 ( Programs )
    September 25, 2012 Finding optimal configrations. Adversarial search. RN - chapters 4.2., 5
    September 27, 2012 Knowledge representation. Propositional logic. RN - chapters: 7.1.-7.4. Homework 4 ( Programs )
    October 2, 2012 Inference in propositional logic. RN - chapters: 7.1.-7.4.
    October 4, 2012 Inference in propositional logic. Efficient inferences with rules. RN - chapters: 7.1.-7.4. Homework 5 ( Programs )
    October 11, 2012 First-order logic. RN - chapters: 8 Homework 6
    October 16, 2012 Inference in First-order logic. RN - chapters: 9
    October 18, 2012 Knowledge based systems RN - chapters: 9,12.5. Homework 7
    October 23, 2012 Planning RN - chapters: 10 .
    October 25, 2012 Midterm exam .
    October 30, 2012 Partial order planning
    Modeling uncertainty     		RN - chapters: 10, 13.1. .
    November 1, 2012 Modeling uncertainty using probabilities RN - chapters: 13 Homework 8
    November 6, 2012 Bayesian Belief networks RN - chapters: 14.1-14.3. .
    November 8, 2012 Inference in Bayesian belief networks RN - chapters: 14.4-14.5 Homework 9
    November 13, 2012 Decision making in the presence of uncertainty lecture notes .
    November 15, 2012 Decision making in the presence of uncertainty: utility theory.
    Introduction to machine learning.    		 lecture notes, RN - chapters: 16, 18.1-3. Homework 10
    November 20, 2012 Machine learning. Density estimation. lecture notes + RN: Chapter 2-.1-20.2. .
    November 27, 2012 Linear regression lecture notes + + RN: Chapter 18.6. .
    November 29, 2012 Binary classification lecture notes + RN: Chapter 18.6. Homework 11 ( Programs for the assignment)
    December 4, 2012 Binary classification II lecture notes + + RN: Chapter 18.6. .
    December 6, 2012 No class .
    December 14, 2012 Final exam .


    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