CS 1571  Introduction to Artificial Intelligence


Time:  TH 1:00pm-2:15pm,  5129 Sennott Square



Instructor:  Milos Hauskrecht
5329 Sennott Square, x4-8845
e-mail: milos_at_cs_dot_pitt_dot_edu
office hours: Tuesday: 9:30-11:00am, Friday: 1:30-2:30pm
 

TA: Charmgil Hong
5406 Sennott Square
e-mail: charmgil_at_cs_dot_pitt_dot_edu
office hours: Tuesday: 11:00am-12:30pm, Wednesday: 11:00am-12:30pm
 



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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:  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. 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 26, 2014 Administrivia. Course overview. RN - chapters 1, 2
August 28, 2014 Solving problems by searching. RN - chapters 3.1-3.
September 2, 2014 Solving problems by searching. RN - chapters 3.1-3.
September 4, 2014 Uninformed search methods. RN - chapters 3.3-4. Homework assignment 1 ( programs )
September 9, 2014 Uninformed search methods II. RN - chapters 3.3-4. .
September 11, 2014 Heuristic search methods. RN - chapters 3.3-5. Homework assignment 2 ( programs )
September 16, 2014 Heuristic search methods: IDA.
Constrain satisfaction search.
RN - chapters 3.5, and 6.1-5 .
September 18, 2014 Constrain satisfaction search.
Combinatorial optimization search.
RN - chapters 6.1-5 Homework assignment 3
September 23, 2014 Combinatorial optimization search methods. RN - chapters 4.1-2. .
September 25, 2014 Parametric optimization.
Adversarial search.
RN - chapters 4.2., and 5 Homework assignment 4 ( programs )
September 30, 2014 Knowledge representation. Propositional logic RN - chapters: 7.1.-7.4. .
October 2, 2014 Propositional logic: inference. RN - chapters: 7.1.-7.5. Homework assignment 5 ( programs )
October 7, 2014 Propositional logic: restricted forms. RN - chapters: 7.1.-7.7. .
October 9, 2014 First-order logic. RN - chapter: 8. Homework assignment 6 ( programs )
October 16, 2014 First-order logic: inference RN - chapter: 9. Homework assignment 7
October 21, 2014 First-order logic: inferences in HNF. Production systems RN - chapter: 9, 12.5.1 .
October 23, 2014 Planning: situation calculus, STRIPS planners RN - chapter: 9, 12.5.1 .
October 28, 2014 Midterm . .
October 30, 2014 Planning (cont). Uncertainty. RN - chapter: 10, 11.2., 13 Homework assignment 8
November 4, 2014 Modeling uncertainty using probabilities RN - chapter: 13 .
November 6, 2014 Bayesian Belief Networks RN - chapter: 14 Homework assignment 9
November 11, 2014 Bayesian Belief Networks: approximate inference
Decision making in the presence of uncertainty
RN - chapter: 14 .
November 13, 2014 Decision making in the presence of uncertainty II RN - chapter: 14 Homework assignment 10
November 18, 2014 Machine Learning RN - chapter: 18
November 20, 2014 Machine Learning: Density estimation, Linear regression RN - chapter: 18 Homework assignment 11 ( Programs and data)
November 26, 2014 Linear regression, Logistic regression RN - chapter: 18
December 2, 2014 Support vector machines RN - chapter: 18
December 4, 2014 Naive Bayes classifier, Decision trees. RN - chapter: 18
Course review.



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 08/25/14