CS2710 Foundations of Artificial Intelligence
Time: MW 2:30pm-3:45pm, Langley Hall A 214 (LANGY A214)
Instructor: Milos
Hauskrecht
Computer Science Department
5329 Sennott Square
phone: x4-8845
e-mail: milos at pitt edu
office hours: Tuesday 1:00-2:30pm, Wednesday 9:30am-10:30am
TA: Patrick Luo
Computer Science Department
5406 Sennot Square
phone: 4-9182
e-mail: zhl78 at pitt edu
office hours: Monday 9:00am-10:30am, Tuesday 2:30pm-4:00pm
TA: Giacomo Nebbia
Intelligent Systems Program
5108 Sennot Square
phone:
e-mail: gin2 at pitt edu
office hours: Monday 10:30am - noon, Tuesday 10:30am-noon
Links
Course
description
Lectures
Grading
Homeworks
Announcements
(check often)
- There is no class on December 2, 2019.
- The final exam for the course will be on December 9, 2019 at 2:30-3:45pm in Langley Hall A 214 (LANGY A214). The exam is cumulative, closed book exam covering the whole semester.
- Homework assignment 11 is out and due on December 4, 2019. Programs/data for the assignment can be found here .
- Course syllabus
- Homework assignment submission rules. The programs and reports should be submitted electronically via courseweb prior to the lecture on the due date. The reports should be submitted in the pdf format. If you include any hand-made writings or drawings in the report please make sure they fit the page and are legible. The submissions (or their parts) that are not legible with a pdf reader will receive zero score. For programming part, please read the rules/instructions for submitting programming part of your assignments .
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 26, 2019 |
Administrivia. Course overview. |
RN - chapters 1, 2 |
. |
August 28, 2019 |
Problem solving by searching. |
RN - Chapter 3.1-3. |
. |
September 4, 2019 |
Uninformed search methods. |
RN - Chapter 3.3-4. |
Homework assignment 1 (Programs for Hw 1) |
September 9, 2019 |
Uninformed search methods II. |
RN - Chapter 3.4. |
. |
September 11, 2019 |
Informed search methods. |
RN - Chapter 3.4-5. |
Homework assignment 2 (Programs for Hw 2) |
September 16, 2019 |
Constraint satisfaction search. |
RN - Chapter 6.
|
. |
September 18, 2019 |
Optimal configuration search methods. |
RN - Chapter 4.1-2. |
Homework assignment 3 (Programs for Hw 3) |
September 23, 2019 |
Methods for finding optimal configurations II.
Adversarial search. |
RN - Chapter 4.1-2.,Chapter 5 |
. |
September 25, 2019 |
Knowledge representation. Propositional logic. |
RN - Chapter 7. |
Homework assignment 4 (Programs for Hw 4) |
September 30, 2019 |
Inference in propositional logic. |
RN - Chapter 7. |
. |
October 2, 2019 |
Inference in propositional logic II. |
RN - Chapter 7. |
Homework assignment 5 (Programs for Hw 5) |
October 7, 2019 |
First-order logic |
RN - Chapter 8 |
. |
October 9, 2019 |
Inference in the first order logic. |
RN - Chapter 8 |
Homework assignment 6 |
October 14, 2019 |
First-order logic: HNF. Production systems.
Planning I: situation calculus. |
RN - Chapters 8,9 and 10 (Intro and 10.4) |
. |
October 16, 2019 |
Planning II: STRIPS, POP planners |
RN - Chapter 10 |
Homework assignment 7 |
October 21, 2019 |
Planning III: abstractions, contingency planers
Models of uncertainty
|
RN - Chapters 10, 13 |
. |
October 23, 2019 |
Midterm
|
All lectures above |
. |
October 28, 2019 |
Bayesian belief networks
|
RN - Chapters 13,14 |
. |
October 30, 2019 |
Bayesian belief networks II
|
RN - Chapters 14 |
Homework assignment 8 |
November 4, 2019 |
Bayesian belief networks III
Decision making in the presence of uncertainty
|
RN - Chapters 14,16 |
. |
November 6, 2019 |
Decision making in the presence of uncertainty II
|
RN - Chapter 16 |
Homework assignment 9 |
November 11, 2019 |
Machine learning
|
RN - Chapter 18 |
. |
November 13, 2019 |
Machine learning II: density estimation
|
RN - Chapter 18 |
Homework assignment 10 |
November 18, 2019 |
Machine learning III: Linear regression
|
RN - Chapter 18 |
|
November 20, 2019 |
Machine learning IV: Classification
|
RN - Chapter 18 |
Homework assignment 11 (Programs/Data for Hw 11) |
December 2, 2019 |
No class
|
RN - Chapter 18 |
. |
December 4, 2019 |
Machine learning V: Multilayer Neural Networks
|
RN - Chapter 18 |
. |
December 9, 2019 |
Final exam
|
RN - Chapter 18 |
. |
Grading
- Homework assignments 45 %
-
Midterm
25 %
-
Final
25 %
-
Lectures/activity 5 %
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.
Academic integrity. 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. Please make sure you understand and abide to the SCI academic integrity policy.
Programming assignments
will be in Python language. Python programs submitted by you should work with Python 3.6. 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 08/26/19