CS3310 Syllabus, Spring 2017

Course goals

Survey of the main techniques of artificial intelligence, especially knowledge representation, inference, control structures, uncertainty, heuristic search, and learning.� The emphasis is on methods for achieving intelligent behavior in computers, not necessarily modeling human behavior.� A variety of skills will be covered, including programming, simulation of programs on paper, knowledge of key terms, and ability to discuss in writing the application of artificial-intelligence methods to real-world problems.� The ultimate goal is to enable students to write programs exhibiting intelligent behavior.

Prerequisites

The official prerequisite for this course is CS2011 and one college-level course in programming.� It is also helpful to have some knowledge of logic (predicate calculus), further programming experience, and some knowledge of data structures.

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Grading

Homework 1, 70 points

Test 1, 100 points

Homework 2, 70 points

Test 2, 100 points

Homework 3, 70 points

Test 3, 100 points

Tests are open-book but no electronic devices are allowed.� Expected class averages on tests will be around 70%.� Questions will emphasize thinking more than memorization.� Lately the grades have been approximately 20% A, 40% A-, 25% B+, and 15% less than B+.� Note the "quizzes" will be treated as pass-fail towards your course grade, although Sakai does compute a score, it will not be counted, just the fact you completed a quiz.

Many test questions will relate to homework problems.� Some homework will be team problems, and some will be individual.� Individual problems must be done by each student on their own without consulting anyone besides the instructor, and that includes looking online.� Team problems must be done by each team without consulting other teams or consulting anyone else.� Some of the homework will require programming in the language Gnu Prolog which you will download following instructions on the first assignment; and some of it will involve programming in Python or Java (your choice).� When you submit programs, always submit a listing of your code and a script of the run of your code.� The late penalty is 10% after the due time on the due date, but no homework is accepted after solutions are displayed.� Homework should be submitted as hard copy, one copy per team when teams are used, unless it specifically says an electronic copy suffices.� Material for each problem on a homework assignment should be included together (no appendices) in a single document.

Textbook and materials

We will email you copies of the PowerPoint slides used in the lectures (the slides on the Sakai site are outdated).� Required textbook is Luger, Artificial Intelligence, latest edition, Addison-Wesley.� Earlier editions are acceptable but the section numbers to read may be different.� The electronic version is cheaper but you cannot consult it during tests as you can the print version, though you could print key pages in advance.� The CS3310 Sakai site has the quizzes and lecture videos from 2006.� Useful additional references are Rowe, Artificial Intelligence through Prolog (on the Web at faculty.nps.edu/ncrowe/book/book.html), Russell and Norvig, Artificial Intelligence, Prentice-Hall; and Winston, Artificial Intelligence, Addison-Wesley.� The Web site faculty.nps.edu/ncrowe/coursematerials also contains programs discussed in class and Web-page demos.

Instructor

Prof. Neil Rowe, GE-328, ncrowe@nps.edu, (831) 656-2462, faculty.nps.edu/ncrowe.� Office hours are to be announced or by arrangement.

CS3310 schedule (readings are in Luger, 6th edition)

By 4/6: Overview of AI: Read chapter 1, install Prolog as per instructions on homework #1

By 4/10: Do Quiz 1

By 4/13: Knowledge representation: Read sections 7.0, 7.1, 7.2, and 7.3

By 4/13: Do Quiz 2 and Quiz 3

By 4/18: Do Quiz 4; finish tutor problems on facts and queries

By 4/21: Inference rules: Read sections 2.1, 2.2, 2.3, 2.4, 14.2.1, and 14.3

By 4/24: Do Quiz 5; Finish tutor problems on rules

Homework #1 due Tuesday, 4/25 in class

Test #1: Thursday, 4/27

By 5/4: Do Quiz 6

By 5/11: Control structures: Read sections 8.1, 8.2, 7.4

By 5/12: Do Quiz 9 (note we are skipping Quizzes 7 and 8)

By 5/16: Reasoning with uncertainty: Read sections 9.0, 9.2.1, 9.3, 11.1, 11.2.1, 11.2.2

By 5/18: Do Quiz 10

Homework #2 due Thursday 5/18 in class

Test #2: Monday 5/22 covering mostly material since Test #1

By 5/29: Heuristic search: Read sections 3.0, 3.1, 3.2, 4.0, 4.2

By 6/2: Do Quiz 11

By 6/5: Planning: Read sections 4.3, 4.4, 8.4, 14.1

By 6/6: Do Quiz 12

By 6/8: Machine learning: Read sections 10.1, 10.3, 10.6

By 6/8: Do Quiz 13

Homework #3 due Monday 6/12 at 1700

Test #3: Wednesday 6/14 at time and place to be scheduled, covering mostly material since Test #2

Protocols

� The rules for collaboration with other students differ from problem to problem.� Some of the homework is group assignments.� But unless a problem is designated as a group assignment, you may not discuss it with anyone besides the instructor.

� �This is a true graduate-level course. Thus you will be expected to solve minor details on your own without consulting the instructor. However, if you are stuck or spending excessive time on a question, email or talk to the instructor.� You should not feel frustrated by a problem.

� It is expected that tests will have averages around 70%.� The Sakai quizzes are difficult but they are graded pass/fail.� Other homework will vary in difficulty though usually they should have higher averages than the quizzes.� So perfect scores by students are not possible and students should not feel bad that they are not perfect.� This is education, not training: We are asking you somewhat difficult questions to prepare you better for the real world.