CS 4100 Artificial Intelligence
Spring 2012
Course Description and Syllabus

Instructor: Prof. Carole Hafner hafner@ccs.neu.edu, Office: 446 West Village H, Tel. 617-373-5116
TA: Saber Shokat Fadaee, saber@ccs.neu.edu, Office: 266 West Village H
Course web site: http://www.ccs.neu.edu/course/cs4100sp12/

Class Meets: Tuesday 11:45 and Thursday 2:50, 110 West Village H
Prof. Hafner Office Hours:  Tuesday and Wednesday, 2-3 p.m.
Saber Office Hours: Thurs 1:30-2:30, Friday 11:30-12:30

This course introduces the fundamental concepts, models and techniques of the artificial intelligence field, along with examples of applications. Topics covered include: automated deduction and problem-solving; heuristic search and planning; bayesian inference and statistical learning methods; natural language processing.  Required coursework includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course.

Required Textbook:
    Artificial Intelligence: A Modern Approach, 3rd Edition by Stuart Russell and Peter Norvig. (Prentice Hall 2010).  BE SURE TO GET THE 3rd EDITION -- it is significantly different (and better) than the 2nd edition!!

Strongly recommended for students new to Python: Learning Python,  3rd edition by Mark Lutz (O'Reilly,  2007). 
Note: The latest edition (4th edition) describes Python 3.0, so please use the 3rd edition. 
Other (free) resources for learning python: The Python Tutorial (vers 2.6), and Dive into Python (somewhat out of date but still useful).

There will be 5-6 homework assignments, containing written and/or programming problems. 

We will use  Python (vers. 2.6 or 2.7), a  language, which is now the preferred language for AI programming.
Assignments will be available in the Assignments Directory
Sample Programs and other class resources will be available in the  Resources Directory
Class notes will be available on the Class Notes Directory

 Course Administration and Rules

Approximately 40% of the course grade will be determined by individual assignments, 45% by the midterm and final exams, 15% by your term project. Class attendance and participation will also be taken into account in determining the course grade. Late assignments may be discounted, and very late assignments may be discarded.  In order to achieve a passing grade, students must pass all three portions of the course (homework, exams, term project).

Academic Honesty: The individual assignments must be each student's own work.  Any group projects assigned must be the work of the students in the group.  Plagiarism or copying will result in official University disciplinary review. Security is an important aspect of computer science. Students are expected to protect their work from plagiarists.

There are no make-up exams in this course.  Normally if a student misses an exam the student will receive a grade of 0 on that exam. Under unusual circumstances (such as documented serious illness), the student's grade on a missed exam will be replaced by the grade on the final exam.


1/10 & 12
1/17 & 19
1/24 & 26
1/31 & 2/2

Intelligent Agents; Python Introduction

Using logic to represent an agent's knowledge

Automated reasoning

Automated reasoning (cont.)
RN 1.3 & 1.4,Ch 2

RN 7.1-7.5; Ch. 8 (review)
Ontology 101 paper
RN Ch. 9.1-9.3
RN 9.4-9.5
2/7 & 9

Search and Heuristics

RN Ch. 3
2/14 & 16



9 3/6 & 8

Planning in AI/Ontology Design

AI for games: Guest Lecture Prof.  Magy Seif El-Nasr
Ontology Design (cont.) and the Protege Tool

Discuss term projects/Review for midterm
Midterm Exam


RN Ch. 10, 11.1, 11.2.1, 11.2.2
Ontology 101 paper (review)

3/13 & 15
3/20 & 22

3/27 & 29

4/3 & 5


Probabilistic Reasoning and Bayes' Nets

Machine Learning 1: Classification Learning
  Decision Tree Learning
  Nearest Neighbor Methods

Machine Learning 2: Perceptrons and Neural Nets

Natural Language and ML: Part of Speech Tagging

Formal Grammars for Natural Language

RN Ch. 13, 14.1 - 14.4

RN 18.1-18.5

RN 18.7,

RN Ch. 22

RN Ch. 23.1-23.3

Student Presentations

Student Presentations

Final exam

Last modified: Feb 14, 2012