Course Objectives
Upon completion of this course, students
1. will know what the goals, objectives and subfields of artificial intelligence are
2. will learn to design and develop computer systems that exhibit intelligent behavior
3. will obtain a sound background concening: heuristic search and search techniques in general, machine learning and
its application, automated theorem proving, games, and knowledge-based systems.
4. will learn about the importance of heuristics in AI systems and
how to come up and enhance heuristics based on feedback.
5. will learn about AI specific programming concepts and languguages, such as LISP and PROLOG
6. will learn to develop computer systems relying on a rapid prototyping approach
7. will get some exposure related to the theoretical, philophical, and social aspects of AI
Textbook
George, F. Luger, Artificial Intelligence, Addison Wesley, 5th Edition, 2005
Student Resources Luger Book
Tentative Course Organization
I Introduction to Ai (Luger 1.1. 1.2, 1.3; what is AI, subfields of AI)
II Heuristic Search (Luger chapters 3 and 4; additional transparencies)
III Machine Learning (Luger Chapters 10, 11, 12; additional transparencies)
IV Automated Reasoning (Predicate Calculus(Luger Section 2.3ff), Luger Chapter 13)
V Reasoning in Uncertain Environments (Luger Chapters 5 and 9)
VI Knowledge-based Systems and Expert Systems (Luger chapter 8; might be
skipped due to the lack of time and of decent teaching material in Luger's book)
VII What is unique about AI progrmming?
VII History of AI and Last Words
Course Elements
Exams(Feb. 26, March 27, TBDL)
Programmining Projects (starting in the February 11 week)
Graded and "Ungraded" Homeworks
The final course grade will be computed as follows: Exam(62%) and
Assignments (38%)---weights are subject to change.
News COSC 4368 Spring 2008
Grade Distribution in 2008: A:2, B+:3, B:1, C+:2.
Scores of Exams and Assignments.
Solution sketeches Midterm2; solutions
of other problems will be distributed as handouts in the May 1 class.
Some Solution Sketches for Assignment1 and
for Solution Sketches for Midterm1.
Due to the fact that Dr. Eick has not taught this course for almost 10
years, the organization of the course as well
as this webpage itself are evolving entities. Please, check the course
webpage at least twice a week.
Reading assignments---read textbook pages: 1-2, 20-31 by Jan. 23: read
chapter 3 excluding subsection 3.3; Jan. 25: read chapter 4, Feb. 7: look
at Mitchell transparencies and
read pages 385-390 and chapter 12; Feb. 12: read chapter 10; March 29:
read 13.2 and 13.3!
2008 Programming and Homework Assignments
Assignment1 (Heuristic Search;
Rook and King vs.
King Animation, Basic Checkmates, Possible Heuristics)
Assignment2 (Machine Learning and FOPL)
Assignment3 (Theorem Proving/Resolution, Reasoning in Uncertain Environments)
Class Transparencies
- Introduction to AI: Dr. Eick's
Introduction to AI, Luger Chapter1 Material.
- Heuristic Search:
Luger Chapter 3a,
Luger Chapter 3b,
Eick Search1,
Eick Search1b(new),
Eick Search2,
Luger Chapter 4a,
Luger Chapter 4b,
Luger Chapter 4c,
Eick Search3.
- Machine Learning:
Tom Mitchell's Introduction to Machine
Learning (Tom Mitchell's
Homepage), EC(EvoNet EC Introduction,
Using EC to Solve TSP, Alife Introduction,
Brief Introduction to
Evolutionary Machine Learning,
Introduction to Genetic Programming,Luger Chapter 12),
Introduction to Classification
and Decision Trees,
Introduction to Reinforcement Learning, Luger Chapter 10.
- Automated Reasoning: Syntax of FOPL,
Eick on Resolution, Eick on
Logic, simple resolution proofs,
Russel on Resolution,
Luger Resolution Material.
- Reasoning in Uncertain Environments (Luger
Probability Theory Review, Eick on Naive Bayesian
Classifier (only transparencies 1, 2, 13, 14 will be used),
Luger: A Few Belief Network Transparencies,
Eick: Brief Introduction to Belief Networks,
Netica Download---Netica
is a belief network tool that will be used in Assignment3)
- Fuzzy Logic and Knowledge-based Systems (KBS in
2 transparencies, Fuzzy
Set1 (will only use first 5 transparencies),
Fuzzy Set2)
- Last Words and Brief History of AI
last updated: April 30, 9a