Website:

        http://mcs.sci.kuniv.edu.kw/~almulla/courses/cs459/cs459.html

Class Time & Location:

        135 11:00-11:50, room Kh\11-209, Khaldia Campus

Instructor

• Mohammed Almulla
• almulla@mcs.sci.kuniv.edu.kw
• Tel: (965) 481-1188 Ext. 5303
• Khaldia\1 Building, Room 3135
• Office hours: Mon, Wed 10-11 am

• Galal Hassan
• galal@mcs.sci.kuniv.edu.kw
• Tel: (965) 481-1188 Ext. 7857 (office)
• Khal/3, Second floor, TA offices
• Office hours:


Sat: 11-1 and 2-3

Sun: 10-12 and 1-2 in classroom

Mon: 11-1 and 2-3

Tue: 11-12

Wed: 10-11 and 2-3

This course is designed to introduce students to a set of theoretical and computational search techniques that serve as a foundation for the study of Artificial Intelligence.
The course requiers background in computer science. The emphasis is on algorithms and theoretical machinery for building and analysing AI systems. Traditional symbolic AI techniques such as deductive inference, game-tree search, and learning systems are covered. The coverage is broad, with selected topics explored in greater depth but with no attempt to exhaustively survey the entire field.

Prerequisites

You should be familiar with programming in high level languages including the use of modular programming, parameter passing mechanisms, analysis of algorithms, and data structures. I expect that all students should be familiar with Pascal/C/C++ and that most of you have had some exposure to ML and/or JAVA. This material is covered in the courses 126, 206, 230, and 350.
Full exposure to algorithms, data structures and knowlege representation is needed for this course. This material is covered in the course 356, which is the actual prerequisite for this course.

Textbook

• Artificial Intelligence, Elaine Rich & Kevin Knight, Second Edition, McGraw Hill

Many textbooks can be used as references for this course. Here are some:

• Principles of Artificial Intelligence, Third Edition, Nils J. Nilsson, Morgan Koffman Publishing Company, ISBN: 0-934613-10-9
• Artificial Intelligence Theory and Practice, Thomas Dean, The Benjamin/Cummings Publishing Company, ISBN: 0-8053-2547-6
• The Great Theorem Prover, Version 3.0, Monty Newborn, Newborn Software Publishing Company.
• How Computer Play Chess, David Levy and Monty Newborn, Computer Science Press, ISBN: 0-7167-8121-2

1. Assignments  %10  (4 assignments)
2. Midterm        %20 (Saturday 26/4/2003,   in class)
3. Project          %30
4. Final Exam    %40 (Sunday 8/6/2003,   8-10 am)

• Search & Problem-Solving
•     Problem-Solving Methods:
•         Generate & Test.
•         Means-End Analysis.
•         Problem Reduction.
•     Algorithmic Search:
•         Breath-First Search.
•         Depth-First Search.
•         Iteratively-Deepening Depth-First Search.
•     Heuristic Search:
•         Hill climbing Search.
•         Beam Search.
•         Best-First Search.
•     Optimal Search:
•         British-Museum.
•         Branch & Bound.
•         Dynamic Programming.
•         A* Algorithm.
•     Tree Search Algorithms:
•         Minimax Search.
•         Alpha-Beta Search.
• Logic and Resolution Proofs:
•     Introduction to Logic.
•         Propositional Calculus.
•         First-order Predicate Calculus.
•     Unification.
•     Resolution.
•     Semantic Trees.
• Programming AI Applications Using:
•     Functional Programming:
•         ML
•     Symbolic Programming:
•         PROLOG
• Selected topic TBA in class.

1. Assignment #1
2. Assignment 2
3. Assignment #3
4. Assignment #4

• Othello
• TicTacToe