CSC361

Artificial Intelligence

CSC361

Spring 2011

Project Grading (Phase 1)

Game rules for the project (New)

Course outline

Project Deliverables,Semester Schedule and Rubrics

Attendence & Bonus: Any discripencies send an e-mail to basit@ksu.edu.sa

Course Code: CSC 361

Course Title: Artificial Intelligence

Credit Hours: 3(3,0,1)

Lecture Time: 1:0 - 3:0 Sunday & 1:0 - 3:0 Tuesday

Pre-requisites: CSC 212

Course Description:

This course provides a general introduction to AI (Artificial Intelligence): Its techniques and its main sub-fields. It gives an overview of underlying ideas, such as search, knowledge representation, expert systems and learning.

Course Objective:

The objective of the course is to enable students to learn about the tools and techniques for understanding and applying their knowledge to solve real world problems. The course will focus on sharpening the practical skills of the students alongwith providing them the theoratical knowledge.

Syllabus (Course in Progress)

Week H date	Week #	Chapter	Topic/Readings	Assignment/ Homework	Note
	1	Course Description	Course Description
	2	1 Introduction	What is Artificial Intelligence?	Blogr	eCorrect Service
			Introduction
	3	2 Problem Search Solving	Problem Solving by Searching
			Problem formulation
	4	- Uninformed Search	Breadth First Search (BFS)	Assignment2
			Uniform Cost Search (UCS)
	5	Un-informed Blind search	Depth First Search (DFS)
			Iterative Deepening Search (IDS)	Assignment3
	6	- Informed Search	Heuristic Functions	Assignment4
			Greedy Search
	7		A* Search
			Iterative Deepening A*
	8	- Optimization	Hill Climbing
			Simulated Annealing,
		Rest


	9	3 Constraint Satisfaction Problems (CSP)	Backtracking Search

	10	4 Game Playing Dersarial Search and Game Playing examples	Game Playing
			Alpha-beta Game Playing
	11	5 Knowledge Representation	Propositional Logic
			Inference Propositional Logic
	12	-First Order Logic	First Order Logic
			Inference First Order Logic
	13	6 Neural Netorkws	Introduction to Neural Networks
		7 Machine Learning

Recommended Books

1. “Artificial Intelligence: A modern approach”

Stuart Russell, Peter Norvig, Prentice Hall, 2003 (new edition 2006)

2. "Artificial Intelligence - Structures and Strategies for Complex Problem Solving", George F. Luger, Pearson Internationl Edition, 2009

3. “Artificial Intelligence Illuminated”

Ben Coppin, Jones andBartlett Publishers, 2004

4. “Artificial Intelligence: A new synthesis”

Nils Nilsson, Morgan Kaufmann, 1998

5. “Introduction to expert systems”

Peter Jackson, Addison Wesley, 1999

6. Lecture slides and your lecture notes!

Grading

Exam	Score Ratio	Time	Place
MedTirm1	20%	1:00 - 3:00 , Sunday 5th December 2010	CCIS Building, Room # 30
MedTirm2	20%	1:00 - 3:00 , Sunday 26th December 2010	CCIS Building, Room # 30
Final exam	40%	TBD
Homework, Quizzes, Project	20%	TBD	CCIS Building, Room # 30