SCHOOL OF COMPUTING
UUM COLLEGE OF ARTS AND SCIENCES
UNIVERSITI UTARA MALAYSIA
COURSE CODE
COURSE
PRE-REQUISITE
SEMESTER
1.0
:
:
:
:
STIN1013
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
NONE
A132
SYNOPSIS
This course discusses the fundamental aspects of Artificial Intelligence (AI) field in terms of
definition, history and characteristics, example of applications, knowledge representation and
problem solving techniques, and several AI programming languages. Towards the end of the
course, there are several discussions of AI advanced technology.
2.0
OBJECTIVE
Upon completion, students are expected to be able to
2.1
2.2
2.3
understand the concept and problem solving principle.
understand different types of AI knowledge representation techniques.
apply knowledge and skill necessary to solve problem using AI techniques.
3.0
LEARNING OUTCOME
Upon completion, students are expected to be able to
3.1
3.2
3.3
3.4
3.5
describe the characteristics of intelligent systems.
identify the differences between intelligent systems and conventional systems.
use appropriate techniques to represent knowledge.
solve the given problems using appropriate AI techniques.
identify the need and opportunity for adopting AI techniques into real world application.
4.0
REFERENCES
Bratko, I. (2011). PROLOG Programming for Artificial Intelligence (4th Edition). Reading:
Addison-Wesley.
Ertel, W. (2011). Introduction to Artificial Intelligence. London: Springer-Verlag.
Floreano, D. & Mattiusi, C. (2008). Bio-inspired Artificial Intelligence: Theories, Methods and
Technologies. Cambridge: MIT Press.
Jones, T. (2008). Artificial Intelligence: A Systems Approach. Massachusetts: Infinity Science
Press LLC.
Luger, G. F. (2009). Artificial Intelligence: Structures and Strategies for Complex Problem Solving
(6th). Addison-Wesley Publishing Co.
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Negnevitsky, M. (2011). Artificial Intelligence: A Guide to Intelligent Systems. England: Addison
Wesley.
Nilsson, N. (2008). The Quest for AI. New York: Cambridge University Press.
Padhy, N. P. (2005). Artificial Intelligence and Intelligent Systems. New Delhi: Oxford University
Press.
Russell, S. J. & Norvig, P. (2009). Artificial Intelligence: A Modern Approach (3rd Edition). New
Jersey: Prentice Hall.
Warwick, K. (2012). Artificial Intelligence: The Basics. Oxon: Routledge.
CONTENT
5.0
NO.
TOPIC
HOUR
1
1.0 Introduction to Artificial Intelligence
1.1 Definition of AI
1.2 History of AI
1.3 Characteristics of AI Systems
1.4 Artificial intelligence as different approach in computing world
1.5 Applications using Artificial Intelligence
1.6 Philosophical Foundations of Artificial Intelligence
2.0 Knowledge and Reasoning
2.1 Definition of knowledge
2.2 Knowledge categories and hierarchy
2.3 Knowledge representation
2.3.1 OAV, semantic network and frames (object-based)
2.3.2 Production rules (rule-based)
2.3.3 Propositional logic (logic-based)
2.3.4 Predicate calculus (FOPL) (logic-based)
2.4 Knowledge reasoning and inference
2.4.1 Modus Ponens
2.4.2 Modus Tollens
2.4.3 Hypothetical Syllogism
2.4.4 Resolution
2.5 Expert Systems
2.5.1 Chaining Strategy
2.6 Case-based Reasoning
2.7 Fuzzy Logic
3.0 Problem Solving and Strategies
3.1 Problem solving paradigms
3.1.1 State space vs problem reduction paradigm
3.2 Blind/Uninformed search strategies
3.2.1 Breadth-first search
3.2.2 Depth-first search
3.2.3 Uniform cost search
3.2.4 Depth limited search
3.2.5 Iterative deepening search
3.3 Heuristic/Informed search strategies
3.3.1 Hill climbing search
3.3.2 Best-first search
3
2
3
2
12
12
4
4.0
5
5.0
6
6.0
7
7.0
3.3.3 A* algorithm
3.4 Comparison of search strategies
Learning
4.1 Learning from observations
4.2 Neural Networks learning
4.3 Reinforcement learning
Communicating, perceiving and acting
5.1 Communication
5.2 Perception
5.3 Robotics
Artificial Intelligence Programming
6.1 Programming in Logic (PROLOG)
6.2 List Processing (LISP)
6.3 Object based programming
6.4 Agent based programming
AI: Present and Future
7.1 Applications of AI in real world
7.2 Advanced Technology in AI
3
3
6
3
TOTAL HOURS
6.0
42
TEACHING METHOD
42 hours lecture, demo, discussion, tutorial and self-centred learning (SCL).
7.0
ASSESMENT
Coursework:
Quiz / SCL
Assignment*
Test**
Final examination
TOTAL
10%
40%
10%
60%
40%
100%
*There will be TWO (2) assignments on topics no. 2, 3 and 6; each worth 20 marks (15 marks for
the submitted scripts + 5 marks for presentation). All assignments are group assignments.
**Tentative date for Test is Friday, 28th March 2014 OR 18th April 2014 (kindly mark this date on
your calendar). The exact date, time and venue will be announced later.
8.0
Group
A
B
C
LECTURER INFO
Name
Nur Azzah Abu Bakar
Aniza Mohamed Din
Dr. Husniza Husni
Room No.
2103, SOC Building
3040, SOC Building
3035, SOC Building
3
Phone
04-9285166
04-9285189
04-9285184
E-mail
nurazzah
anizamd
husniza
9.0
OTHERS
Plagiarism is considered as a very serious academic misconduct. All students are responsible to
make sure their work are free from plagiariasm. The lecturers will not tolerate, and will not
assess any plagiarised attempt found in students’ work.
4