Topic outline

  • Course Information


    This course introduces students to the principles of Artificial Intelligence which includes Expert System, Fuzzy Logic, Artificial Neural Networks and Genetic Algorithm. Project based exercise will be also included in order to have a better understanding on the course.

    Course Outcomes

    At the end of this course student should be able to:

    ·         Explain the concept of intelligent control and their applications.

    ·         Design the fuzzy logic and artificial Neural Networks through case study or project based exercise.

    ·         Analyze Genetic Algorihtm system trough case study.

    ·         Use and apply engineering tools to simulate various intelligent system.

    ·         Explain the impact of engineering solution in global context.


    1. Michael Negnevitsky, “Artificial Intelligence : a Guide to Intelligent Systems”, Addison Wesley, 2005.
    2. Marzuki Khalid, “Artificial Intelligence : Fuzzy Logic Module”, Universiti Teknologi Malaysia.
    3. Marzuki Khalid, “Artificial Intelligence : Artificial Neural Networks Module”, Universiti Teknologi Malaysia

  • Topic 1

    Chapter 1: Introduction to Artificial Intelligence

    1.1 Overview of Artificial Intelligence (AI)
    1.2 Artificial Intelligence application
    1.3 Comparison with classical controller

  • Topic 2

    Chapter 2a: Expert System

    2.1 Knowledge representation technique

    2.2 Expert system development team

    2.3 Rule-based expert system structure

  • Topic 3

    Chapter 2b: Expert System

    2.4 Expert system characteristic

    2.5 Forward and backward chaining

    2.6 Conflict resolution

  • Topic 4

    Chapter 3a: Fuzzy Logic

    3.1 Overview of Fuzzy Concepts and Fuzzy Logic Systems

    3.2 Definition of Fuzzy Sets

  • Topic 5

    Chapter 3b: Fuzzy Logic

    3.3 Fuzzy Set Operation

    3.4 Fuzzy Relation

  • Topic 6

    Chapter 3c: Fuzzy Logic

    3.5 Fuzzy Inference

    3.6 Fuzzy Logic Control

  • Topic 7

    Chapter 4a: Artificial Neural Network

    4.1 Basic Concepts

    4.2 ANN Applications

  • Topic 8

    Chapter 4b: Artificial Neural Network

    4.3 ANN Model

    4.4 ANN Learning

  • Topic 9

    Chapter 4c: Artificial Neural Network

    4.5 Simple ANN

    4.6 Multilayer Neural Network & Backpropagation Algorithm

  • Topic 10

    Chapter 5: Genetic Algorithm (GA)

    5.1 Basic Concepts

    5.2 Genetic Algorithm

    5.3 Case Study

  • Previous Test Questions

    Previous Test Questions

  • Previous Final Exam Questions

    Previous Final Exam Questions

  • Topic 13