last modified: 23/02/2006

Course code: Wb5435-05

Course name: Machine Intelligence

This concerns a Course

ECTS credit points: 3

Faculty of 3mE

Section of Man-Machine Systems

Lecturer(s): Prof.dr. T. Tomiyama

Tel.:  015 - 27 81021 /      

 

Course year:

MSc 1st year

Course language:

English

In case of Dutch: Please contact the lecturer about an English alternative, whenever needed.

Semester:

2A

Hours per week:

4

Other hours:

     

Assessment:

Written exam

Assessment period:

2A

(see academic calendar)

 

Prerequisites (course codes):

Computer programming courses

Engineering Informatics (Wb5430-05), not a must but recommended

Follow up (course codes):

     

Detailed description of topics:

This course firstly gives an introduction to computational aspects of intelligent systems, in particular, artifical intelligence, logic, and knowledge based systems. These techniques form symbolic computing techniques for advanced reasoning and embedded intelligence. Secondly, the course discusses some soft computing techniques that have been hinted or inpired by biological phenomena or other physical phenomena, such as fuzzy logic, genetic algorithm, simulated annealing, and artificial neural networks. Thirdly, the course illustrates some techniques for intelligent systems to deal with real world applications.

The course will not only describe theoretical apsects but also depict applications of these technique to intelligent systems and engineering.

 

Topics

 

1. Fundamental Theories and Techniques

1.1. Artificial Intelliigence, Pattern Recognition, and Robotics

1.2. Logic

1.3. Knowledge Representation

1.4. Fundamental Reasoning Techniques

1.5. Knowledge Based Systems

 

2. Soft Computing and Bio-Inspired Computing

2.1. Fuzzy Logic

2.2. Genetic Algorithm

2.3. Simulated Annealing

2.4. Artificial Neural Networks

 

3. Intelligent Systems

3.1. Model-based Reasoning and Qualitative Physics

3.2. Machine Learning

3.3. Self-Organization and Emergence

Course material:

  • Benny Raphael, Ian F. C. Smith, Fundamentals of Computer Aided Engineering, ISBN: 0-471-48715-5, (2003), Wiley & Sons.
  • Handouts
  • Other references will be specified during the course or obtainable from the blackboard.

 

References from literature:

  •      

Remarks assessment, entry requirements, etc.:

Assesment will be based on the final exam and or final report.

Learning goals:

The student must be able to:

  1. describe fundamental logical computing techniques and soft computing techniques

  • explain principles of logic, knowledge representation techniques, and reasoning algorithms

  • explain principles of fuzzy logic, genetic algorithm, simulated annealing, and artificial neural networks

  1. describe fundamental mechanisms and architecture of reasoning systems and embedded intelligence

  • explain mechanisms and architecture of knowledge based systems, model-based reasoning systems, machine learning systems

  • explain mechanisms of self-organization and emergent systems

  1. implement intelligent systems using these techniques to deal with real world applications

  • compare different computing techniques

  • select an appropriate method for the application, based on the comparison

  • compose an algorithm for the chosen method

  • demonstrate the algorithm in some way (not necessarily in the form of programs)

Computer use:

Not necessary.

Laboratory project(s):

     

Design content:

The course helps to understand how to design "intelligent systems."

Percentage of design:  20%