Download Course Intro

MITM613
Wednesday [ 6:00 – 9:00 ] am
1st week
Good evening …. Every body
•Course details
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1. Introduction to Intelligent Systems
2. Rule-based Systems
3. Uncertainty
4. Intelligent Agents
5. Symbolic Learning
6. Soft Computing
7. Hybrid Systems
8. Tools and languages
9. Current Trends and Issues in Intelligent Systems
•Course Objectives:
Upon
completion of programme, students should be able to:
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Explain the various methods of implementing Intelligent systems.
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Describe the issues involved in each method of implementing an
Intelligent System.
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Describe the tools that can be used.
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Develop a particular intelligent system of choice in a class project
environment
•Learning Outcomes:
1.
Define the terminology commonly used in Artificial
Intelligence (AI) and Intelligent Systems.
2.
Describe the different methods of AI and Intelligent Systems
namely the knowledge base system and the computational
learning systems.
3.
Analyze existing knowledge based system and computational
learning system.
4.
Design knowledge based system and / or learning system
such as expert system and prediction system.
•CONT.. Learning Outcomes:
5.
Use various tools for implementation and development of
knowledge based system and / or learning system.
6.
Implement an expert system by building the knowledge base
and the inferencing engine.
7.
Implement a prediction system using methods such as neural
network or Support vector machine.
Main Reference
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Adrian A. Hopgood,
Intelligent Systems
for Engineers and
Scientists, 2nd
Edition, CRC
Publication (2000).
Other Reference
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Michael Negnevitsky,
Artificial Intelligence:
A Guide to Intelligent
Systems, 2nd Edition,
Addison Wesley
(2004).
•Marks Distribution
Assignments
15%
Case Studies
10%
Quiz
5%
Mid-semester exam
15%
Project
15%
Final Exam
40%
•About Course Project:
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In groups of 4, your group would design and implementation a
realistic artificial intelligence application from the advanced
topics given below.
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The project consists of several parts, and would be graded
separately. Each team has to produce joint deliverables, which
will be the basis for the grades of all team members.
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The team members will also be asked for feedback on the
performance of the other team members. This subjective
feedback may be used to adjust individual scores. Team
members are also required to document their activities, e.g. in
the form of work sheets.
•CONT… About Course Project:
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The members of a team can select their own project topic,
subject to my approval. Ideally, the teams should have chosen a
topic by the end of the third week. If necessary, you can
postpone this decision into the fourth week, but this will leave
you with less time for the requirements specification.
Genetic Algorithms
Expert system
Neural Networks
Robotic
Fuzzy Logic
Case-based reasoning
Image Processing
Virtual reality
Signal Processing
Intelligent Agents
•CONT… About Course Project:
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Your final report should contain the follow sections : -
Front Cover
Title
Group Leader’s Name
Member’s Names
Members Pictures
Matrix number
Front Cover Details - Week 04
Report
- Week 12
Presentation
- Week 13
Report Format
1.0
Introduction
2.0
Review of two other application
3.0
Objective and Purpose of System
4.0
Existing Systems
5.0
Requirements of system
6.0
Methodology and Algorithms
7.0
System Analysis Design
8.0
Screen Design or Screen Capture
9.0
Comparison with two other applications
10.0
Problems Faced
11.0
References