MITM613 Wednesday [ 6:00 – 9:00 ] am 1 st week

Good evening …. Every body

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 details

 Upon completion of programme, students should be able to: Explain the various methods of implementing Intelligent systems. Describe the issues involved in each method of implementing an Intelligent System. Describe the tools that can be used. Develop a particular intelligent system of choice in a class project environment Course Objectives:

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. 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. CONT.. Learning Outcomes:

Main Reference Adrian A. Hopgood, Intelligent Systems for Engineers and Scientists, 2nd Edition, CRC Publication (2000). Other Reference Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems, 2nd Edition, Addison Wesley (2004).

Marks DistributionAssignments15% Case Studies 10% Quiz5% Mid-semester exam 15% Project15% Final Exam 40%

In groups of 4, your group would design and implementation a realistic artificial intelligence application from the advanced topics given below. 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. 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. About Course Project:

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. CONT… About Course Project: Genetic AlgorithmsExpert system Neural NetworksRobotic Fuzzy LogicCase-based reasoning Image ProcessingVirtual reality Signal ProcessingIntelligent Agents

Your final report should contain the follow sections : - CONT… About Course Project: Front Cover Title Group Leader’s Name Member’s Names Members Pictures Matrix number Report Format 1.0 Introduction 2.0Review of two other application 3.0 Objective and Purpose of System 4.0Existing Systems 5.0Requirements of system 6.0Methodology and Algorithms 7.0System Analysis Design 8.0Screen Design or Screen Capture 9.0Comparison with two other applications 10.0Problems Faced 11.0References Front Cover Details - Week 04 Report - Week 12 Presentation - Week 13