UNIVERSITY OF COLOMBO

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UNIVERSITY OF COLOMBO SCHOOL OF
COMPUTING
IT5301 Intelligent Systems
DEGREE OF BACHELOR OF INFORMATION TECHNOLOGY
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Year 3 SEMESTER 5

• Compulsory Units
• Visual Computing
• Project Management Software Quality Management
• Optional Units
• Intelligent Systems
• Security of Information Systems
• Systems Network Administration

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IT5301 Intelligent Systems

• Course Objectives
• Applications of Intelligent Systems
• Reasons to be considered for selecting this unit
• Syllabus and Time Allocation
• Recommended Readings
• Introduce the Course Structure
• Topic Objectives
• Details of topics
• Examination Further Information

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Course Objectives

• Give students a grasp of the breadth of topics
  generally considered within the realm of
  Artificial Intelligence (AI)
• Introduce students to the key concepts in AI and
  their relationship to mainstream computing
• Impart skills in applying AI techniques for
  problem solving
• Providing an appreciation of the more advanced
  topics in AI

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Application of Intelligent Systems

• Diagnosis and Troubleshooting
• Planning and Scheduling
• Process Monitoring and Control
• Software Engineering

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Application of Intelligent Systems

• Diagnosis and Troubleshooting
• Example Electrical distribution system fault
  detection
• Collect data from instruments or users and deduce
  faults and suggest corrective actions

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Application of Intelligent Systems

• Planning and Scheduling
• Example Airline crew scheduling
• Planning assembly and test of printed
• circuit boards
• Constraints were described in some formal manner
  and used to guide an initial placement of tasks

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Application of Intelligent Systems

• Process Monitoring and Control
• Example Controlling a group of elevators
• Software Engineering
• Example tools to improve the process of
  software development

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AI Systems in use Medical
Applications

• ACORN Used in Accident Emergency Department
  Westminister Hospital, London
• Was built for use by senior nurses to assist in
  the management of patient.
• Why ?
• Medical audits have discovered that 38 of
  patients attending with acute heart disease were
  sent home in error.
• Technology used
• Hybrid backward-chaining rule-based and Bayesian
  system

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Fault Diagnosis

• Toshiba Company, Japan
• The system diagnoses faults and restores
  operation to an electric power system.
• Technology used
• Rules and frames based system
• The fault diagnosis system has 900 rules and the
  fault restoration system has 600 rules.

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Agriculture

• Virginia Tech Alexsndria, Virginia
• CRoPs System that selects crop rotations for
  each field on individual farms, ensuring that the
  combined crop rotations, i.e. the whole-farm
  plan, meets the production and financial needs of
  farmers

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Games and Animation

• Chess IBMs Deep Blue Chess program
• This program beats chess world champion in a
  match in 1997.
• Searches 200,000,000 positions per second.

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Syllabus and Time Allocation
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Recommended Readings

• Main Reference
• Artificial Intelligence A Modern Approach.
  Russell Norvig. Prentice Hall. 1995.

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• Supplementary Readings
• Artificial Intelligence A New Synthesis.
  Nilsson. Morgan Kaufmann. 1998.
• Computational Intelligence. Poole, Mackworth
  Goebel. Oxford. 1998.
• Building Expert Systems in Prolog. Merritt.
  Springer-Verlag. 1989.
• Computer Vision, D.H. Ballard and C.M. Brown,
  Pritice Hall

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1. Foundational Issues in
Intelligent Systems (6 Hrs.)

• Have a grasp of the history, nature and scope of
  AI
• Understand the need for AI in computing
• Be familiar with some of the underlying
  philosophical issues concerning AI

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2. Search Techniques
(10 Hrs.)

• Have a good grasp of the key AI concept of search
• Describe the major search algorithms of AI
• Apply search algorithms to solve real-world
  problems
• Apply algorithms for simple game playing

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3. Knowledge Representation
and Reasoning (10 Hrs.)

• Have a good grasp of the key AI concept of
  knowledge representation
• Describe the major knowledge representation and
  reasoning frameworks in AI
• Formulate how to represent knowledge in different
  problem contexts
• Describe how logic and reasoning works in static
  and changing situations
• Have a basic knowledge of how uncertainty is
  handled in reasoning

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4. Natural Language
Processing (10 Hrs.)

• Have a good grasp of the AI application area,
  Natural Language Processing (NLP)
• Describe the major stages of the NLP task
• Apply the techniques and algorithms for
  performing the subtasks of NLP
• Understand clearly the application areas of NLP
  technology

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5. Knowledge Based Systems
(10 Hrs.)

• Have a good grasp of the AI application area,
  Knowledge Based Systems (KBS)
• Understand the importance of separating knowledge
  from algorithm in KBSs
• Implement rule-based KB systems and understand
  how they may be extended to handle uncertainty
• Determine the appropriateness of KBS technology
  for real-life problems

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6. Computer Vision
(10 Hrs.)

• Have a good grasp of the AI application area,
  Computer vision
• Describe the main techniques used in image
  representation and recognition
• Understand how AI techniques are used for
  computer vision

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7. Introduction to other topics in AI (04
Hrs.)

• Have a basic awareness of other AI techniques
• Understand which real-life tasks these techniques
  may be useful in
• Appreciate the content of other course modules
  related to AI

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Tutorials /Practical Exercises

• Students are expected to have some practical
  knowledge in using Prolog

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Examination

• Three hour examination paper
• Structured Questions Only
• No Case Studies/Tutorials

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Further Information

• www.bit.lk
• Detailed Syllabus Topic Objectives
• Information ? Course Structure ?
• Semester 5 (IT5301)
• Queries
• it5301_at_ucsc.cmb.ac.lk