Course Overview
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Course Synopsis
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Artificial Intelligence is the study of the science of making intelligent machines, especially intelligent computer programs. In this field we try to understand human intelligence and after it we use computers to adapt (implement using computer programs) this intelligence. This subject contains concepts from many other subjects of computer science and it uses these concepts to give practical solutions for the benefit of human beings.
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Course Learning Outcomes
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After completing this course you should be able to:
- Define that what is artificial intelligence and why it is important.
- Analyze and apply any search strategy over the given problem.
- Learn about some successful application of artificial intelligence.
- Characterize and classify expert systems.
- Design expert system.
- Use CLIPS software for expert system development.
- Examine fuzzy systems.
- Research machine learning and planning.
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Course Calendar
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Week 01
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2
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Formal Definitions for Artificial Intelligence
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3
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History and Evolution of Artificial Intelligence
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Week 02
Week 03
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7
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DFS, BFS and Progressive Deepening
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8
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Heuristically Informed Searches
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Assignment 1
Week 04
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12
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Genetic Algorithm Problems
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Quiz 1
Week 05
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14
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Knowledge Representation and Reasoning
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Week 06
GDB
Quiz 2
Week 07
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19
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Roles of an expert system
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20
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Expert System & Forward Chaining
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Week 08
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24
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CLIPS Integrated Development Environment
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Mid-Term Exams
Week 09
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25
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Design of expert systems
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26
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Design of expert systems 2
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Week 10
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28
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Handling uncertainty with fuzzy systems
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30
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Fuzzy Set Representation
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Quiz 3
Week 11
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31
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Fuzzy Inference System
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32
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Fuzzy Inference Process
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Assignment 2
Week 12
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35
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Version Space and Searching
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36
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Candidate Elimination Algorithm
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Week 13
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37
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Decision Trees Learning
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Quiz 4
Week 14
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40
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Multiple layers of Perceptrons
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41
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Supervised and Un-supervised Searches
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Week 15
Final-Term Exams
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