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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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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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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12
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Genetic Algorithm Problems
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14
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Knowledge Representation and Reasoning
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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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24
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CLIPS Integrated Development Environment
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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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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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31
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Fuzzy Inference System
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32
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Fuzzy Inference Process
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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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37
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Decision Trees Learning
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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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47
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Assignment: All topics that has been broadcast
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