COSC 387: Artificial Intelligence

Fall 2000

Primary Texts:

Schedule

Week 
Topic 
Chapters 
     
Week 1  Introduction: What is AI?, Strong vs. Weak
1
Week 2  Introduction: Areas, Brief History, Paradigms
1
Week 3  Symbolic Programming and Lisp
2
Week 4  Blind Search: Depth-First, Breadth-First
4
Week 5  Informed Search: Hill-Climbing, Beam, Best-First, Genetic Algorithms
4
Week 6  Admissible Search: Brand-and-Bound, A*
4
Week 7  Logic: Propsitional, Resolution, Predicate
3
Week 8  Logic: Unification, First-Order Resolution, Midterm Exam
3
Week 9  Learning: Nearest Neighbor, Naive Bayes
5
Week 10 Learning: Tree and Rule Induction, Information Retrieval
5
Week 11 Learning: Neural Networks, Perceptron, Back-propagation
5
Week 12 Image Understanding: Binary and Grayscale Vision
9
Week 13 Image Understanding: Stereo Vision, Optical Flow
9
Week 14 Uncertainty: Bayesian Inference Networks
8
Week 15   Uncertainty: Utility Theory; Philosophical Issues in AI
8
     
Dec. 18, 4-6 PM   Final Exam
 


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