Introduction to Artificial Intelligence

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Lecture 0 : Course Introduction and Survey of Topics MS PowerPoint format
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Lecture 1: Intelligent Agents and Problem Solving MS PowerPoint format
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Lecture 2: Into to Search and Constraints MS PowerPoint format
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Lecture 3: Uniformed Search: DFS, BFS, B&B MS PowerPoint format
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Lecture 4: Constraint Satisfaction Problems MS PowerPoint format
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Lecture 5: Informed Search: Hill-climbing, Beam MS PowerPoint format
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Lecture 6: Informed Search: A* MS PowerPoint format
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Lecture 7: AI Applications 1: Interaction, Games MS PowerPoint format
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Lecture 8: Game Tree Search: Intro
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Lecture 9: Game Tree Search: Conclusion MS PowerPoint format
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Lecture 10: Knowledge Representation MS PowerPoint format
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Lecture 11: Intro to Propositional Logic MS PowerPoint format
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Lecture 12: Propositional Inference MS PowerPoint format
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Lecture 13: Production Systems MS PowerPoint format
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Lecture 14: Predicates and Relations MS PowerPoint format
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Lecture 15: First Order Logic MS PowerPoint format
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Lecture 16: First-Order Knowledge Bases MS PowerPoint format
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Lecture 17: Clausal (Conjunctive Normal) Form MS PowerPoint format
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Lecture 18: Unification MS PowerPoint format
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Lecture 19: Resolution Theorem-proving / Review MS PowerPoint format
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Lecture 20: Theorem-proving and Decidability MS PowerPoint format
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Lecture 21: Logic Programming MS PowerPoint format
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Lecture 22: Hour Exam 1 (Closed-Book)
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Lecture 23: Classical Planning / Midterm ReviewMS PowerPoint format
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Lecture 24: More Classical Planning MS PowerPoint format
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Lecture 25: Hierarchical Abstraction Planning MS PowerPoint format
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Lecture 26: Conditional Planning and Replanning MS PowerPoint format
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Lecture 27: Universal Reactive Planning MS PowerPoint format
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Lecture 28: Uncertainty and Probabilistic Reasoning MS PowerPoint format
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Lecture 29: Probability Review; Bayesian Inference MS PowerPoint format
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Lecture 30: Intro to Graphical Models, Part I MS PowerPoint format
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Lecture 31: Intro to Graphical Models, Part II MS PowerPoint format
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Lecture 32: AI Applications 2: Machine Translation MS PowerPoint format
Lecture 33: Inference in Graphical Models MS PowerPoint format
Lecture 34: Introduction to Machine Learning MS PowerPoint format
Lecture 35: Machine Learning Basics / Review MS PowerPoint format
Lecture 36: Decision Trees MS PowerPoint format

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