Lecture Videos

Lecture 1: Introduction and Scope

Lecture 2: Reasoning: Goal Trees and Problem Solving

Lecture 3: Reasoning: Goal Trees and Rule-Based Expert Systems

Lecture 4: Search: Depth-First, Hill Climbing, Beam

Lecture 5: Search: Optimal, Branch and Bound, A*

Lecture 6: Search: Games, Minimax, and Alpha-Beta

Lecture 7: Constraints: Interpreting Line Drawings

Lecture 8: Constraints: Search, Domain Reduction

Lecture 9: Constraints: Visual Object Recognition

Lecture 10: Introduction to Learning, Nearest Neighbors

Lecture 11: Learning: Identification Trees, Disorder

Lecture 12A: Neural Nets

Lecture 12B: Deep Neural Nets

Lecture 13: Learning: Genetic Algorithms

Lecture 14: Learning: Sparse Spaces, Phonology

Lecture 15: Learning: Near Misses, Felicity Conditions

Lecture 16: Learning: Support Vector Machines

Lecture 17: Learning: Boosting

Lecture 18: Representations: Classes, Trajectories, Transitions

Lecture 19: Architectures: GPS, SOAR, Subsumption, Society of Mind

Lecture 21: Probabilistic Inference I

Lecture 22: Probabilistic Inference II

Lecture 23: Model Merging, Cross-Modal Coupling, Course Summary