Lecture Notes

Notes from lectures 6 and 21 are not available.

Lecture 1: What is Artificial Intelligence (AI)? (PDF)

Lecture 2: Problem Solving and Search (PDF)

Lecture 3: Logic (PDF)

Lecture 4.: Satisfiability and Validity (PDF - 1.2 MB)

Lecture 5.: First-Order Logic (PDF)

Lecture 7.: Resolution Theorem Proving: Propositional Logic (PDF)

Lecture 8.: Resolution Theorem Proving: First Order Logic (PDF)

Lecture 9: Logic Miscellanea (PDF)

Lecture 10: Planning (PDF)

Lecture 11: Partial-Order Planning Algorithms (PDF)

Lecture 12: Graph Plan (PDF)

Lecture 13: Planning Miscellany (PDF)

Lecture 14: Probability (PDF)

Lecture 15: Bayesian Networks (PDF)

Lecture 16: Inference in Bayesian Networks (PDF)

Lecture 17: Where do Bayesian Networks Come From? (PDF)

Lecture 18: Learning With Hidden Variables (PDF)

Lecture 19: Decision Making under Uncertainty (PDF)

Lecture 20: Markov Decision Processes (PDF)

Lecture 22: Reinforcement Learning (PDF)

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