Courses:

Techniques in Artificial Intelligence (SMA 5504) >> Content Detail



Lecture Notes



Lecture Notes

The lecture notes in this section provide the slides used during class and accompanying transcripts of the in-class lectures given by the instructor.
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)


 



 








© 2010-2021 OpenCollege.com, All Rights Reserved.
Open College is a service mark of AmeriCareers LLC.