Lecture #5 looked at handling uncertainty, and, in particular, the use of probability theory.
Notes are available in two formats:
This lecture was based on Chapters 13 of the text book, Section 13.1 through 13.5. As ever, the book goes into much more detail than I did.
The following paper is easy to read, and gives a flavor of what the world was like when the majority view in AI was that probability wasn't very helpful:
P. Cheeseman, In defence of probability, Proceedings of the 9th International Joint Conference on Artificial Intelligence, Los Angeles, 1985.Here too, thanks to Carlos, is one of Judea Pearl's classic papers that laid the foundations for Bayesian networks:
J. Pearl, How to do with probabilities what people say you can't, Proceedings of the Second Conference on Artificial Intelligence Applications, Miami, 1985.