# Notes and Reading - Lecture #5

Lecture #5 looked at handling uncertainty, and, in particular, the
use of probability theory.

### Notes

Notes are available in two formats:

### Reading

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.