INF2D: 20: Uncertainty, Rationality and Probability
We now start a new, and final, part of the course. From now on, we will be studying how one can use probabilistic inference combined with quantified metrics for representing preferences (the bigger the number, the more the agent wants it), to model agents that make rational decisions. This section introduces some basic concepts, which we will then study in much more detail for the remainder of the course.
Lecture Slides
Lecture 20 (Previous Year's Notes Version) Slides:
Required Reading
R&N Section 13.1–13.2 or NIE Chapter (13) "Quantifying Uncertainty", Sections 1–2.
NOTE: The abbreviation R&N refers to:
“Artificial Intelligence: A Modern Approach” Third Edition, Russell R & Norvig P, Prentice Hall, 2010 (R&N).
The abbreviation NIE stands for the following edition of the same book:
“Artificial Intelligence: A Modern Approach” Third Edition, Pearson New International Edition, Russell R & Norvig P, Pearson, 2014.
Quiz Acting under Uncertainty
These questions are designed to test your understanding of the above course content; doing this quiz does not contribute to your overall grade. Some questions require a text answer. You can ask for formative feedback on these from your tutor or on piazza. Other questions are multiple choice or they require a numeric answer: you will get immediate feedback for these. Please don't attempt this quiz until you have acquainted yourself with this lecture and the required reading.
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