This folder introduces probabilistic reasoning in dynamic environments, starting with assumptions one makes so as to make inference tractable. It consists of:
- two videos of short lectures. They cover:
- Stationary Processes and the Markov Assumption
- Inference: Filtering and Prediction
- Some required reading from Russell and Norvig
- A quiz that tests your understanding of the material presented here.
Please watch the videos or attend the in-persion lecture, do the required reading, and attempt the quiz. If there is anything you don't understand, then please ask your question at the lecture or post it on piazza.
Lecture 26 Slides: Whole!
26a: Stationary Processes and the Markov Assumption
26a slides: 26a.pdf
26b video:
26b: Inference: Filtering and Prediction
26b slides: 26b.pdf
26b video:
Required Reading
R&N Section 15.1–15.2 or NIE Chapter (15) "Probabilistic Reasoning over Time", 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 26: Time and Uncertainty I
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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