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INF2D: 28: Dynamic Bayesian Networks

This folder presents an example Dynamic Bayesian Network (DBN) that makes some odd predictions, and a revised design of the DBN to fix that issue.  The purpose is to show you when you might want to revise your model, making it more complex by introducing a new random variable.  The folder consists of the following material:

  • two videos of short lectures.  They cover:
    1. Dynamic Bayesian Networks I
    2. Dynamic Bayesian Networks II
  • 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 28 Slides: Whole!

28.pdf

28a: Dynamic Bayesian Networks I

28a slides: 28a.pdf 
28a video:

28b: Dynamic Bayesian Networks II

28b slides: 28b.pdf 
28b video:

Required Reading

R&N Section 15.5  or NIE Chapter (15) "Probabilistic Reasoning over Time", Section 5.

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 28: Dynamic Bayesian Networks

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.

You must be logged onto Learn to do this quiz.

License
All rights reserved The University of Edinburgh

Book traversal links for INF2D: 28: Dynamic Bayesian Networks

  • INF2D: Week 10: Rational Decision Making
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  • INF2D: 29: Decision Making Under Uncertainty

Navigation links

  • INF2D: Course Overview
  • INF2D: Course Materials
    • INF2D: Week 1 - Introduction. Intelligent Agents. Search Problems
    • INF2D: Week 2: Informed Search and Using Constraints, Adversarial Search
    • INF2D: Week 3: Revision, CW1 and Logical Agents
    • INF2D: Week 4: Propositional Inference, First-Order Logic, Unification
    • INF2D: Week 5: Resolution, Situation Calculus, Revision
    • INF2D: Week 6: Symbolic Planning
    • INF2D: Week 7: From Symbolic Planning to Uncertainty and Rationality
    • INF2D: Week 8: Probabilistic Inference
    • INF2D: Week 9: Approximate Inference Methods, and Time
    • INF2D: Week 10: Rational Decision Making
      • INF2D: 28: Dynamic Bayesian Networks
      • INF2D: 29: Decision Making Under Uncertainty
      • INF2D: 30: Markov Decision Processes and AI Ethics
  • INF2D: Tutorial Exercises
  • Inf2D Labs
  • INF2D: Resource List
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