INF2D: Week 10: Rational Decision Making
Welcome to the final week of lectures for Inf2D!
Having studied how to reason about your beliefs in the face of uncertainty, both in a static environment (BNs) and in a dynamic one (DBNs or the special case, HMMs), we are finally in a position to merge those probabilistic inferences with a numeric representation of preferences to show how an agent can make rational decisions: recall the principle of Maximising Expected Utility, which captures an optimal trade off between what the agent prefers and what it thinks it can achieve.
28: Decision Making under Uncertainty
29: Markov Decision Processes
30: Revision Lecture
As always, these lectures will be delivered in person and live streamed. If there is anything you don't understand, then you have several options:
- Post a question on piazza;
- Ask a question at the in-person lecture; and/or
- Ask your tutor.
Good luck with your assignments and your exam, and I very much hope you will continue to pursue further AI courses on your degree programme next year.