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Table of Contents
General probability stuff is assumed, like , finding marginals, conditionals, etc.
Bayesian Nets
- Bayes law in general
- Computing the joint for a BN
- Using the joint to compute arbitrary probabilities and arbitrary conditional probabilities
- Kalman Model
- Make sure you understand the inputs and outputs and what it does in general
- You do NOT need to memorize the formula
Utility
- Axioms of Utility in general, but you do not have to memorize them
- Computing the Expected Utility
- Risk averseness in general and what does it means in a practical sense when working with Lotteries (including as in the homework)
- Be able to do EVSI, like in the Homework
Complex Decision Making
- Value Iteration
- Policy Iteration
- Modified Policy Iteration
- Q-learning will NOT be on the test
