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| Topic | Russell and Norvig 4th edition |
Russell and Norvig 3rd edition |
Other |
|---|---|---|---|
| Intro | Ch 1, Ch 2 | Ch 1, Ch 2 | |
| Probability and Naive Bayes | Ch 12 | Ch 13 | |
| Search | 3.1-3.6 | 3.1-3.6 | |
| Robot Motion | 26.1-26.6 | 25.1-25.5 | |
| Bayes Nets | Ch 13 | Ch 14.1, 14.2, 14.4 | Charniak Bayes Nets |
| Natural Language | Ch 23 | Ch 23 | |
| Hidden Markov Models Computer Vision |
14.1-14.3 | 15.1-15.3 |
HMMs from Jurafsky and Martin
(8.1-8.4)
Forsyth Prob/Stats (chapter 14) |
| Computer Vision | Ch 25 | Ch 24 | |
| Classification | 19.1-19.4 | 18.1-18.4 | Forsyth AML 1.2 and 2.2 |
| Linear Classifiers | 19.6 | 18.6 | Jurafsky and Martin ch 5 |
| Neural Nets | Ch. 21 | 18.7 | Jurafsky and Martin
ch 7,
ch 9, Goldberg ch. 4-5, 13.15 Karpathy notes Forsyth AML (Chapter 16) |
| Reinforcement Learning | 17.1-17.2 | 17.1-17.3 | |
| Game Search | 5.1-5.6 | 5.1-5.6 | |
| Constraint Satisfaction | Ch 6, 4.1 | Ch 6, 4.1 | |
| Classical Planning | 11.1-11.3 | Ch 10 | Poole/Mackworth Ch 6 |
| Vector semantics | Ch 24 | Jurafsky and Martin ch 6 |