Topic | Materials |
Introduction. | Chapter 1. Introduction slides: ppt, pdf. |
Search. Constraint satisfaction and optimization problems. | Chapters 3, 4, 5. Search slides: ppt, pdf. More search slides: ppt, pdf. |
Game playing. | Chapter 6. Slides: ppt, pdf. |
Logic. | Chapters 7, 8, 9. Propositional logic slides: ppt, pdf. First-order logic slides: ppt, pdf. |
Planning. | Planning slides: ppt, pdf. Chapter 11. |
Probabilistic reasoning. | Chapters 13-17. Probability slides: ppt, pdf. Bayes nets slides: ppt, pdf. Markov processes and HMMs slides: ppt, pdf. |
Decision theory. Markov decision processes, POMDPs. Game theory. | Chapters 18, 19, 20. Decision theory slides: ppt, pdf. MDP/POMDP slides: ppt, pdf. Game theory slides: ppt, pdf. |
Machine learning. | Machine learning slides: ppt, pdf. |
Wrapping up. | Wrapping up slides: ppt, pdf. |
Introduction to Artificial Intelligence
Instructor: Henry Kautz
Textbook: Artificial Intelligence: A Modern Approach (3rd Edition), Stuart Russell & Peter Norvig
Download Slides from here
Topic | Slides |
search & planning | search.ppt graph-search demo |
game playing | games_and_pp.ppt |
from propositional logic to Prolog | logic-to-prolog.ppt Online Prolog tutuorial: http://www.amzi.com/ AdventureInProlog/ |
natural language processing | nlp-all.pdf |
introduction to probabilistic reasoning | (see slides below) |
algorithms for probabilistic reasoning | revised & updated set of slides on probablistic reasoning: revised-rn-bayes-all.pdf |
robotics & probabilistic reasoning over time | Probabilistic Reasoning Over Time- includes description of particle filtering algorithm rn-ch15-abbrev.pdf- slides for R&N Chapter 15 |
rule learning | Decision Trees |
neural networks & Bayesian learning | Neural Nets Bayesian Learning |
local search genetic algorithms | local search |
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