Monday, 4 February 2013

Artificial Intelligence : A Modern Approach




TopicMaterials
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
TopicSlides
search & planningsearch.ppt

graph-search demo
game playinggames_and_pp.ppt
from propositional logic to Prologlogic-to-prolog.ppt

Online Prolog tutuorial: http://www.amzi.com/
AdventureInProlog/
natural language processingnlp-all.pdf
introduction to probabilistic reasoning(see slides below)
algorithms for probabilistic reasoningrevised & updated set of slides on probablistic reasoning:
revised-rn-bayes-all.pdf
robotics & probabilistic reasoning over timeProbabilistic Reasoning Over Time- includes description of particle filtering algorithm

rn-ch15-abbrev.pdf- slides for R&N Chapter 15
rule learningDecision Trees
neural networks & Bayesian learningNeural Nets

Bayesian Learning
local search genetic algorithmslocal search





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