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These are my notes from [http://robots.stanford.edu/ Sebastian Thrun] and [http://norvig.com/ Peter Norvig]'s [http://ai-class.org/ AI class]. A course on Artificial Intelligence. See [[AI class overview]] for an overview. I'm keeping a journal in [[AI class journal]].
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= Week 1 =
These are my notes from [http://robots.stanford.edu/ Sebastian Thrun] and [http://norvig.com/ Peter Norvig]'s [http://ai-class.org/ AI class]. A course on Artificial Intelligence.


== Welcome to AI ==
Course undertaken October to December 2011. Here goes nothing. :P


=== Introduction ===
= Welcome =


{{#ev:youtubehd|BnIJ7Ba5Sr4}}
Hi there. My on-going involvement in this class is sketchy at best. I have a whole heap of other things that I'm meant to be doing, and having done half the class I'm not sure that it's the right thing for me. Anyway, I've really enjoyed doing what I've done so far and if there's something here that's useful to you that's great. But I'm not sure that I'm going to be finishing my work here. Sorry.


Will deliver a good introduction to AI. Going to be a lot of work, but very rewarding.
= Documentation =


New videos every week, and quizzes to test your knowledge built into the videos.
* [[AI class prerequisites]] for prerequisites
* [[AI class readings]] for the readings
* [[AI class overview]] for an overview
* [[AI class journal]] for my journal
* [[AI class errata]] for my notes on mistakes I've found in the coursework


For the advanced version of the course are homework assignments and exams. These will be graded to determine if you can master AI the same way any good Stanford student could do it.
= Resources =


If you finish the course the lecturers will sign a letter of accomplishment and let you know what your rank in the class was.
* [https://www.ai-class.com/home/ Course web-site]
* [https://www.ai-class.com/sforum/ Course forum]
** [http://www.reddit.com/r/aiclass Reddit forum]
** [http://www.aiqus.com/ Aiqus forum]
*** [http://www.aiqus.com/users/1817/peter-norvig Peter Norvig on Aiqus]
* [https://www.ai-class.com/registration/progress Course progress]
* [https://www.ai-class.com/overview Course information]
** [https://www.ai-class.com/faq Course FAQ]
** [https://www.ai-class.com/resources Course related material]
** [https://www.ai-class.com/schedule Course schedule]
* [http://mike.thedt.net/ytsubs/ytsubs.php YouTube closed-captions ripper]


=== Course Overview ===
= Lecture notes =


{{#ev:youtubehd|Q7_GQq7cDyM}}
* Week 1
** [[AI class unit 1|Welcome to AI]]
** [[AI class unit 2|Problem Solving]]
** [[AI class homework 1|Homework 1]]
* Week 2
** [[AI class unit 3|Probability in AI]]
** [[AI class unit 4|Probabilistic Inference]]
** [[AI class homework 2|Homework 2]]
* Week 3
** [[AI class unit 5|Machine Learning]]
** [[AI class unit 6|Unsupervised Learning]]
** [[AI class homework 3|Homework 3]]
* Week 4
** [[AI class unit 7|Representation with Logic]]
** [[AI class unit 8|Planning]]
** [[AI class homework 4|Homework 4]]
* Week 5
** [[AI class unit 9|Planning under Uncertainty]]
** [[AI class unit 10|Reinforcement Learning]]
** [[AI class homework 5|Homework 5]]


Purpose of the class:
= Office hours =


* To teach the basics of AI artificial intelligence
* [http://www.youtube.com/watch?v=pIfrmdM0Ht0 Office hours 1]
* To excite you
* [http://www.youtube.com/watch?v=ajMKay1LMRw Office hours 2]
* [http://www.youtube.com/watch?v=iL0fFmNWb0A Office Hours for Week 5]
* [http://www.youtube.com/watch?v=7cPOkxHtxJ8 Office Hours for Week 6]
* Office hours for Week 7: [http://www.youtube.com/watch?v=XF_ACsJiz64 part 1] and [http://www.youtube.com/watch?v=Y6LF-_-pMgI part 2]


Structure:
= Discussion =


* Videos -> Quizzes -> Answer Videos
* [http://www.aiqus.com/questions/5378/practicing-probability-calculations Practising probability calculations]
* Assignments (like quizzes but without the answers) and exams
* [http://www.aiqus.com/questions/4152/thinking-about-giving-up-the-course Norvig defines conditional probability in terms of unconditional probability]
* [http://www.aiqus.com/questions/4183/probability-cheatsheet-for-ai-class Probability cheatsheet for AI]


=== Intelligent Agents ===
= Other people's notes =


The agent has sensors that measure the environment, and actuators that can affect the environment.
* [https://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0B0JaMwvGlHuEYTE1MWI5NzgtZTViMC00YmNlLWI5ZjktZjg0YWM1MTcxYzAy&hl=en_US Conditional Independence Write-Up]
** [https://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0B0JaMwvGlHuEOWM3MTliYTgtODZjNi00NGY3LTkzNTAtYWYyMDUzM2JlMTE1&hl=en_US Independence does not imply conditional independence...]
* [https://www.evernote.com/shard/s1/sh/333fb301-8d12-4927-87ec-c81cdd42b7d2/240bbab26642f5d49d32c38053e905f6 Unit 5 on evernote]
* [http://wiki.geekdownunder.net/index.php?title=Main_Page GeekDownUnder]
** [http://www.khanacademy.org Khan Academy]: free online video lectures on a variety of topics
** [http://openclassroom.stanford.edu/MainFolder/VideoPage.php?course=MachineLearning&video=01.5-Introduction-InstallingOctave&speed=100 Installing Octave]: video tutor about installing Octave
** [http://www.gnu.org/software/octave/doc/interpreter/ Octave Documentation]: documentation of Octave
** [http://guioctave.com/ Gui Octave]: graphical User Interface for Octave
** [http://thedatahub.org/ The Data Hub]: a registry of open knowledge datasets and projects
* [http://larvecode.tumblr.com/tagged/ai-class LarveCode]


The function that maps sensors to actuators is called the Control Policy of the agent.
= Practice questions =


This is the Perception-Action cycle:
* [http://www.maths.uq.edu.au/courses/MATH3104/Lectures/goodhill/bayes_solutions.pdf MATH 3104: Practice with Bayes theorem]
 
* [http://www.intmath.com/counting-probability/10-bayes-theorem.php 10. Bayes' Theorem]
[[File:AI class 2011-10-15-191700.PNG]]
 
=== Applications of AI ===
 
[[File:AI class 2011-10-15-193200.PNG]]
 
[[File:AI class 2011-10-15-192600.PNG]]
 
[[File:AI class 2011-10-15-192800.PNG]]

Latest revision as of 15:54, 10 November 2013

These are my notes from Sebastian Thrun and Peter Norvig's AI class. A course on Artificial Intelligence.

Course undertaken October to December 2011. Here goes nothing. :P

Welcome

Hi there. My on-going involvement in this class is sketchy at best. I have a whole heap of other things that I'm meant to be doing, and having done half the class I'm not sure that it's the right thing for me. Anyway, I've really enjoyed doing what I've done so far and if there's something here that's useful to you that's great. But I'm not sure that I'm going to be finishing my work here. Sorry.

Documentation

Resources

Lecture notes

Office hours

Discussion

Other people's notes

Practice questions

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