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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.
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.
* [[AI class overview]] for an overview
* [[AI class journal]] for my journal


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


= Week 1 =
= Welcome =


== Welcome to AI ==
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.


=== Introduction ===
= Documentation =


{{#ev:youtubehd|BnIJ7Ba5Sr4}}
* [[AI class prerequisites]] for prerequisites
 
* [[AI class readings]] for the readings
Will deliver a good introduction to AI. Going to be a lot of work, but very rewarding.
* [[AI class overview]] for an overview
 
* [[AI class journal]] for my journal
New videos every week, and quizzes to test your knowledge built into the videos.
* [[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.
 
If you finish the course the lecturers will sign a letter of accomplishment and let you know what your rank in the class was.
 
=== Course Overview ===
 
{{#ev:youtubehd|Q7_GQq7cDyM}}
 
Purpose of the class:
 
* To teach the basics of AI artificial intelligence
* To excite you
 
Structure:
 
* Videos -> Quizzes -> Answer Videos
* Assignments (like quizzes but without the answers) and exams
 
=== Intelligent Agents ===
 
{{#ev:youtubehd|cx3lV07w-XE}}
 
The agent has sensors that measure the environment, and actuators that can affect the environment.
 
The function that maps sensors to actuators is called the Control Policy of the agent.
 
This is the Perception-Action cycle:
 
[[File:AI class 2011-10-15-191700.PNG]]
 
=== Applications of AI ===
 
{{#ev:youtubehd|N6JW8TQzbX8}}
 
[[File:AI class 2011-10-15-193200.PNG]]
 
[[File:AI class 2011-10-15-192600.PNG]]
 
[[File:AI class 2011-10-15-192800.PNG]]
 
[[File:AI class 2011-10-15-201000.PNG]]
 
[[File:AI class 2011-10-15-201200.PNG]]
 
[[File:AI class 2011-10-15-201500.PNG]]
 
=== Terminology ===
 
{{#ev:youtubehd|5lcLmhsmBnQ}}
 
[[File:AI class 2011-10-15-203000.PNG]]
 
[[File:AI class 2011-10-15-202600.PNG]]
 
=== Checkers ===
 
{{#ev:youtubehd|qVppDRbx2kM}}
 
[[File:AI class 2011-10-15-212700.PNG]]
 
=== Poker Question ===
 
{{#ev:youtubehd|M_AdFAazf4k}}
 
{{#ev:youtubehd|DjILhASM3A8}}
 
=== Robot Car Question ===
 
{{#ev:youtubehd|vz-ERydsKLU}}
 
{{#ev:youtubehd|nOWCfVG0xNQ}}
 
[[File:AI class 2011-10-18-093400.PNG]]
 
=== AI and Uncertainty ===
 
{{#ev:youtubehd|ytw6_8a5Wls}}
 
[[File:AI class 2011-10-17-001100.PNG]]
 
=== Machine Translation ===
 
{{#ev:youtubehd|sPSN0aI0PgE}}
 
[[File:AI class 2011-10-18-094200.PNG]]
 
[[File:AI class 2011-10-18-094400.PNG]]
 
=== Chinese Translation ===
 
{{#ev:youtubehd|RWhwKudtixY}}
 
{{#ev:youtubehd|vvyaXxjsxBU}}
 
{{#ev:youtubehd|lFJey0tOvBg}}
 
=== Summary ===
 
{{#ev:youtubehd|mXM38kjzK-M}}
 
[[File:AI class 2011-10-19-023500.PNG]]
 
== Problem Solving ==
 
=== Introduction ===


{{#ev:youtubehd|ZQmJuHtpGfs}}
= Resources =


In this unit we talk about problem solving. The theory and technology of building agents that can plan ahead to solve problems. In particular we're talking about problem solving where the complexity of the problem comes from the idea that there are many states, as in this problem here:
* [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]


[[File:AI class 2011-10-19-024500.PNG]]
= Lecture notes =


A navigation problem where there's many choices to start with and the complexity comes from picking the right choice now and picking the right choice at the next intersection and the intersection after that. Stringing together a sequence of actions.
* 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]]


This is in contrast to the type of complexity shown in this picture:
= Office hours =


[[File:AI class 2011-10-19-024501.PNG]]
* [http://www.youtube.com/watch?v=pIfrmdM0Ht0 Office hours 1]
* [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]


Where the complexity comes from the partial observability, that we can't see through the fog where the possible paths are or we can't see the results of our actions or even the actions themselves are not known. This type of complexity will be covered in another unit.
= Discussion =


Here's an example of a problem:
* [http://www.aiqus.com/questions/5378/practicing-probability-calculations Practising probability calculations]
* [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]


[[File:AI class 2011-10-19-025600.PNG]]
= Other people's notes =


This is a route finding problem. Where we are given start city Arad and a destination city Bucharest (the capital of Romania) and the problem then is to find a route from Arad to Bucharest. The actions that the agent can execute are driving from one city to the next along one of the roads shown on the map. The question is, is there a solution that the agent can come up with given the knowledge shown here to the problem of driving from Arad to Bucharest?
* [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]


=== What is a Problem? ===
= Practice questions =


{{#ev:youtubehd|SIHc9LgMeaU}}
* [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]

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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