Week 06:
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Topic: Adversarial Search

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Objectives:

• Describe how search is used to solve problems in artificial intelligence
• Describe and use uninformed and informed search algorithms and optimizations

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1. Watch the following Case Study:
   • The Story of A* and STRIPS by Nils Nilsson (6 min 22 sec).
   
   Reference: Coursera's Artificial Intelligence Planning by Gerhard Wickler and Austin Tate
   
   
2. Complete the "13. Games" unit (Required) and "14. Game Theory" unit (Optional) in the Introduction to Artificial Intelligence course from Udacity:
   1. Sign In to Udacity
   2. Select Introduction to Artificial Intelligence from the Course Catalog
   3. Press the "Take the Class" button
   4. (Required) Watch the videos and take the quizzes in the "13. Games" unit.
   5. (Optional) Watch the videos and take the quizzes in the "14. Game Theory" unit.
   
   Alternatively, download the following ZIP file containing Flash Video files:
   • 13. Games
   • 14. Game Theory
   
   
3. Complete "Lecture 6: Adversarial Search" and "Step By Step: Alpha-Beta" in "Week 4" in the CS188.1x: Artificial Intelligence course from edX:
   1. Log in to edX.
   2. Click the Find Courses link at the top of the page.
   3. In the "all schools" drop down, select "UC BerkeleyX"
   4. At the bottom of the page, click "see more courses" link.
   5. Near the bottom of the page, click the "register for CS188.1X" button to the right of the CS188.1x: Artificial Intelligence course with the following details: Starts: 24 Sep 2012 • Instructors: Dan Klein • UC BerkeleyX
      Note: Only select the "CS188.1x: Artificial Intelligence" course that started on 24 SEP 2012. The videos in the other "CS188.1x: Artificial Intelligence" course are not yet accessible.
      
   6. Click the "View Archived Course" button.
   7. Click the "Courseware" button at the top.
   8. Under "Week 4", watch the following lectures and read through quizzes and any available answers:
      • Lecture 6: Adversarial Search
      • Step By Step: Alpha-Beta
      Warning: Make sure you stop the current video before selecting a new video ... or both videos will play at the same time.
      Warning: Quizzes may not function. Answers may not be given for all quizzes.
      
   
   Reference: edX's CS188.1x Artificial Intelligence course from BerkeleyX by Dan Klein.
   
   
4. Using the following texts:
   • Artificial Intelligence: A Modern Approach, Third Edition (cited as AIMA)
   • A Few Useful Things to Know about Machine Learning by Pedro Domingos from Communications of the ACM, 55 (10), 78-87, 2012. (cited as DOMINGOS)
   
   Read the following pages:
   • Required: 39 Pages

     Order	Topic	Book	Section	Page Numbers	Pages	Presentations
     1.	Adversarial Search	AIMA	Chapter 5:	Pages 161-190	(30 Pages)	Informed Search Algorithms, Game Playing, and Search: deterministic state space models
     2.	A Few Useful Things to Know about Machine Learning	DOMINGOS	Communications of the ACM, 55 (10), 2012:	Pages 78-87	(9 Pages)

     
     
   Reference: University of California, Berkeley's CS 188: Introduction to Artificial Intelligence (Fall 2005) by Stuart Russell
   Reference: Stanford University's CS221: Artificial Intelligence: Principles and Techniques (Autumn 2012-2013) by Percy Liang
   
   
5. Do Assignment 05.