Topic 11d
Uninformed Search (Reinforcement Learning)

Learning Outcomes

By the end of this topic students should be able to:

• Explain the process used with [hill climbing | genetic algorithms].
• Explain how [hill climbing | genetic algorithms] is an example of reinforcement learning.

Learning Materials

• Readings
• Hill Climbing
  • This is a solid explanation, although a bit mathy.
  • This is a good but brief start (stop when you get to the section labeled "Case Study")
• Genetic Algorithms - pp 591-592
• Videos
• Dr. Schafer explains Hill Climbing
• Dr. Schafer demos Hill Climbing in action
  • NOTE:
    • This video is being misplayed by the server. The edit I have in the master program is RIGHT, but the edit being played by the Panopto server is wrong - it is swapping segments 1 and 2.
    • I am trying to troubleshoot and fix this, but, in the mean time, please note that the segments SHOULD be played
      • Opening slides - first 8 seconds
      • Segment 1 - for some reason is from 1:28-7:32
      • Segment 2 - for some reason is from 0:08-1:28
      • Segment 3 - for some reason is from 7:32-end
  • The website I use in that demo
  • www.cs.uni.edu//~schafer/cohort23/FCCS/lessons/CH11/T11d/sampleData/buzz.png
• Dr. Schafer explains Genetic Algorithms

 

Checking for Understanding

Answer the following questions from your textbook. The answers to all Q&E questions are in the back of your book in Appendix F.

• p 592, #5

Additional Guidance

• NA

Further Information

• NA