Topic 11d
Uninformed Search (Reinforcement Learning)

Learning Outcomes

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

• Briefly explain the process used with [hill climbing | genetic algorithms].
  • Given a scenario to solve a problem, identify if it is using hill climbing or genetic algorithms.
• Identify how [hill climbing | genetic algorithms] is an example of reinforcement learning.

Learning Materials

• Readings
• Hill Climbing
  • 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
  • The website we use in that demo
  • www.cs.uni.edu//~schafer/cohort23/FCCS/lessons/CH11/T11d/sampleData/buzz.png
• Dr. Schafer explains Genetic Algorithms
• How a "researcher" used hill climbing and simulated annealing to discover the optimal layout for a computer keyboard.
• Why typing sucks
• Dr. Schafer talks about training auto-complete
  • This doesn't 100% fit in with today's topics, but it is another good example of learning.

 

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

Answers & Guidance

The answers to the CFU questions above are provided in the back of the book. We do not feel that additional video explanations are helpful for these questions. However, if you are still confused or have additional questions, please feel free to reach out to us.