Hi all,

Lecture 3: Optimization is now available on the course website. In this part of the course, we explore how AI can search for solutions that optimize for some goal — minimizing cost, maximizing rewards or benefits, or satisfying some constraints as best as possible, for example. In doing so, we'll explore three different approaches used in AI: local search, linear programming, and constraint satisfaction algorithms.

A few other important announcements for this week:

Quiz 3 is now available and is due by 11:59pm ET on Wed 7/15. As a reminder, each quiz is open-book: you may use any and all non-human resources during a quiz, but the only humans to whom you may turn for help or from whom you may receive help are the course’s heads. And remember to submit your quiz via Gradescope as well!
Project 3 is now available as well and is due by 11:59pm ET on Sun 7/19. This week, you'll build an AI to generate crossword puzzles using constraint satisfaction techniques.
Sections this week will be an opportunity to talk more about these optimization problems, see additional examples of lecture material, and ask questions about this week's concepts. You're encouraged to attend if you can!

As always, feel free to reach out to me or any of the course staff with any questions!

All the best,
Brian