The course is not covering all the chapters in the AIMA text, nor all the material in each of the assigned chapters. Each mention of a chapter reading in the Schedule links to an item below that gives the details of what to read (and what to skip). Be sure to read the short Summary section at the end of each assigned chapter.
Chapter 1 - Entire chapter. There may well be a quiz question asking you to describe the most interesting material that you found in the chapter. Note the birthplace of AI, in 1956.
Chapter 2 - Entire chapter. The agent view of AI is repeated throughout the book, so pay attention to it. Study the vacuum-cleaner world discussion carefully. It will be on a quiz. Note that the PEAS formulation is for a task, not for the means that an agent uses to deal with a task. The problem solving aspects start in Chapter 3.
Chapter 3 - Entire chapter. The searching strategies in this chapter are "uninformed", not "informed". The distinction will become clear in Chapter 4. Many important problems are known to be NP-hard and therefore demand search-based solution methods. See Appendix A, section A.1 for a discussion of NP-hard and related complexity concepts.
Chapter 4 - Read through the top of page 101. Then read section 4.2 through Figure 4.8. Then, section 4.3 through page 113. Read the section "Simulated annealing search" on page 115 - I'll do a live physical demo in class.
Chapter 5 - Read to the bottom of page 146. Focus on the map coloring constraint example, including figures 5.4 and 5.5. Map coloring will be included in a quiz. (There are no readings in chapter 6. But if you want to do a game-related project - nothing even similar to board games please! - you'll need to study chapter 6 in detail.)
Chapters 7, 8, and 9, require close study and re-reading:
Chapter 7 - Read to the bottom of page 217. Study figure 7.5 until you understand the point it's making. Pay special attention to the Resolution concept starting on page 213, as well as the example of resolution shown in figure 7.13.
Chapter 8 - Again, not easy material, as in chapter 7. Read through page 255.
Chapter 9 - Read through page 276, including figure 9.4. THen pages 280-282. Then section 9.4 to the top of page 289. Then section 9.5 to the bottom of page 299, especially figures 9.11 and 9.12.
Chapter 13 - This introduces probability as it is used in AI. Read through page 482.
Chapter 14 - Read pages 492-495. Skim sections 14.4 and 14.5.
Chapter 16 - Through page 593. Study figure 16.5 and the discussion below it on page 598.
Chapter 18 - Read sections 18.1, 18.2, and 18.3. I will discuss section 18.4 in class.
Chapter 22 - Read through figure 22.6 at the top of page 801.
Chapter 24 - Entire chapter, but don't be very concerned with all the mathematics included.
Chapter 25 - Entire chapter, and again, don't be very concerned with the mathematics.