As part of your review
process, I recommend you study:
- Notes from class
- Reread book chapters
- Homework and programming assignments
- Look over exercises at the end of the chapter in the book.
Chapter One: Introduction, Focus on Section 1.1
- Formulate a reasonable working definition of AI
- Know the four categories of definitions of AI found in figure 1.1
and be able to discuss the pros and cons of these categories.
- Be able to explain and discuss the Turing Test
Chapter Two: Intelligent Agents, Focus on Sections 2.1-3
- Be able to define a rational agent
- What four things does a rational agent depend on?
- Understand and identify the sensors, actuators, percepts, and the
percept sequence of an agent
- Be able to discuss good agent behavior and performance measures
- Be able to provide a PEAS description of an agent's task
environment
- Be able to discuss and identify the properties of a task
environment (pages 41, 42)
Chapter Three: Solving Problems by Searching, Focus on Sections 3.1-5
- Be able to define and identify the components of a problem
(states, initial state, successor function, goal test, path cost)
- Understand the general tree-search algorithm and the role of the
fringe
- Understand and be able to use the four ways we measure
problem-solving performance
- Describe the behavior of depth-first, breadth-first, iterative
deepening and uniform-cost search, and compare their relative
advantages and disadvantages
Chapter Four: Informed Search and Exploration, Focus on 4.1-3
- How does “informed search” try to improve on “uninformed search”?
- Be able to discuss the role of the evaluation function in
informed search
- Describe the behavior of greedy best-first search
- Explain how A* search works, what its advantages are, and
identify any restrictions on heuristics which can be used with it
- Discuss strategies for inventing admissible heuristic functions
- Understand the state space landscape and how it impacts local
search algorithms
- Describe the ways hill climbing can be modified to avoid some of
the issues that come up in the landscape
- Describe the behavior of hill climbing, simulated annealing,
local beam, and genetic algorithms search, and compare their relative
advantages and disadvantages