I may use n-queens, checkers, chess, 8-puzzle (sliding block), rubic's cube, backgammon, tic-tac-toe as the context in any question on the exam. If you are not familiar with these, you may want to learn the basic idea of how they work.
All algorithms as described in the book
Space complexity, Time complexity. You should be able to derive and discuss these. I prefer you not just memorize them.
Optimality and Completeness. You should be able to prove and discuss these.
You should know how all of the following algorithms work. This includes being able to simulate there execution for a small problem, and discuss their optimality, completeness, space complexity and time complexity.
Depth, Breadth, Uniform cost, Iterative Deepening, Bi-directional
Greedy-best-first, A*, IDA*, Recursive Best-First Search, SMA*
Heuristics, Admissibility, Consistency, Making Heuristics
Tree vs. Graph search, Closed list.
On-line search
Search in a continuous space
Genetic Algorithms
Simulated Annealing
Particle swarm Optimization
Ply, Minimax, Terminal test, Evaluation functions, Cut-off, Quiescence search, Horizon problem, and Complexity
Min/Max search
$\alpha \beta$ pruning
$\alpha \beta$ pruning w/ random nodes no limits, that is -$\infty$ to $\infty$
$\alpha \beta$ pruning w/ random nodes and limits