mtreview.txt

+ Know complexities of search algos.
+ Iterative deepening reduces memory cost
+ Reflex agent simply maps states to actions
+ Solutions transforms start state to goal state
+ Put all key algos. in cheat sheet
+ CSPs use tree search because duplicate states will never arise
	because we branch on one variable at each state
+ MRV is fail fast
+ Once we choose a variable to assign, choose the least constraining value
	more likely to succeed than others
+ For each value in the tail, is the value at head consistent with tail value?
	if not, cross it out
+ Arc consistency is for detecting failure earlier
+ Solution to a game is a strategy:
	for every possible state, what is the best move to make?
+ With finite horizons in MDP, optimal action in a certain state could depend on time
	not true with infinite horizons
+ RL: T, R, unknown
+ Exponential moving average biases recent samples
+ Learning rate?
+ Know probability
+ Variable elimination not on MT
+ Know representation of Bayes Nets