Discussion
What does a factored representation allow that an atomic one does not?
Answer: D
Splitting a state into variables lets an algorithm notice that two states agree on most variables, which is what makes constraint propagation, Bayesian networks and planning heuristics possible. Objects and relations require the further step to structured representations. Memory efficiency is a side benefit and dynamism is unrelated. Each level of representation buys a class of inference that the level below cannot express, which is the reason the hierarchy is worth learning.
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