Monte Carlo is a way to evaluate according to simulations. Simulating is a
way to probe a problem space in a way that renders the task somehow more
tractable, when the computational power allows it. With Scrabble and
Backgammon, simulating provides players that have World Championship
strenght in astonishingly low thinking time.
For what I can guess, simulating evaluations for chess could help the engine
find moves according the most frequent developments. So that may be a way
to find an evaluation that we may consider "natural". Natural for a
position being the propensity to converge towards some result, when we
abstract away any rational process to find the best move.
That seems to be an interesting way to select a move in situations when
there is not anyone that is clearly better than the rest.
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