  We study correlations between the structure and properties of a free
association network of the English language, and solutions of psycholinguistic
Remote Association Tests (RATs). We show that average hardness of individual
RATs is largely determined by relative positions of test words (stimuli and
response) on the free association network. We argue that the solution of RATs
can be interpreted as a first passage search problem on a network whose
vertices are words and links are associations between words. We propose
different heuristic search algorithms and demonstrate that in "easily-solving"
RATs (those that are solved in 15 seconds by more than 64\% subjects) the
solution is governed by "strong" network links (i.e. strong associations)
directly connecting stimuli and response, and thus the efficient strategy
consist in activating such strong links. In turn, the most efficient mechanism
of solving medium and hard RATs consists of preferentially following sequence
of "moderately weak" associations.
