Hills, Jones, and Todd (2012) observed that response patterns
during the semantic fluency task (e.g., “name all the animals
you can in a minute”) display statistical signatures of memory
search that mirror optimal foraging in physical space. They
proposed a model of memory search based on exploration-
exploitation tradeoffs known to produce optimal foraging
patterns when animals search for food resources, applied to a
spatial model of semantic memory. However, Abbott,
Austerweil, and Griffiths (2015) demonstrated that optimal
foraging behavior could also naturally emerge from a random
walk applied to a network representation of semantic memory,
without reliance on a foraging process. Since then, this has
been a very active are of debate in the literature, but core
confounds have prevented any clear conclusions between the
random walk and cue switching model. We control confounds
here by using a fixed training corpus and learning model to
create both spatial and network representations, and evaluate
the ability of the cue switching model and several variants of
the random walk model to produce the behavioral
characteristics seen in human data. Further, we use BIC to
quantitatively compare the models’ ability to fit the human
data, an obvious comparison that has never before been
undertaken. The results suggest a clear superiority of the Hills
et al. cue switching model. The mechanism used to search
memory in the fluency task is likely to have been exapted from
mechanisms evolved for foraging in spatial environments.