Optimal Foraging in Semantic Memory


When searching for items in memory, people explore internal representations in much the same way that animals forage in space. Results from a number of fields support this notion at a deeper level of evolutionary homology, with evidence that goal-directed cognition is an evolutionary descendent of animal foraging behavior (Hills, 2006). Is it possible then that humans forage in memory using similar search policies to the way that animals forage in space? To investigate this, we examine how people retrieve items from memory in the category fluency task: Participants were asked to retrieve as many types of animals from memory as they could in 3 minutes. Clusters or patches of these items, along with their semantic similarity and frequency, were found with an automatic Wikipedia corpus analysis using the BEAGLE semantic memory model (Jones & Mewhort, 2007), and via hand-coded category membership from Troyer et al. (1997). Participants did not seem to use static patch boundaries, such as ‘pets’, to search memory, but instead used fluid patch boundaries that were updated with each new item retrieved. We found that participants leave patches in memory when the marginal (i.e., current) rate of finding items is near the average rate for the entire task, as predicted by optimal foraging theory. Furthermore, participants appear to search within patches using item similarity, but decide where to “land” when moving between patches using item frequency.

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