joshua abbott  

Computational Cognitive Science Lab
Department of Psychology
5429 Tolman Hall
University of California, Berkeley

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Random walks and Semantic memory
The human mind has a remarkable ability to store a vast amount of information in memory, and an even more remarkable ability to retrieve these experiences when needed. Understanding the representations and algorithms that underlie human memory search could potentially be useful in other information retrieval settings, including internet search. When people are asked to retrieve members of a category from memory, clusters of semantically related items tend to be retrieved together. A recent article by Hills, Jones and Todd (2012) argues that this pattern reflects a process similar to optimal strategies for foraging for food in patchy spatial environments, with people making a strategic decision to switch away from a cluster of related information as it becomes depleted. We demonstrate that similar behavioral phenomena also emerge from a random walk on a semantic network derived from human word association data. Random walks provide an alternative account of how people search their memory, postulating an undirected rather than a strategic search process. We show that results resembling optimal foraging are produced by random walks when related items are close together in the semantic network. These findings are reminiscent of arguments from the debate on mental imagery, showing how different processes can produce similar results when operating on different representations.

J.T. Abbott, J.L. Austerweil, and T.L. Griffiths. Human memory search as a random walk in a semantic network. Advances in Neural Information Processing Systems 25, 2012.
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J.T. Abbott, J.L. Austerweil, and T.L. Griffiths. Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122(3), 558-569. 2015.