Random walkers with extreme value memory: modelling the peak-end rule

Abstract

Motivated by the psychological literature on the "peak-end rule" for remembered experience, we perform an analysis within a random walk framework of a discrete choice model where agents' future choices depend on the peak memory of their past experiences. In particular, we use this approach to investigate whether increased noise/disruption always leads to more switching between decisions. Here extreme value theory illuminates different classes of dynamics indicating that the long-time behaviour is dependent on the scale used for reflection; this could have implications, for example, in questionnaire design.

22 pages, 12 figures, v2 essentially identical to published version at http://stacks.iop.org/1367-2630/17/053049

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