Abstract

The success of simulation environments will depend partly on how realistically the models mimic human behavior. While human behavior is affected by various moderators (see Pew and Mavor [28], for an initial list), cognitive models typically do not take into account the effects of many of these moderators. We propose that cognitive models can be augmented to account for such effects by modifying either their knowledge or the parameters of the architecture that they are built with. To provide an example of the two ways in which cognitive models can be modified to capture the effects of behavior moderators, we present an ACT-R model that performs a cognitive task while being affected by the moderators of as anxiety and pre-task appraisal. These changes are validated in a preliminary way by comparison with human data, which shows us where these models can be improved and provides lessons for further work. Most importantly, we argue that more realistic models of human behavior reflecting these moderators and individual differences can be achieved by implementing similar modifications within other cognitive models and by reusing these modifications for an existing architecture as an overlay.

Citations