@inproceedings{Wor2013,
Author = {Wortelen, Bertram and Lüdtke, Andreas and Baumann, Martin},
Title = {Simulating Attention Distribution of a Driver Model: How to Relate Expectancy and Task Value?},

Year = {2013},
Month = {07},
Editor = {Robert West, Terry Stewart},
Booktitle = {Proceedings of the 12th International Conference on Cognitive Modeling},
Url = {http://iccm-conference.org/2013-proceedings/172/index.html},
type = {inproceedings},
note = {This work discusses two distinct formulations of a simulation model for human attention allocation. The purpose of the Adaptive Information Expectancy (AIE) model is to work as an integral part of a cognitive architecture in order to allow accurate simula},
Abstract = {This work discusses two distinct formulations of a simulation model for human attention allocation. The purpose of the Adaptive Information Expectancy (AIE) model is to work as an integral part of a cognitive architecture in order to allow accurate simulations of the attention distribution for various cognitive models. The distribution of attention is calculated based on the two influencing factors event expectancy and task value. In related work these factors have been either related by addition or by multiplication. In the current paper both alternatives have been used to simulate a cognitive driver model. Better model fits to human drivers were observed for the additive variant. However, a closer look at the data does not necessarily argue against the multiplicative variant.}
}
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