Abstract
Abstract Previous research has developed a formal methods-based (cognitive-level) model of the Interacting Cognitive Subsystems central engine, with which we have simulated attentional capture in the context of Barnard’s key-distractor Attentional Blink task. This model captures core aspects of the allocation of human attention over time and as such should be applicable across a range of practical settings when human attentional limitations come into play. In addition, this model simulates human electrophysiological data, such as electroencephalogram recordings, which can be compared to real electrophysiological data recorded from human participants. We have used this model to evaluate the performance trade-offs that would arise from varying key parameters and applying either a constructive or a reactive approach to improving interactive systems in a stimulus rich environment. A strength of formal methods is that they are abstract and the resulting specifications of the operator are general purpose, ensuring that our findings are broadly applicable. Thus, we argue that new modelling techniques from computer science can also be employed in computational modelling of the mind. These would complement existing techniques, being specifically targeted at psychological level modelling, in which it is advantageous to directly represent the distribution of control.
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