Abstract
The systems with which humans interact are becoming increasingly complex; there is a corresponding need for such systems to anticipate and understand human action. Current approaches to develop this ability do not robustly represent human users to the systems with which they are interacting. Fusing neurocognitive models with existing approaches may provide an effective way to capture and represent neural action in a way that behaviors can be predicted and shared with the systems that humans are operating.
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