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Task-independent metrics of computational hardness predict human cognitive performance.

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Franco, Juan Pablo 
Doroc, Karlo 
Yadav, Nitin 
Bossaerts, Peter 
Murawski, Carsten 


The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of cognitive tasks using a set of task-independent metrics related to the computational resource requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that they predict both time spent on a task as well as accuracy in three canonical cognitive tasks. Our findings demonstrate that performance in cognitive tasks can be predicted based on generic metrics of their inherent computational hardness.


Funder: University of Melbourne; doi:


Benchmarking, Cognition, Hardness, Humans, Task Performance and Analysis

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Springer Science and Business Media LLC