Exploring the Complexity of Human Decision-Making and Cognition

Published on June 16, 2023

Imagine navigating a maze with limited mental resources. Computational complexity theory offers a key to understanding how humans tackle complex environments. Much like solving a challenging puzzle, our brains have limited capacity to process vast amounts of information. By adopting this theoretical framework, we can unravel the underlying factors that drive our cognitive demands. This approach promises fresh insights into the workings of our cognitive systems and the intricate relationship between task complexity and human behavior. The research presented in this article supports the potential of computational complexity theory in shedding light on human decision-making and cognitive science as a whole. To fully harness its power, however, we must explore open research questions and overcome challenges in applying this theory to real-world scenarios.

Abstract
A central aim of cognitive science is to understand the fundamental mechanisms that enable humans to navigate and make sense of complex environments. In this letter, we argue that computational complexity theory, a foundational framework for evaluating computational resource requirements, holds significant potential in addressing this challenge. As humans possess limited cognitive resources for processing vast amounts of information, understanding how humans perform complex cognitive tasks requires comprehending the underlying factors that drive information processing demands. Computational complexity theory provides a comprehensive theoretical framework to achieve this goal. By adopting this framework, we can gain new insights into how cognitive systems work and develop a more nuanced understanding of the relation between task complexity and human behavior. We provide empirical evidence supporting our argument and identify several open research questions and challenges in applying computational complexity theory to human decision-making and cognitive science at large.

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