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Updated: Feb 18, 2026

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
Published on: August 2, 2018
Computational Complexity and Human Decision-Making
Peter Bossaerts1, Carsten Murawski2
1Brain, Mind & Markets Laboratory, Department of Finance, The University of Melbourne, Melbourne, VIC 3010, Australia; Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3010, Australia.
Abstract:
The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology.
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