The evolution of decision rules in complex environments.
Modelling Animal Decisions Group:; Fawcett, TW; Fallenstein, B; et al.Higginson, Andrew D.; Houston, AI; Mallpress, DE; Trimmer, PC; McNamara, JM
Date: 1 March 2014
Journal
Trends in Cognitive Sciences
Publisher
Elsevier
Publisher DOI
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Abstract
Models and experiments on adaptive decision-making typically consider highly simplified environments that bear little resemblance to the complex, heterogeneous world in which animals (including humans) have evolved. These studies reveal an array of so-called cognitive biases and puzzling features of behaviour that seem irrational in ...
Models and experiments on adaptive decision-making typically consider highly simplified environments that bear little resemblance to the complex, heterogeneous world in which animals (including humans) have evolved. These studies reveal an array of so-called cognitive biases and puzzling features of behaviour that seem irrational in the specific situation presented to the decision-maker. Here we review an emerging body of work that highlights spatiotemporal heterogeneity and autocorrelation as key properties of most real-world environments that may help us understand why these biases evolved. Ecologically rational decision rules adapted to such environments can lead to apparently maladaptive behaviour in artificial experimental settings. We encourage researchers to consider environments with greater complexity to understand better how evolution has shaped our cognitive systems.
Psychology - old structure
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