Affiliation:
1. Ohio State University, USA
Abstract
A synthesis of findings from neuroscience, psychology, and behavioral biology has been recently used to show that several key features of cognition in neuron-based brains of vertebrates are also present in bee-based swarms of honey bees. Here, simulation tests are administered to the honey bee swarm cognition system to study its decision-making performance. First, tests are used to evaluate the ability of the swarm to discriminate between choice options and avoid picking inferior “distractor” options. Second, a “Treisman feature search test” from psychology, and tests of irrationality developed for humans, are administered to show that the swarm possesses some features of human decision-making performance. Evolutionary adaptation of swarm decision making is studied by administering swarm choice tests when there are variations on the parameters of the swarm’s decision-making mechanisms. The key result is that in addition to trading off decision-making speed and accuracy, natural selection seems to have settled on parameters that result in individual bee-level assessment noise being effectively filtered out to not adversely affect swarm-level decision-making performance.
Subject
Artificial Intelligence,Computational Theory and Mathematics,Computer Science Applications
Cited by
5 articles.
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