The University of Sheffield
BeesResponses_HistoryOfReinforcementLearning.xlsx (54.76 kB)

Data for 'Honeybees solve a multi-comparison ranking task by probability matching'

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posted on 2020-09-01, 20:18 authored by HaDi MaBouDi, James MarshallJames Marshall, Andrew Barron

Honeybees forage on diverse flowers which vary in the amount and type of rewards they offer, and bees are challenged with maximizing the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here, we set bees a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees’ choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by basing their colour choices on their history of reinforcement for each colour. Computational modelling suggests a structure like the honeybee mushroom body with reinforcement-related plasticity at both input and output can be sufficient for this cognitive strategy.We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the use and limitations of this simple cognitive strategy for foraging animals.


Brains on Board: Neuromorphic Control of Flying Robots

Engineering and Physical Sciences Research Council

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