Bee Foraging in Uncertain Environments using
Predictive Hebbian Learning
P Read Montague Peter Dayan Christophe
Person TJ Sejnowski
Nature, 377, 725-728.
Abstract
Recent work has identified a neuron with widespread projections to
odour processing regions of the honeybee brain whose activity represents
the reward value of gustatory stimuli. We have constructed a model of bee
foraging in uncertain environments based on this type of neuron and a
predictive form of hebbian synaptic plasticity. The model uses visual input
from a simulated three-dimensional world and accounts for a wide range of
experiments on bee learning during foraging, including risk aversion. The
predictive model shows how neuromodulatory influences can be used to bias
actions and control synaptic plasticity in a way that goes beyond standard
correlational mechanisms. Although several behavioural models of
conditioning in bees have been proposed, this model is based on the neural
substrate and was tested in a simulation of bee flight.