Foraging in an Uncertain Environment Using Predictive Hebbian Learning
Abstract
Survival is enhanced by an ability to predict the availability of food, the likelihood of predators, and the presence of mates. We present a concrete model that uses diffuse neurotransmitter systems to implement a predictive version of a Hebb learning rule embedded in a neural ar(cid:173) chitecture based on anatomical and physiological studies on bees. The model captured the strategies seen in the behavior of bees and a number of other animals when foraging in an uncertain environment. The predictive model suggests a unified way in which neuromodulatory influences can be used to bias actions and control synaptic plasticity.
Cite
Text
Montague et al. "Foraging in an Uncertain Environment Using Predictive Hebbian Learning." Neural Information Processing Systems, 1993.Markdown
[Montague et al. "Foraging in an Uncertain Environment Using Predictive Hebbian Learning." Neural Information Processing Systems, 1993.](https://mlanthology.org/neurips/1993/montague1993neurips-foraging/)BibTeX
@inproceedings{montague1993neurips-foraging,
title = {{Foraging in an Uncertain Environment Using Predictive Hebbian Learning}},
author = {Montague, P. Read and Dayan, Peter and Sejnowski, Terrence J.},
booktitle = {Neural Information Processing Systems},
year = {1993},
pages = {598-605},
url = {https://mlanthology.org/neurips/1993/montague1993neurips-foraging/}
}