A simple model for learning in volatile environments.
Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-order statistics of observations dynamically evolve over time. We propose a new model, the volatile Kalma...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-07-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1007963 |