Learning and forgetting using reinforced Bayesian change detection

V Moens, A Zénon - PLoS computational biology, 2019 - journals.plos.org
Agents living in volatile environments must be able to detect changes in contingencies while
refraining to adapt to unexpected events that are caused by noise. In Reinforcement …

BAM: Bayes with adaptive memory

J Nassar, J Brennan, B Evans, K Lowrey - arxiv preprint arxiv:2202.02405, 2022 - arxiv.org
Online learning via Bayes' theorem allows new data to be continuously integrated into an
agent's current beliefs. However, a naive application of Bayesian methods in non stationary …

Using sequential drift detection to test the API economy

S Ackerman, P Dube, E Farchi - arxiv preprint arxiv:2111.05136, 2021 - arxiv.org
The API economy refers to the widespread integration of API (advanced programming
interface) microservices, where software applications can communicate with each other, as …

[PDF][PDF] Learning and making decisions in changing environments with Variational Inference

V Moens - 2018 - dial.uclouvain.be
Understanding the brain, and, broadly speaking, studying human nature, can be regarded
as a nested problem: a group of of individuals of a kind try to model the specifics of this kind …