English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A classical learning setting typically concerns an agent/student who collectsdata, or observations, from a system in order to estimate a certain property ofinterest. Correctional learning is a type of cooperative teacher-studentframework where a teacher, who has partial knowledge about the system, has theability to observe and alter (correct) the observations received by the studentin order to improve the accuracy of its estimate. In this paper, we show howthe variance of the estimate of the student can be reduced with the help of theteacher. We formulate the corresponding online problem - where the teacher hasto decide, at each time instant, whether or not to change the observations dueto a limited budget - as a Markov decision process, from which the optimalpolicy is derived using dynamic programming. We validate the framework innumerical experiments, and compare the optimal online policy with the one fromthe batch setting.

A Teacher-Student Markov Decision Process-based Framework for Online Correctional Learning