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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In recent years some researchers have explored the use of reinforcementlearning (RL) algorithms as key components in the solution of various naturallanguage processing tasks. For instance, some of these algorithms leveragingdeep neural learning have found their way into conversational systems. Thispaper reviews the state of the art of RL methods for their possible use fordifferent problems of natural language processing, focusing primarily onconversational systems, mainly due to their growing relevance. We providedetailed descriptions of the problems as well as discussions of why RL iswell-suited to solve them. Also, we analyze the advantages and limitations ofthese methods. Finally, we elaborate on promising research directions innatural language processing that might benefit from reinforcement learning.

Survey on reinforcement learning for language processing