<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Intent Machines

Name: Intent Machines
Keywords: machine learning, user intentions, intent machine, automation

descriptionPublicationkeyboard_double_arrow_right Report 21 Feb 2024 English Publisher:Zenodo

Authors: Hart, Anthony; Reusche, D;

doi: 10.5281/zenodo.10654543

Intent Machines

- Summary
- Subjects
- Metrics

Abstract

This paper serves as an overview of the abstract mathematical structures that may be used to formalize intents and the machines that process them. We will give a hierarchy of progressively more specific structures with the goal of capturing the concept of an abstract intent machine at different levels of abstraction, and use these insights to understand different methods for composing/combining/coordinating these machines.

Keywords

machine learning, user intentions, intent machine, automation

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

Average

Green