Machine Learning in Artificial Intelligence: Towards a Common Understanding

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dc.contributor.authorKühl, Niklas
dc.contributor.authorGoutier, Marc
dc.contributor.authorHirt, Robin
dc.contributor.authorSatzger, Gerhard
dc.date.accessioned2019-01-03T00:35:51Z
dc.date.available2019-01-03T00:35:51Z
dc.date.issued2019-01-08
dc.description.abstractThe application of “machine learning” and “artificial intelligence” has become popular within the last decade. Both terms are frequently used in science and media, sometimes interchangeably, sometimes with different meanings. In this work, we aim to clarify the relationship between these terms and, in particular, to specify the contribution of machine learning to artificial intelligence. We review relevant literature and present a conceptual framework which clarifies the role of machine learning to build (artificial) intelligent agents. Hence, we seek to provide more terminological clarity and a starting point for (inter¬disciplinary) discussions and future research.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.630
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59960
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAI, Machine Learning, IoT, and Analytics: Exploring the Implications for Knowledge Management and Innovation
dc.subjectKnowledge Innovation and Entrepreneurial Systems
dc.subjectArtificial Intelligence, Machine Learning, Statistical Learning, Intelligent Agents
dc.titleMachine Learning in Artificial Intelligence: Towards a Common Understanding
dc.typeConference Paper
dc.type.dcmiText

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