<div class="csl-bib-body">
<div class="csl-entry">Clemens Heitzinger, & Stefan Woltran. (2024). A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations. In H. Werthner, C. Ghezzi, & J. Kramer (Eds.), <i>Introduction to Digital Humanism : A Textbook</i> (pp. 135–149). Springer. https://doi.org/10.1007/978-3-031-45304-5_9</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/192268
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dc.description.abstract
This chapter gives an overview of the most important methods in artificial intelligence (AI). The methods of symbolic AI are rooted in logic, and finding possible solutions by search is a central aspect. The main challenge is the combinatorial explosion in search, but the focus on the satisfiability problem of propositional logic (SAT) since the 1990s and the accompanying algorithmic improvements have made it possible to solve problems on the scale needed in industrial applications. In machine learning (ML), self-learning algorithms extract information from data and represent the solutions in convenient forms. ML broadly consists of supervised learning, unsupervised learning, and reinforcement learning. Successes in the 2010s and early 2020s such as solving Go, chess, and many computer games as well as large language models such as ChatGPT are due to huge computational resources and algorithmic advances in ML. Finally, we reflect on current developments and draw conclusions.
en
dc.language.iso
en
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dc.subject
Artificial Intelligence
en
dc.title
A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations
en
dc.type
Book Contribution
en
dc.type
Buchbeitrag
de
dc.contributor.editoraffiliation
Politecnico di Milano, Italy
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dc.contributor.editoraffiliation
Imperial College London, United Kingdom
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dc.relation.isbn
978-3-031-45304-5
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dc.description.startpage
135
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dc.description.endpage
149
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dc.type.category
Edited Volume Contribution
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tuw.booktitle
Introduction to Digital Humanism : A Textbook
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tuw.relation.publisher
Springer
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tuw.relation.publisherplace
Cham
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tuw.researchTopic.id
C5
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tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-06 - Forschungsbereich Machine Learning
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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tuw.publication.orgunit
E056-13 - Fachbereich LogiCS
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tuw.publisher.doi
10.1007/978-3-031-45304-5_9
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dc.description.numberOfPages
15
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tuw.author.orcid
0000-0003-1594-8972
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tuw.editor.orcid
0000-0002-7234-5011
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wb.sciencebranch
Informatik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.value
100
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item.cerifentitytype
Publications
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item.languageiso639-1
en
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item.openairecristype
http://purl.org/coar/resource_type/c_3248
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item.grantfulltext
none
-
item.fulltext
no Fulltext
-
item.openairetype
book part
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crisitem.author.dept
E194-06 - Forschungsbereich Machine Learning
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.orcid
0000-0003-1594-8972
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering