Sarah Alice Gaggl

From International Center for Computational Logic

Dr. Sarah Alice Gaggl

Group LeaderTechnische Universität DresdenInternational Center for Computational Logic Logic Programming and Argumentation

Starting in October 2020 I will be leading the research group Logic Programming and Argumentation at the Institute of Artificial Intelligence, TU-Dresden. Also starting in October 2020 I will be project leader of BMBF funded project NAVAS - Navigation Approaches for Answer Sets. Since 2019 I am a principal investigator in the Transregional Collaborative Research Centre 248 Center for Perspicuous Computing (CPEC) which aims at enabling comprehension in a cyber-physical world with the human in the loop. From April 2013 till September 2020 I was a postdoctoral research assistant at the Computational Logic Group at the TU-Dresden.

My research interests are in (but not limmited to)

Before joining the TU Dresden I received my PhD in Computer Science in 2013 at the Vienna University of Technology. From 2009 to 2012 I was working as a project research assistant in the Database and Artificial Intelligence Group at the WWTF project New Methods for Analyzing, Comparing, and Solving Argumentation Problems under the supervision of Stefan Woltran.

For further information have a look at my CV.

Newest Publications

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Mei Yang, Sarah Alice Gaggl, Sebastian Rudolph
Neva – Extension Visualization for Argumentation Frameworks
Proceedings of the 8th International Conference on Computational Models of Argument (COMMA 2020), volume 326 of Frontiers in Artificial Intelligence and Applications, 477-478, September 2020
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Sarah Alice Gaggl, Matthias Thimm, Mauro Vallati
Proceedings of the Third International Workshop on Systems and Algorithms for Formal Argumentation (SAFA'20)
Volume 2672, September 2020. CEUR-WS.org
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Sarah Alice Gaggl, Thomas Linsbichler, Marco Maratea, Stefan Woltran
Design and results of the second international competition on computational models of argumentation
Artificial Intelligence, 279, February 2020
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Wolfgang Dvořák, Sarah Alice Gaggl, Anna Rapberger, Johannes Peter Wallner, Stefan Woltran
The ASPARTIX System Suite
Proceedings of the 8th International Conference on Computational Models of Argument (COMMA 2020), volume 326 of Frontiers in Artificial Intelligence and Applications, 461-462, September 2020
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Sarah Alice Gaggl, Thomas Linsbichler, Marco Maratea, Stefan Woltran
Design and Results of the Second International Competition on Computational Models of Argumentation
Technical Report, arXiv.org, volume CoRR abs/1909.00621, September 2019
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Sarah Alice Gaggl, Thomas Linsbichler, Marco Maratea, Stefan Woltran
Summary Report of the Second International Competition on Computational Models of Argumentation
AI Magazine, 39(4):77-79, December 2018
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Federico Cerutti, Sarah Alice Gaggl, Matthias Thimm, Johannes Peter Wallner
Foundations of Implementations for Formal Argumentation
In Pietro Baroni; Dov Gabbay; Massimiliano Giacomin; Leendert van der Torre, eds., Handbook on Formal Argumentation, chapter Foundations of implementations for formal argumentation, 688-767. College Publications, February 2018
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Federico Cerutti, Sarah Alice Gaggl, Matthias Thimm, Johannes Peter Wallner
Foundations of Implementations for Formal Argumentation
The IfCoLog Journal of Logics and their Applications; Special Issue Formal Argumentation, 4:2623-2705, September 2017
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Sarah Alice Gaggl, Sebastian Rudolph, Lukas Schweizer
Practical Fixed-Domain Reasoning for Description Logics - Extended Abstract
In Juan L. Reutter, Divesh Srivastava, eds., Proceedings of the 11th Alberto Mendelzon International Workshop on Foundations of Data Management and the Web, Montevideo, Uruguay, June 7-9, 2017, volume 1912 of CEUR Workshop Proceedings, June 2017. CEUR-WS.org
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Wolfgang Dvořák, Sarah Alice Gaggl
Stage semantics and the SCC-recursive schema for argumentation semantics
Journal of Logic and Computation, 26(4):1149-1202, August 2016
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Courses


Suggested Thesis Topics


Completed Theses

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CPEC
Center for Perspicuous Computing

NAVAS
Navigation Approaches for Answer Sets