Ranking Transition-based Medical Recommendations using Assumption-based Argumentation

Kenneth Skiba; Matthias Thimm; Johannes Peter Wallner

doi:10.1007/978-3-031-63536-6_12

Ranking Transition-based Medical Recommendations using Assumption-based Argumentation

Kenneth Skiba
, Matthias Thimm
, Johannes Peter Wallner

Institute of Software Engineering and Artificial Intelligence (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

We present a general framework to rank assumption in assumption-based argumentation frameworks (ABA frameworks), relying on their relationship to other assumptions and the syntactical structure of the ABA framework. We propose a new family of semantics for ABA frameworks that is using reductions to the abstract argumentation setting and leveraging existing ranking-based semantics for abstract argumentation. We show the suitability of these semantics by investigating a case study based on medical recommendations for patients with multiple health conditions and show that the relationship of the recommendations are enough to establish a ranking between the recommendations.

Original language	English
Title of host publication	Robust Argumentation Machines - First International Conference, RATIO 2024, Proceedings
Editors	Philipp Cimiano, Anette Frank, Michael Kohlhase, Benno Stein
Publisher	Springer
Pages	202-220
Number of pages	19
ISBN (Print)	9783031635359
DOIs	https://doi.org/10.1007/978-3-031-63536-6_12
Publication status	Published - 2024
Event	1st International Conference on Recent Advances in Robust Argumentation Machines: RATIO 2024 - Bielefeld, Germany Duration: 5 Jun 2024 → 7 Jun 2024 https://ratio-conference.net/

Publication series

Name	Lecture Notes in Computer Science
Volume	14638

Conference

Conference	1st International Conference on Recent Advances in Robust Argumentation Machines
Abbreviated title	RATIO 2024
Country/Territory	Germany
City	Bielefeld
Period	5/06/24 → 7/06/24
Internet address	https://ratio-conference.net/

Keywords

ABA
Ranking-based semantics
TMR

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Fields of Expertise

Information, Communication & Computing

Access to Document

10.1007/978-3-031-63536-6_12Licence: CC BY 4.0

Cite this

Skiba, K., Thimm, M., & Wallner, J. P. (2024). Ranking Transition-based Medical Recommendations using Assumption-based Argumentation. In P. Cimiano, A. Frank, M. Kohlhase, & B. Stein (Eds.), Robust Argumentation Machines - First International Conference, RATIO 2024, Proceedings (pp. 202-220). (Lecture Notes in Computer Science; Vol. 14638). Springer. https://doi.org/10.1007/978-3-031-63536-6_12

Ranking Transition-based Medical Recommendations using Assumption-based Argumentation. / Skiba, Kenneth; Thimm, Matthias; Wallner, Johannes Peter.
Robust Argumentation Machines - First International Conference, RATIO 2024, Proceedings. ed. / Philipp Cimiano; Anette Frank; Michael Kohlhase; Benno Stein. Springer, 2024. p. 202-220 (Lecture Notes in Computer Science; Vol. 14638).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Skiba, K, Thimm, M & Wallner, JP 2024, Ranking Transition-based Medical Recommendations using Assumption-based Argumentation. in P Cimiano, A Frank, M Kohlhase & B Stein (eds), Robust Argumentation Machines - First International Conference, RATIO 2024, Proceedings. Lecture Notes in Computer Science, vol. 14638, Springer, pp. 202-220, 1st International Conference on Recent Advances in Robust Argumentation Machines, Bielefeld, North Rhine-Westphalia, Germany, 5/06/24. https://doi.org/10.1007/978-3-031-63536-6_12

Skiba, Kenneth ; Thimm, Matthias ; Wallner, Johannes Peter. / Ranking Transition-based Medical Recommendations using Assumption-based Argumentation. Robust Argumentation Machines - First International Conference, RATIO 2024, Proceedings. editor / Philipp Cimiano ; Anette Frank ; Michael Kohlhase ; Benno Stein. Springer, 2024. pp. 202-220 (Lecture Notes in Computer Science).

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Ranking Transition-based Medical Recommendations using Assumption-based Argumentation

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Fields of Expertise

Access to Document

Other files and links

FWF - Neue KI - A Novel Computational Workflow for Argumentation in AI

Cite this

Ranking Transition-based Medical Recommendations using Assumption-based Argumentation

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Fields of Expertise

Access to Document

Other files and links

Projects

FWF - Neue KI - A Novel Computational Workflow for Argumentation in AI

Cite this