Possibilistic Logic Underlies Abstract Dialectical Frameworks

Jesse Heyninck; Gabriele Kern-Isberner; Tjitze Rienstra; Kenneth Skiba; Matthias Thimm

doi:10.24963/ijcai.2022/368

Possibilistic Logic Underlies Abstract Dialectical Frameworks

Jesse Heyninck, Gabriele Kern-Isberner, Tjitze Rienstra, Kenneth Skiba, Matthias Thimm

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

14 Downloads (Pure)

Abstract

Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, we ask which monotonic three-valued logic allows to capture the main semantic concepts underlying ADFs. We show that possibilistic logic is the unique logic that can faithfully encode all other semantical concepts for ADFs. Based on this result, we also characterise strong equivalence and introduce possibilistic ADFs.

Original language	English
Title of host publication	Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)
Publisher	International Joint Conferences on Artificial Intelligence
Pages	2655-2661
ISBN (Electronic)	978-1-956792-00-3
DOIs	https://doi.org/10.24963/ijcai.2022/368
Publication status	Published - 2022
Event	Thirty-First International Joint Conference on Artificial Intelligence - Messe Wien, Vienna, Austria Duration: 23 Jul 2022 → 29 Jul 2022 https://ijcai-22.org/

Conference

Conference	Thirty-First International Joint Conference on Artificial Intelligence
Abbreviated title	IJCAI 2022
Country/Territory	Austria
City	Vienna
Period	23/07/22 → 29/07/22
Internet address	https://ijcai-22.org/

Access to Document

10.24963/ijcai.2022/368

Full TextFinal published version, 178 KBLicence: Taverne

https://dblp.org/rec/conf/ijcai/HeyninckKRST22

Cite this

@inproceedings{df70ffdd700e4d1a9f21e4ce0df3a82d,

title = "Possibilistic Logic Underlies Abstract Dialectical Frameworks",

abstract = "Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, we ask which monotonic three-valued logic allows to capture the main semantic concepts underlying ADFs. We show that possibilistic logic is the unique logic that can faithfully encode all other semantical concepts for ADFs. Based on this result, we also characterise strong equivalence and introduce possibilistic ADFs.",

author = "Jesse Heyninck and Gabriele Kern-Isberner and Tjitze Rienstra and Kenneth Skiba and Matthias Thimm",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2022 ; Conference date: 23-07-2022 Through 29-07-2022",

year = "2022",

doi = "10.24963/ijcai.2022/368",

language = "English",

pages = "2655--2661",

booktitle = "Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)",

publisher = "International Joint Conferences on Artificial Intelligence",

address = "United States",

url = "https://ijcai-22.org/",

}

Heyninck, J, Kern-Isberner, G, Rienstra, T, Skiba, K & Thimm, M 2022, Possibilistic Logic Underlies Abstract Dialectical Frameworks. in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22). International Joint Conferences on Artificial Intelligence, pp. 2655-2661, Thirty-First International Joint Conference on Artificial Intelligence, Vienna, Austria, 23/07/22. https://doi.org/10.24963/ijcai.2022/368

Possibilistic Logic Underlies Abstract Dialectical Frameworks. / Heyninck, Jesse; Kern-Isberner, Gabriele; Rienstra, Tjitze et al.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22). International Joint Conferences on Artificial Intelligence, 2022. p. 2655-2661.

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

TY - GEN

T1 - Possibilistic Logic Underlies Abstract Dialectical Frameworks

AU - Heyninck, Jesse

AU - Kern-Isberner, Gabriele

AU - Rienstra, Tjitze

AU - Skiba, Kenneth

AU - Thimm, Matthias

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2022

Y1 - 2022

N2 - Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, we ask which monotonic three-valued logic allows to capture the main semantic concepts underlying ADFs. We show that possibilistic logic is the unique logic that can faithfully encode all other semantical concepts for ADFs. Based on this result, we also characterise strong equivalence and introduce possibilistic ADFs.

AB - Abstract dialectical frameworks (in short, ADFs) are one of the most general and unifying approaches to formal argumentation. As the semantics of ADFs are based on three-valued interpretations, we ask which monotonic three-valued logic allows to capture the main semantic concepts underlying ADFs. We show that possibilistic logic is the unique logic that can faithfully encode all other semantical concepts for ADFs. Based on this result, we also characterise strong equivalence and introduce possibilistic ADFs.

U2 - 10.24963/ijcai.2022/368

DO - 10.24963/ijcai.2022/368

M3 - Conference article in proceeding

SP - 2655

EP - 2661

BT - Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)

PB - International Joint Conferences on Artificial Intelligence

T2 - Thirty-First International Joint Conference on Artificial Intelligence

Y2 - 23 July 2022 through 29 July 2022

ER -