Abstract Argumentation Frameworks with Domain Assignments
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Main Track. Pages 2076-2082.
https://doi.org/10.24963/ijcai.2021/286
Keywords
- Knowledge Representation and Reasoning: Non-monotonic Reasoning
- Knowledge Representation and Reasoning: Computational Models of Argument
Abstract
Argumentative discourse rarely consists of opinions whose claims apply universally. As with logical statements, an argument applies to specific objects in the universe or relations among them, and may have exceptions. In this paper, we propose
an argumentation formalism that allows associating arguments with a domain of application. Appropriate semantics are given, which formalise the notion of partial argument acceptance, i.e. the set of objects or relations that an argument can be applied
to. We show that our proposal is in fact equivalent to the standard Argumentation Frameworks of Dung, but allows a more intuitive and compact expression of some core concepts of commonsense and non-monotonic reasoning, such as the scope of an argument, exceptions, relevance and others.
@inproceedings{ijcai2021p286,
title = {Abstract Argumentation Frameworks with Domain Assignments},
author = {Vassiliades, Alexandros and Patkos, Theodore and Flouris, Giorgos and Bikakis, Antonis and Bassiliades, Nick and Plexousakis, Dimitris},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {2076--2082},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/286},
url = {https://doi.org/10.24963/ijcai.2021/286},
}
TY - CPAPER TI - Abstract Argumentation Frameworks with Domain Assignments AU - Vassiliades, Alexandros AU - Patkos, Theodore AU - Flouris, Giorgos AU - Bikakis, Antonis AU - Bassiliades, Nick AU - Plexousakis, Dimitris T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 2076 EP - 2082 DO - 10.24963/ijcai.2021/286 UR - https://doi.org/10.24963/ijcai.2021/286 ER -Copied
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