Many-valued Argumentation, Conditionals and a Probabilistic Semantics for Gradual Argumentation
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866908397839843328 |
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| author | Alviano, Mario Giordano, Laura Dupré, Daniele Theseider |
| author_facet | Alviano, Mario Giordano, Laura Dupré, Daniele Theseider |
| contents | In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with respect to a class of gradual semantics, through the verification of graded (strict or defeasible) implications over a preferential interpretation. As a proof of concept, in the finitely-valued case, an Answer set Programming approach is proposed for conditional reasoning in a many-valued argumentation semantics of weighted argumentation graphs. The paper also develops and discusses a probabilistic semantics for gradual argumentation, which builds on the many-valued conditional semantics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_07523 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Many-valued Argumentation, Conditionals and a Probabilistic Semantics for Gradual Argumentation Alviano, Mario Giordano, Laura Dupré, Daniele Theseider Artificial Intelligence I.2.4 In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with respect to a class of gradual semantics, through the verification of graded (strict or defeasible) implications over a preferential interpretation. As a proof of concept, in the finitely-valued case, an Answer set Programming approach is proposed for conditional reasoning in a many-valued argumentation semantics of weighted argumentation graphs. The paper also develops and discusses a probabilistic semantics for gradual argumentation, which builds on the many-valued conditional semantics. |
| title | Many-valued Argumentation, Conditionals and a Probabilistic Semantics for Gradual Argumentation |
| topic | Artificial Intelligence I.2.4 |
| url | https://arxiv.org/abs/2212.07523 |