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An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation

AAAI 2025 · Learning theory and algorithms › Prediction and decision losses · approach: Ranking models from comparisons · 0 citations (OpenAlex)

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Introduces a family of argument-ranking semantics obtained by applying social ranking functions (notably lexicographic excellence) to extension rankings, giving a refinement of skeptical/credulous/rejected acceptance, with axiomatic necessary and sufficient conditions.

Problem

Argument-ranking semantics are technically distinct from extension-based acceptance classifications (skeptical, credulous, rejected), so they do not refine these classes. The paper asks how to build rankings that refine skeptical/credulous acceptance.

Approach

Combine extension-ranking semantics (which order sets of arguments by plausibility) with social ranking functions (which rank elements by the quality of sets containing them), generalised to partial orders via a set-rank notion. Arguments are ranked by how often they appear in better-ranked extensions, using lex-cel; axioms (Independence from the worst set, Pareto-efficiency, Dominating set) are s

Key results

Surprising findings

Limitations

Experimental setup

Baselines: singleton argument-ranking semantics serialisability-based argument-ranking semantics ordinal Banzhaf-based argument ranking ceteris paribus majority-based argument ranking

Builds on: extension-ranking semantics lexicographic excellence operator argument-ranking semantics principles

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