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Modular Semantics and Characteristics for Bipolar Weighted Argumentation Graphs

arXiv 1807.06685 ↗First posted 17 Jul 2018cs.AI cs.LOcited by 23

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Abstract (arXiv)

This paper addresses the semantics of weighted argumentation graphs that are bipolar, i.e. contain both attacks and supports for arguments. It builds on previous work by Amgoud, Ben-Naim et. al. We study the various characteristics of acceptability semantics that have been introduced in these works, and introduce the notion of a modular acceptability semantics. A semantics is modular if it cleanly separates aggregation of attacking and supporting arguments (for a given argument a) from the computation of their influence on a's initial weight. We show that the various semantics for bipolar argumentation graphs from the literature may be analysed as a composition of an aggregation function with an influence function. Based on this modular framework, we prove general convergence and divergence theorems. We demonstrate that all well-behaved modular acceptability semantics converge for all acyclic graphs and that no sum-based semantics can converge for all graphs. In particular, we show divergence of Euler-based semantics (Amgoud et al.) for certain cyclic graphs. Further, we provide the first semantics for bipolar weighted graphs that converges for all graphs.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jul 2018.

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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 4; 2025: 6; 2026: 7.

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  1. 2023SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report]cited by 18
  2. 2024PeerArg: Argumentative Peer Review with LLMscited by 9
  3. 2023Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks (Technical Report)cited by 7
  4. 2025Change in Quantitative Bipolar Argumentation: Sufficient, Necessary, and Counterfactual Explanationscited by 4
  5. 2022Inferring Attack Relations for Gradual Semanticscited by 3
  6. 2024Explaining Arguments' Strength: Unveiling the Role of Attacks and Supports (Technical Report)cited by 3
  7. 2024CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks (Technical Report)cited by 3
  8. 2025Neuro-Argumentative Learning with Case-Based Reasoningcited by 3
  9. 2025On Gradual Semantics for Assumption-Based Argumentationcited by 3
  10. 2025Contestability in Quantitative Argumentationcited by 3
  11. 2022The Inverse Problem for Argumentation Gradual Semanticscited by 2
  12. 2025Set Contribution Functions for Quantitative Bipolar Argumentation and their Principlescited by 2
11 more
  1. 2026Strength Change Explanations in Quantitative Argumentationcited by 2
  2. 2022Many-valued Argumentation, Conditionals and a Probabilistic Semantics for Gradual Argumentationcited by 1
  3. 2024Applying Attribution Explanations in Truth-Discovery Quantitative Bipolar Argumentation Frameworkscited by 1
  4. 2025Argumentative Debates for Transparent Bias Detection [Technical Report]cited by 1
  5. 2026ARGORA: Orchestrated Argumentation for Causally Grounded LLM Reasoning and Decision Makingcited by 1
  6. 2026Towards an Argumentative Foundation for Evaluative AIcited by 1
  7. 2021Learning Gradual Argumentation Frameworks using Genetic Algorithmscited by 0
  8. 2026LLM-based Argument Mining meets Argumentation and Description Logics: a Unified Framework for Reasoning about Debatescited by 0
  9. 2026Double Rectified Linear Unit-based Modular Semantics for Quantitative Bipolar Argumentation Frameworkcited by 0
  10. 2026Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflictcited by 0
  11. 2026Contrastive Explanations in Quantitative Bipolar Argumentation Frameworkscited by 0