Research map / Large language models / Language, safety and interpretability
Bilateral Gradual Semantics for Weighted Argumentation
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's full text. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Proposes bilateral gradual semantics for weighted argumentation that assigns each argument an acceptability and a rejectability degree, with principles and three iterative-limit semantics (ARM, ARC, ARH).
Problem
Existing gradual semantics for weighted argumentation measure only acceptability degree, ignoring a rejectability (negative strength) dimension and the gradual analogue of defense.
Approach
Non-reciprocal bilateral evaluation: acceptability is driven by basic weight and attackers' acceptability and rejectability, while rejectability is determined solely by attackers' acceptability; three h-categorizer-style semantics (max-based, card-based, hybrid) are defined as limits of convergent iterative sequences and characterized by a set of principles.
Key results
- Proves that the iterative sequences for the ARM, ARC and ARH semantics converge for any weighted argumentation graph (Theorems 1, 4, 7).
- ARM satisfies Quality Precedence, ARC satisfies Cardinality Precedence, and ARH satisfies Compensation; ARC satisfies all principles except QP and Compensation.
- Worked example shows the ARM semantics gives sigma+(a)=3/4 > sigma+(x)=1/2 (quality over quantity), while ARC gives sigma+(a)=5/16 < sigma+(x)=1/3 (quantity over quality).
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Prioritize attacker quality rather than attacker quantity | Bilateral gradual semantics on the Figure 2 WAG · Figure 2 WAG | acceptability degree: ARM: 3/4 (a) > 1/2 (x); ARC: 5/16 (a) < 1/3 (x) | Mixed |
| Prioritize attacker quality rather than attacker quantity | Bilateral gradual semantics on the Figure 2 WAG · Figure 2 WAG | rejectability degree: ARM: 1/3 (a) < 1/2 (x); ARC: 7/10 (a) > 2/3 (x) | Mixed |
| Balance attacker quality and quantity | ARH · Figure 3 WAG | rejectability degree: 4/5 (a) = 4/5 (z) | No clear effect |
Surprising findings
- Under the bilateral semantics, the principles Quality Precedence, Cardinality Precedence and A-Maximality are mutually incompatible, and Compensation is incompatible with both QP and CP.
Limitations
- Semantics are not yet extended to weighted bipolar argumentation graphs or SETAF; left as future work.
- Some principles are incompatible, so no single semantics satisfies all desirable principles (ARM, ARC, ARH each miss some).
Experimental setup
Baselines: weighted max-based semantics weighted card-based semantics h-categorizer semantics
Builds on: h-categorizer gradual semantics principles (Amgoud et al. 2017) labelling semantics weighted max-based and card-based semantics
Closest papers by meaning
- How Many Properties Do We Need for Gradual Argumentation? (AAAI 2018 · similarity 0.91)
- Convergent Semantics for Weighted Bipolar Argumentation (AAAI 2026 · similarity 0.91)
- Non-flat ABA Is an Instance of Bipolar Argumentation (AAAI 2024 · similarity 0.87)
- An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation (AAAI 2025 · similarity 0.86)
- Redefining ABA+ Semantics via Abstract Set-to-Set Attacks (AAAI 2024 · similarity 0.86)
- Defeasible Normative Reasoning: A Proof-Theoretic Integration of Logical Argumentation (AAAI 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.