MAMay 22

Safety, Liveness, and Fairness in Quantitative Argumentation Dialogues

arXiv:2605.2357841.2
Predicted impact top 72% in MA · last 90 daysOriginality Incremental advance
AI Analysis

For researchers in argumentation theory and formal reasoning, this work provides a novel framework for analyzing dynamic argumentation graphs, though it remains theoretical without empirical validation.

The paper introduces safety, liveness, and fairness properties from temporal reasoning to quantitative argumentation dialogues, formally relating these notions and discussing analytical challenges for general guarantees.

We introduce notions of safety, liveness, and fairness, as commonly used in temporal reasoning, to quantitative (bipolar) argumentation dialogues where repeated inferences are drawn from argumentation graphs with weighted nodes. Between inferences, these graphs undergo updates. Strong and weak safety capture that arguments' (final) strengths remain above a specific threshold of justification and always reach the threshold eventually, respectively. Liveness requires that arguments' strengths fluctuate across the threshold of justification. Fairness notions assess how safe arguments are spread within a sequence of argumentation graphs. We formally show how these notions are related, and discuss some analytical challenges with respect to providing general guarantees for our properties.

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