Beyond But-for Test: Counterfactual Explanation in Abstract Argumentation via Actual Causality (Extended Version)

📅 2026-06-29
📈 Citations: 0
Influential: 0
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🤖 AI Summary
This work addresses the limitations of existing counterfactual explanations in abstract argumentation, which predominantly rely on but-for tests and struggle with complex causal scenarios such as preemption and overdetermination. The paper proposes an intervention-based counterfactual reasoning framework that formalizes argument acceptability conditions as structural equations and incorporates refined counterfactual criteria from the Halpern-Pearl model of actual causality. By enabling simultaneous interventions on multiple variables and integrating witness constraints to fix key argument labels, the approach achieves precise identification of intricate causal structures within abstract argumentation frameworks. This method represents the first systematic effort to handle such complexities in this domain, demonstrating significantly enhanced expressiveness and reliability compared to current approaches.
📝 Abstract
Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the status of certain other arguments were changed? Existing approaches are limited to the but-for test and fail to accommodate more refined counterfactual conditions. To overcome these limitations, we introduce an intervention-based counterfactual reasoning framework in abstract argumentation. Our approach encodes the acceptance conditions of arguments as equations, then defines an intervention operator that supports (1) changing sets of arguments simultaneously, and (2) fixing witness arguments to their actual labels. Guided by the refined counterfactual condition introduced in the Halpern-Pearl definition, our method goes beyond the but-for test, thereby correctly identifying causes in argumentation structures such as Preemption and Overdetermination. Through comparison, we show that our method surpasses prior methods in both expressiveness and reliability.
Problem

Research questions and friction points this paper is trying to address.

counterfactual explanation
abstract argumentation
actual causality
but-for test
causal reasoning
Innovation

Methods, ideas, or system contributions that make the work stand out.

counterfactual explanation
abstract argumentation
actual causality
intervention-based reasoning
Halpern-Pearl causality
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