Choosing the Lens: Strategic Perspective Activation in Context-Dependent Argumentation

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Authors	Albert Sadowski & Jarosław A. Chudziak
Year	2026
Field	AI / Agents
arXiv	2605.31581
PDF	Download
Categories	cs.AI

Abstract

The same arguments often need to be evaluated under different external regimes. An agent with influence over the regime has a strategic lever that standard formalisms do not directly capture. We introduce context-dependent argumentation frameworks (CDAFs), an extension of Dung's theory in which a defeat function determines, per context, which attacks succeed. A perspective-labeled specialisation derives the defeat function from a relevance set $ρ$ and a priority $π$. The relevance set is the agent's action space. In a small worked example, the agent's target argument is rejected under every full-relevance injective priority, yet accepted under partial activations, one of which no VAF audience can mirror. We define the corresponding decision problem, ACTIVATION-MANIPULATION, and record baseline complexity bounds. Tight bounds and multi-agent variants are left open.

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Engineering Breakdown

The Problem

The same arguments often need to be evaluated under different external regimes. We define the corresponding decision problem, ACTIVATION-MANIPULATION, and record baseline complexity bounds.

The Approach

We introduce context-dependent argumentation frameworks (CDAFs), an extension of Dung's theory in which a defeat function determines, per context, which attacks succeed.

Key Results

Tight bounds and multi-agent variants are left open.

Research Areas

This paper contributes to the following areas of AI/ML engineering:

• Autonomous agents
• Planning
• Tool use
• Agentic systems
• LLM agents
• Strategic

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