Approximating Stability for Applied Argument-based Inquiry
Publication date
2022-11
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Abstract
In argument-based inquiry, agents jointly construct arguments supporting or attacking a topic claim to find out if the claim can be accepted given the agents’ knowledge bases. While such inquiry systems can be used for various forms of automated information intake, several efficiency issues have so far prevented widespread application. In this paper, we aim to tackle these efficiency issues by exploring the notion of stability: can additional information change the justification status of the claim under discussion? Detecting stability is not tractable for every input, since the problem is CoNP-complete, yet in practical applications it is essential to guarantee efficient computation. This makes approximation a viable alternative. We present a sound approximation algorithm that recognises stability for many inputs in polynomial time and discuss several of its properties. In particular, we show that the algorithm is sound and identify constraints on the input under which it is complete. As a final contribution of this paper, we describe how the proposed algorithm is used in three different case studies at the Netherlands Police.
Keywords
Dynamic argumentation, Inquiry, Law enforcement, Structured argumentation, Computer Science (miscellaneous), Signal Processing, Computer Vision and Pattern Recognition, Computer Science Applications, Artificial Intelligence
Citation
Odekerken, D, Bex, F, Borg, A & Testerink, B 2022, 'Approximating Stability for Applied Argument-based Inquiry', Intelligent Systems with Applications, vol. 16, 200110. https://doi.org/10.1016/j.iswa.2022.200110