[{"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"<jats:p>The connection between inconsistent databases and Dung’s abstract argumentation framework has recently drawn growing interest. Specifically, an inconsistent database, involving certain types of integrity constraints such as functional and inclusion dependencies, can be viewed as an argumentation framework in Dung’s setting. Nevertheless, no prior work has explored the exact expressive power of Dung’s theory of argumentation when compared to inconsistent databases and integrity constraints. In this paper, we close this gap by arguing that an argumentation framework can also be viewed as an inconsistent database. We first establish a connection between subset-repairs for databases and extensions for AFs considering conflict-free, naive, admissible, and preferred semantics. Further, we define a new family of attribute-based repairs based on the principle of maximal content preservation. The effectiveness of these repairs is then highlighted by connecting them to stable, semi-stable, and stage semantics. Our main contributions include translating an argumentation framework into a database together with integrity constraints. Moreover, this translation can be achieved in polynomial time, which is essential in transferring complexity results between the two formalisms.</jats:p>"}],"publication":"Proceedings of the AAAI Conference on Artificial Intelligence","title":"Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases","date_created":"2025-05-15T11:05:36Z","publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","year":"2025","issue":"14","department":[{"_id":"574"}],"user_id":"99353","_id":"59910","project":[{"_id":"121","name":"TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des maschinellen Lernens"}],"status":"public","type":"conference","doi":"10.1609/aaai.v39i14.33651","volume":39,"author":[{"last_name":"Mahmood","full_name":"Mahmood, Yasir","id":"99353","first_name":"Yasir"},{"first_name":"Markus","last_name":"Hecher","full_name":"Hecher, Markus"},{"first_name":"Axel-Cyrille","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo"}],"date_updated":"2026-02-20T10:07:00Z","page":"15058-15066","intvolume":"        39","citation":{"ama":"Mahmood Y, Hecher M, Ngonga Ngomo A-C. Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Vol 39. Association for the Advancement of Artificial Intelligence (AAAI); 2025:15058-15066. doi:<a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">10.1609/aaai.v39i14.33651</a>","ieee":"Y. Mahmood, M. Hecher, and A.-C. Ngonga Ngomo, “Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 2025, vol. 39, no. 14, pp. 15058–15066, doi: <a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">10.1609/aaai.v39i14.33651</a>.","chicago":"Mahmood, Yasir, Markus Hecher, and Axel-Cyrille Ngonga Ngomo. “Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 39:15058–66. Association for the Advancement of Artificial Intelligence (AAAI), 2025. <a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">https://doi.org/10.1609/aaai.v39i14.33651</a>.","mla":"Mahmood, Yasir, et al. “Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 39, no. 14, Association for the Advancement of Artificial Intelligence (AAAI), 2025, pp. 15058–66, doi:<a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">10.1609/aaai.v39i14.33651</a>.","bibtex":"@inproceedings{Mahmood_Hecher_Ngonga Ngomo_2025, title={Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases}, volume={39}, DOI={<a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">10.1609/aaai.v39i14.33651</a>}, number={14}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, publisher={Association for the Advancement of Artificial Intelligence (AAAI)}, author={Mahmood, Yasir and Hecher, Markus and Ngonga Ngomo, Axel-Cyrille}, year={2025}, pages={15058–15066} }","short":"Y. Mahmood, M. Hecher, A.-C. Ngonga Ngomo, in: Proceedings of the AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), 2025, pp. 15058–15066.","apa":"Mahmood, Y., Hecher, M., &#38; Ngonga Ngomo, A.-C. (2025). Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, <i>39</i>(14), 15058–15066. <a href=\"https://doi.org/10.1609/aaai.v39i14.33651\">https://doi.org/10.1609/aaai.v39i14.33651</a>"},"publication_identifier":{"issn":["2374-3468","2159-5399"]},"publication_status":"published"},{"issue":"13","publication_identifier":{"issn":["2374-3468","2159-5399"]},"publication_status":"published","intvolume":"        38","page":"14388-14396","citation":{"apa":"Muschalik, M., Fumagalli, F., Hammer, B., &#38; Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, <i>38</i>(13), 14388–14396. <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">https://doi.org/10.1609/aaai.v38i13.29352</a>","bibtex":"@inproceedings{Muschalik_Fumagalli_Hammer_Huellermeier_2024, title={Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles}, volume={38}, DOI={<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>}, number={13}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)}, author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke}, year={2024}, pages={14388–14396} }","mla":"Muschalik, Maximilian, et al. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, vol. 38, no. 13, 2024, pp. 14388–96, doi:<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>.","short":"M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396.","ieee":"M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, 2024, vol. 38, no. 13, pp. 14388–14396, doi: <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>.","chicago":"Muschalik, Maximilian, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, 38:14388–96, 2024. <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">https://doi.org/10.1609/aaai.v38i13.29352</a>.","ama":"Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>. Vol 38. ; 2024:14388-14396. doi:<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>"},"year":"2024","volume":38,"date_created":"2024-03-27T14:50:04Z","author":[{"first_name":"Maximilian","last_name":"Muschalik","full_name":"Muschalik, Maximilian"},{"first_name":"Fabian","last_name":"Fumagalli","id":"93420","full_name":"Fumagalli, Fabian"},{"full_name":"Hammer, Barbara","last_name":"Hammer","first_name":"Barbara"},{"first_name":"Eyke","last_name":"Huellermeier","full_name":"Huellermeier, Eyke","id":"48129"}],"date_updated":"2025-09-11T16:20:11Z","doi":"10.1609/aaai.v38i13.29352","title":"Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles","publication":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)","type":"conference","status":"public","abstract":[{"text":"While shallow decision trees may be interpretable, larger ensemble models like gradient-boosted trees, which often set the state of the art in machine learning problems involving tabular data, still remain black box models. As a remedy, the Shapley value (SV) is a well-known concept in explainable artificial intelligence (XAI) research for quantifying additive feature attributions of predictions. The model-specific TreeSHAP methodology solves the exponential complexity for retrieving exact SVs from tree-based models. Expanding beyond individual feature attribution, Shapley interactions reveal the impact of intricate feature interactions of any order. In this work, we present TreeSHAP-IQ, an efficient method to compute any-order additive Shapley interactions for predictions of tree-based models. TreeSHAP-IQ is supported by a mathematical framework that exploits polynomial arithmetic to compute the interaction scores in a single recursive traversal of the tree, akin to Linear TreeSHAP. We apply TreeSHAP-IQ on state-of-the-art tree ensembles and explore interactions on well-established benchmark datasets.","lang":"eng"}],"department":[{"_id":"660"}],"user_id":"93420","_id":"53073","project":[{"name":"TRR 318 - C3: TRR 318 - Subproject C3","_id":"126"},{"_id":"109","name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren"},{"_id":"117","name":"TRR 318 - C: TRR 318 - Project Area C"}],"language":[{"iso":"eng"}],"keyword":["Explainable Artificial Intelligence"]},{"publication":"Proceedings of the AAAI Conference on Artificial Intelligence","abstract":[{"text":"<jats:p>Logic-based argumentation is a well-established formalism modeling nonmonotonic reasoning. It has been playing a major role in AI for decades, now.  Informally, a set of formulas is the support for a given claim if it is consistent, subset-minimal, and implies the claim. In such a case, the pair of the support and the claim together is called an argument. In this paper, we study the propositional variants of the following three computational tasks studied in argumentation: ARG (exists a support for a given claim with respect to a given set of formulas), ARG-Check (is a given set a support for a given claim), and ARG-Rel (similarly as ARG plus requiring an additionally given formula to be contained in the support). ARG-Check is complete for the complexity class DP, and the other two problems are known to be complete for the second level of the polynomial hierarchy and, accordingly, are highly intractable. Analyzing the reason for this intractability, we perform a two-dimensional classification: first, we consider all possible propositional fragments of the problem within Schaefer's framework, and then study different parameterizations for each of the fragment.\r\nWe identify a list of reasonable structural parameters (size of the claim, support, knowledge-base) that are connected to the aforementioned decision problems. Eventually, we thoroughly draw a fine border of parameterized intractability for each of the problems showing where the problems are fixed-parameter tractable and when this exactly stops. Surprisingly, several cases are of very high intractability (paraNP and beyond).</jats:p>","lang":"eng"}],"language":[{"iso":"eng"}],"keyword":["General Medicine"],"issue":"7","year":"2021","date_created":"2023-07-03T11:34:49Z","publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","title":"Parameterized Complexity of Logic-Based Argumentation in Schaefer's Framework","type":"conference","status":"public","user_id":"99353","_id":"45841","publication_status":"published","publication_identifier":{"issn":["2374-3468","2159-5399"]},"citation":{"ieee":"Y. Mahmood, A. Meier, and J. Schmidt, “Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 2021, vol. 35, no. 7, pp. 6426–6434, doi: <a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">10.1609/aaai.v35i7.16797</a>.","chicago":"Mahmood, Yasir, Arne Meier, and Johannes Schmidt. “Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 35:6426–34. Association for the Advancement of Artificial Intelligence (AAAI), 2021. <a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">https://doi.org/10.1609/aaai.v35i7.16797</a>.","ama":"Mahmood Y, Meier A, Schmidt J. Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Vol 35. Association for the Advancement of Artificial Intelligence (AAAI); 2021:6426-6434. doi:<a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">10.1609/aaai.v35i7.16797</a>","mla":"Mahmood, Yasir, et al. “Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 35, no. 7, Association for the Advancement of Artificial Intelligence (AAAI), 2021, pp. 6426–34, doi:<a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">10.1609/aaai.v35i7.16797</a>.","bibtex":"@inproceedings{Mahmood_Meier_Schmidt_2021, title={Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework}, volume={35}, DOI={<a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">10.1609/aaai.v35i7.16797</a>}, number={7}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, publisher={Association for the Advancement of Artificial Intelligence (AAAI)}, author={Mahmood, Yasir and Meier, Arne and Schmidt, Johannes}, year={2021}, pages={6426–6434} }","short":"Y. Mahmood, A. Meier, J. Schmidt, in: Proceedings of the AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), 2021, pp. 6426–6434.","apa":"Mahmood, Y., Meier, A., &#38; Schmidt, J. (2021). Parameterized Complexity of Logic-Based Argumentation in Schaefer’s Framework. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, <i>35</i>(7), 6426–6434. <a href=\"https://doi.org/10.1609/aaai.v35i7.16797\">https://doi.org/10.1609/aaai.v35i7.16797</a>"},"intvolume":"        35","page":"6426-6434","author":[{"full_name":"Mahmood, Yasir","id":"99353","last_name":"Mahmood","first_name":"Yasir"},{"first_name":"Arne","full_name":"Meier, Arne","last_name":"Meier"},{"first_name":"Johannes","full_name":"Schmidt, Johannes","last_name":"Schmidt"}],"volume":35,"date_updated":"2024-06-04T15:59:46Z","doi":"10.1609/aaai.v35i7.16797"}]