@unpublished{62723, abstract = {{Structural measures of graphs, such as treewidth, are central tools in computational complexity resulting in efficient algorithms when exploiting the parameter. It is even known that modern SAT solvers work efficiently on instances of small treewidth. Since these solvers are widely applied, research interests in compact encodings into (Q)SAT for solving and to understand encoding limitations. Even more general is the graph parameter clique-width, which unlike treewidth can be small for dense graphs. Although algorithms are available for clique-width, little is known about encodings. We initiate the quest to understand encoding capabilities with clique-width by considering abstract argumentation, which is a robust framework for reasoning with conflicting arguments. It is based on directed graphs and asks for computationally challenging properties, making it a natural candidate to study computational properties. We design novel reductions from argumentation problems to (Q)SAT. Our reductions linearly preserve the clique-width, resulting in directed decomposition-guided (DDG) reductions. We establish novel results for all argumentation semantics, including counting. Notably, the overhead caused by our DDG reductions cannot be significantly improved under reasonable assumptions.}}, author = {{Mahmood, Yasir and Hecher, Markus and Groven, Johanna and Fichte, Johannes K.}}, booktitle = {{Pre-print of paper accepted at AAAI 2026}}, title = {{{Structure-Aware Encodings of Argumentation Properties for Clique-width}}}, year = {{2026}}, } @unpublished{62721, abstract = {{We introduce the notion of contrastive ABox explanations to answer questions of the type "Why is a an instance of C, but b is not?". While there are various approaches for explaining positive entailments (why is C(a) entailed by the knowledge base) as well as missing entailments (why is C(b) not entailed) in isolation, contrastive explanations consider both at the same time, which allows them to focus on the relevant commonalities and differences between a and b. We develop an appropriate notion of contrastive explanations for the special case of ABox reasoning with description logic ontologies, and analyze the computational complexity for different variants under different optimality criteria, considering lightweight as well as more expressive description logics. We implemented a first method for computing one variant of contrastive explanations, and evaluated it on generated problems for realistic knowledge bases.}}, author = {{Koopmann, Patrick and Mahmood, Yasir and Ngonga Ngomo, Axel-Cyrille and Tiwari, Balram}}, booktitle = {{Pre-print of paper accepted at AAAI 2026}}, title = {{{Can You Tell the Difference? Contrastive Explanations for ABox Entailments}}}, year = {{2026}}, } @inproceedings{65494, author = {{Manzoor, Ali and Zahera, Hammada M. and Saleem, Muhammad and Mahmood, Yasir and Speck, René and Khan, Hashim and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web – 23rd European Semantic Web Conference, ESWC 2026, Dubrovnik , Croatia, May 10-14, 2026, Proceedings}}, keywords = {{dice hamada hashim kiakadamie mahmood manzoor ngonga rene sail saleem}}, title = {{{Document-level Relation Extraction using Reinforcement Learning with Knowledge Graph Feedback}}}, year = {{2026}}, } @unpublished{61065, abstract = {{Abduction is the task of computing a sufficient extension of a knowledge base (KB) that entails a conclusion not entailed by the original KB. It serves to compute explanations, or hypotheses, for such missing entailments. While this task has been intensively investigated for perfect data and under classical semantics, less is known about abduction when erroneous data results in inconsistent KBs. In this paper we define a suitable notion of abduction under repair semantics and propose a set of minimality criteria that guides abduction towards `useful' hypotheses. We provide initial complexity results on deciding existence of and verifying abductive solutions with these criteria, under different repair semantics and for the description logics DL-Lite and EL_bot.}}, author = {{Haak, Anselm and Koopmann, Patrick and Mahmood, Yasir and Turhan, Anni-Yasmin}}, booktitle = {{arXiv:2507.21955}}, title = {{{Why not? Developing ABox Abduction beyond Repairs}}}, year = {{2025}}, } @inproceedings{63888, author = {{Haak, Anselm and Koopmann, Patrick and Mahmood, Yasir and Turhan, Anni-Yasmin}}, booktitle = {{Proceedings of the 38th International Workshop on Description Logics - DL 2025}}, editor = {{Tendera, Lidia and Ibanez Garcia, Yazmin and Koopmann, Patrick}}, location = {{Opole, Poland}}, title = {{{Why not? Developing ABox Abduction beyond Repairs}}}, year = {{2025}}, } @inproceedings{59910, abstract = {{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.}}, author = {{Mahmood, Yasir and Hecher, Markus and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{Proceedings of the AAAI Conference on Artificial Intelligence}}, issn = {{2374-3468}}, number = {{14}}, pages = {{15058--15066}}, publisher = {{Association for the Advancement of Artificial Intelligence (AAAI)}}, title = {{{Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases}}}, doi = {{10.1609/aaai.v39i14.33651}}, volume = {{39}}, year = {{2025}}, } @article{59912, abstract = {{Abstract We study the expressivity and the complexity of various logics in probabilistic team semantics with the Boolean negation. In particular, we study the extension of probabilistic independence logic with the Boolean negation, and a recently introduced logic first-order theory of random variables with probabilistic independence. We give several results that compare the expressivity of these logics with the most studied logics in probabilistic team semantics setting, as well as relating their expressivity to a numerical variant of second-order logic. In addition, we introduce novel entropy atoms and show that the extension of first-order logic by entropy atoms subsumes probabilistic independence logic. Finally, we obtain some results on the complexity of model checking, validity and satisfiability of our logics.}}, author = {{Hannula, Miika and Hirvonen, Minna and Kontinen, Juha and Mahmood, Yasir and Meier, Arne and Virtema, Jonni}}, issn = {{0955-792X}}, journal = {{Journal of Logic and Computation}}, number = {{3}}, publisher = {{Oxford University Press (OUP)}}, title = {{{Logics with probabilistic team semantics and the Boolean negation}}}, doi = {{10.1093/logcom/exaf021}}, volume = {{35}}, year = {{2025}}, } @unpublished{61066, abstract = {{Argumentation is a central subarea of Artificial Intelligence (AI) for modeling and reasoning about arguments. The semantics of abstract argumentation frameworks (AFs) is given by sets of arguments (extensions) and conditions on the relationship between them, such as stable or admissible. Today's solvers implement tasks such as finding extensions, deciding credulous or skeptical acceptance, counting, or enumerating extensions. While these tasks are well charted, the area between decision, counting/enumeration and fine-grained reasoning requires expensive reasoning so far. We introduce a novel concept (facets) for reasoning between decision and enumeration. Facets are arguments that belong to some extensions (credulous) but not to all extensions (skeptical). They are most natural when a user aims to navigate, filter, or comprehend the significance of specific arguments, according to their needs. We study the complexity and show that tasks involving facets are much easier than counting extensions. Finally, we provide an implementation, and conduct experiments to demonstrate feasibility.}}, author = {{Fichte, Johannes and Fröhlich, Nicolas and Hecher, Markus and Lagerkvist, Victor and Mahmood, Yasir and Meier, Arne and Persson, Jonathan}}, booktitle = {{arXiv:2505.10982}}, title = {{{Facets in Argumentation: A Formal Approach to Argument Significance}}}, year = {{2025}}, } @inproceedings{63572, author = {{Demir, Caglar and Yekini, Moshood Olawale and Röder, Michael and Mahmood, Yasir and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783032060655}}, issn = {{0302-9743}}, location = {{Porto}}, publisher = {{Springer Nature Switzerland}}, title = {{{Tree-Based OWL Class Expression Learner over Large Graphs}}}, doi = {{10.1007/978-3-032-06066-2_29}}, year = {{2025}}, } @inbook{54580, author = {{Mahmood, Yasir and Virtema, Jonni and Barlag, Timon and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783031569395}}, issn = {{0302-9743}}, publisher = {{Springer Nature Switzerland}}, title = {{{Computing Repairs Under Functional and Inclusion Dependencies via Argumentation}}}, doi = {{10.1007/978-3-031-56940-1_2}}, year = {{2024}}, } @article{54092, author = {{Kontinen, Juha and Mahmood, Yasir and Meier, Arne and Vollmer, Heribert}}, journal = {{Mathematical Structures in Computer Science}}, keywords = {{dice mahmood}}, pages = {{1--15}}, publisher = {{Cambridge University Press}}, title = {{{Parameterized Complexity of Weighted Team Definability}}}, doi = {{10.1017/S0960129524000033}}, year = {{2024}}, } @article{59911, abstract = {{AbstractIn this article, we study the complexity of weighted team definability for logics with team semantics. This problem is a natural analog of one of the most studied problems in parameterized complexity, the notion of weighted Fagin-definability, which is formulated in terms of satisfaction of first-order formulas with free relation variables. We focus on the parameterized complexity of weighted team definability for a fixed formula $\varphi$ of central team-based logics. Given a first-order structure $\mathcal{A}$ and the parameter value $k\in \mathbb N$ as input, the question is to determine whether $\mathcal{A},T\models \varphi$ for some team T of size k. We show several results on the complexity of this problem for dependence, independence, and inclusion logic formulas. Moreover, we also relate the complexity of weighted team definability to the complexity classes in the well-known W-hierarchy as well as paraNP.}}, author = {{Kontinen, Juha and Mahmood, Yasir and Meier, Arne and Vollmer, Heribert}}, issn = {{0960-1295}}, journal = {{Mathematical Structures in Computer Science}}, number = {{5}}, pages = {{375--389}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Parameterized complexity of weighted team definability}}}, doi = {{10.1017/s0960129524000033}}, volume = {{34}}, year = {{2024}}, } @inproceedings{58377, abstract = {{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.}}, author = {{Mahmood, Yasir and Hecher, Markus and Ngonga Ngomo, Axel-Cyrille}}, title = {{{Dung's Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases}}}, doi = {{10.1609/AAAI.V39I14.33651}}, year = {{2024}}, } @inbook{57238, abstract = {{Abstract argumentation is a popular toolkit for modeling, evaluating, and comparing arguments. Relationships between arguments are specified in argumentation frameworks (AFs), and conditions are placed on sets (extensions) of arguments that allow AFs to be evaluated. For more expressiveness, AFs are augmented with acceptance conditions on directly interacting arguments or a constraint on the admissible sets of arguments, resulting in dialectic frameworks or constrained argumentation frameworks. In this paper, we consider flexible conditions for rejecting an argument from an extension, which we call rejection conditions (RCs). On the technical level, we associate each argument with a specific logic program. We analyze the resulting complexity, including the structural parameter treewidth. Rejection AFs are highly expressive, giving rise to natural problems on higher levels of the polynomial hierarchy.}}, author = {{Fichte, Johannes K. and Hecher, Markus and Mahmood, Yasir and Meier, Arne}}, booktitle = {{Frontiers in Artificial Intelligence and Applications}}, isbn = {{9781643685489}}, issn = {{0922-6389}}, location = {{Santiago de Compostela, Spain}}, publisher = {{IOS Press}}, title = {{{Rejection in Abstract Argumentation: Harder Than Acceptance?}}}, doi = {{10.3233/faia240867}}, year = {{2024}}, } @inproceedings{55655, abstract = {{Argumentation is a well-established formalism for nonmonotonic reasoning, with popular frameworks being Dung’s abstract argumentation (AFs) or logic-based argumentation (Besnard-Hunter’s framework). Structurally, a set of formulas forms support for a claim if it is consistent, subset-minimal, and implies the claim. Then, an argument comprises support and a claim. We observe that the computational task (ARG) of asking for support of a claim in a knowledge base is “brave”, since many claims with a single support are accepted. As a result, ARG falls short when it comes to the question of confidence in a claim, or claim strength. In this paper, we propose a concept for measuring the (acceptance) strength of claims, based on counting supports for a claim. Further, we settle classical and structural complexity of counting arguments favoring a given claim in propositional knowledge bases (KBs). We introduce quantitative reasoning to measure the strength of claims in a KB and to determine the relevance strength of a formula for a claim.}}, author = {{Hecher, Markus and Mahmood, Yasir and Meier, Arne and Schmidt, Johannes}}, booktitle = {{Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence}}, publisher = {{International Joint Conferences on Artificial Intelligence Organization}}, title = {{{Quantitative Claim-Centric Reasoning in Logic-Based Argumentation}}}, doi = {{10.24963/ijcai.2024/377}}, year = {{2024}}, } @unpublished{57814, abstract = {{We study consistent query answering via different graph representations. First, we introduce solution-conflict hypergraphs in which nodes represent facts and edges represent either conflicts or query solutions. Considering a monotonic query and a set of antimonotonic constraints, we present an explicit algorithm for counting the number of repairs satisfying the query based on a tree decomposition of the solution-conflict hypergraph. The algorithm not only provides fixed-parameter tractability results for data complexity over expressive query and constraint classes, but also introduces a novel and potentially implementable approach to repair counting. Second, we consider the Gaifman graphs arising from MSO descriptions of consistent query answering. Using a generalization of Courcelle's theorem, we then present fixed-parameter tractability results for combined complexity over expressive query and constraint classes.}}, author = {{Hankala, Teemu and Hannula, Miika and Mahmood, Yasir and Meier, Arne}}, booktitle = {{arXiv:2412.08324}}, title = {{{Parameterised Complexity of Consistent Query Answering via Graph Representations}}}, year = {{2024}}, } @article{54577, abstract = {{Argumentation is a well-established formalism dealing with conflicting information by generating and comparing arguments. It has been playing a major role in AI for decades. In logic-based argumentation, we explore the internal structure of an argument. 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 article, 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 (Creignou et al. 2014 and Parson et al., 2003) 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 (STOC 1978) and then study different parameterizations for each of the fragments. We 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 (para-NP and beyond).}}, author = {{Mahmood, Yasir and Meier, Arne and Schmidt, Johannes}}, issn = {{1529-3785}}, journal = {{ACM Transactions on Computational Logic}}, number = {{3}}, pages = {{1--25}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{Parameterized Complexity of Logic-based Argumentation in Schaefer’s Framework}}}, doi = {{10.1145/3582499}}, volume = {{24}}, year = {{2023}}, } @inproceedings{54578, abstract = {{Argumentation is a well-established formalism for nonmonotonic reasoning and a vibrant area of research in AI. Claim-augmented argumentation frameworks (CAFs) have been introduced to deploy a conclusion-oriented perspective. CAFs expand argumentation frameworks by an additional step which involves retaining claims for an accepted set of arguments. We introduce a novel concept of a justification status for claims, a quantitative measure of extensions supporting a particular claim. The well-studied problems of credulous and skeptical reasoning can then be seen as simply the two endpoints of the spectrum when considered as a justification level of a claim. Furthermore, we explore the parameterized complexity of various reasoning problems for CAFs, including the quantitative reasoning for claim assertions. We begin by presenting a suitable graph representation that includes arguments and their associated claims. Our analysis includes the parameter treewidth, and we present decomposition-guided reductions between reasoning problems in CAF and the validity problem for QBF.}}, author = {{Fichte, Johannes K. and Hecher, Markus and Mahmood, Yasir and Meier, Arne}}, booktitle = {{Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence}}, publisher = {{International Joint Conferences on Artificial Intelligence Organization}}, title = {{{Quantitative Reasoning and Structural Complexity for Claim-Centric Argumentation}}}, doi = {{10.24963/ijcai.2023/358}}, year = {{2023}}, } @inbook{54579, author = {{Mahmood, Yasir and Virtema, Jonni}}, booktitle = {{Logic, Language, Information, and Computation}}, isbn = {{9783031397837}}, issn = {{0302-9743}}, publisher = {{Springer Nature Switzerland}}, title = {{{Parameterized Complexity of Propositional Inclusion and Independence Logic}}}, doi = {{10.1007/978-3-031-39784-4_17}}, year = {{2023}}, } @inproceedings{54089, author = {{Hannula, Miika and Hirvonen, Minna and Kontinen, Juha and Mahmood, Yasir and Meier, Arne and Virtema, Jonni}}, booktitle = {{18th European Conference on Logics in Artificial Intelligence, JELIA 2023, Proceedings}}, keywords = {{dice enexa mahmood}}, title = {{{Logics with probabilistic team semantics and the Boolean negation}}}, year = {{2023}}, }