@article{MTMT:37013474, title = {Relational games and repeated bayesian relational games with decision tables for influencer marketing}, url = {https://m2.mtmt.hu/api/publication/37013474}, author = {Nghia, Vu Duc and Demetrovics, János and Thi, Vu Duc and Son, Nguyen Hoang and Giang, Nguyen Long}, doi = {10.1007/s00500-025-11043-7}, journal-iso = {SOFT COMPUT}, journal = {SOFT COMPUTING}, volume = {30}, unique-id = {37013474}, issn = {1432-7643}, year = {2026}, eissn = {1433-7479}, pages = {1637-1663} } @article{MTMT:37353270, title = {Deterministic Q-Learning with Relational Game Theory: Polynomial-Time Convergence to Minimal Winning Coalitions in Symmetric Influence Networks and Extension}, url = {https://m2.mtmt.hu/api/publication/37353270}, author = {Vu, Duc Nghia and Demetrovics, János}, doi = {10.3390/math14091526}, journal-iso = {MATHEMATICS-BASEL}, journal = {MATHEMATICS}, volume = {14}, unique-id = {37353270}, abstract = {This paper presents a theoretically grounded integration of deterministic Q-learning with relational game theory (QLRG) for efficiently identifying minimal winning coalitions in Online Social Networks (OSNs). We address the fundamental challenge that coalition formation is NP-hard under traditional approaches by leveraging structural properties of relational dependencies and Armstrong’s axioms to transform the problem into one solvable in polynomial time. Our framework reduces the state space from exponential O(2n) to O(n2) through a sufficient statistic representation based on coalition size, follower reach, and terminal status, while achieving O(n4) time complexity under deterministic, static, and sufficiently symmetric influence structures. The QLRG framework introduces three critical innovations: (1) a principled agent selection mechanism derived directly from the Q-function that eliminates heuristic weight tuning; (2) a formal Boost action defined through temporal closure operators that captures influence spread dynamics; and (3) a constrained MDP formulation that enforces relational consistency through action elimination rather than penalty terms. We prove that the Bellman optimality operator forms a contraction mapping, guaranteeing deterministic convergence to optimal policies with established rates of O(1/√k) for decreasing learning rates or linear convergence up to bias for constant rates. To bridge the gap between this idealized model and the asymmetry inherent in real OSNs, we further develop a cluster-based sufficient statistics approach. By partitioning the network into communities with bounded internal variation, we relax the global symmetry requirement while preserving polynomial state space complexity, and obtaining a single within-community swap changes the optimal Q-value by at most εi1−γ, which is a local Lipschitz continuity result. The implications of this are both theoretical and practical, and they form the bedrock for relaxing the global symmetry assumption in the QLRG framework. Empirical validation on synthetic networks satisfying the symmetry assumption demonstrates that QLRG consistently identifies minimal winning coalitions matching the optimal solutions found by exhaustive search, while operating with polynomial-time complexity. Unlike conventional approaches, our framework simultaneously satisfies four critical properties: deterministic convergence, policy optimality, minimal coalition identification, and computational tractability. The work bridges computational social science and operations research, providing a mathematically rigorous foundation for strategic decision-making in influencer marketing and coalition formation. While the framework requires symmetry assumptions that may only hold approximately in real-world OSNs, it establishes an idealized baseline for future extensions addressing stochasticity, dynamics, and partial observability. This research represents a paradigm shift from empirical improvements to theoretically grounded convergence guarantees for coalition formation problems, demonstrating how structural mathematical insights can transform intractable problems into efficiently solvable ones without sacrificing solution quality.}, year = {2026}, eissn = {2227-7390}, pages = {1-47}, orcid-numbers = {Vu, Duc Nghia/0009-0006-2088-5506} } @article{MTMT:37486643, title = {Subgraphs of the projective norm graph}, url = {https://m2.mtmt.hu/api/publication/37486643}, author = {Bayer, Tomas and Mészáros, Tamás and Rónyai, Lajos and Szabó, Tibor}, doi = {10.1017/fms.2026.10245}, journal-iso = {FORUM MATH SIGMA}, journal = {FORUM OF MATHEMATICS SIGMA}, volume = {14}, unique-id = {37486643}, issn = {2050-5094}, abstract = {The limited dependence between the additive and the multiplicative structure of fields is in the background of a number of explicit constructions of various types of pseudorandom objects. In this direction we study the size of the intersection of (the additive) translates of fibers of the (multiplicative) norm function over finite fields. Besides extending earlier upper bounds, our main focus here is on obtaining lower bounds. From our results we conclude several consequences in extremal combinatorics. Our motivation is the projective norm graph NG(, t) and its small subgraph statistics. NG(, t) provides a tight construction for the Turán number of complete bipartite graphs Kt,s with s > (t − 1)!; in particular, it does not contain Kt,(t−1)!+1. Yet, for t ≥ 4 it is not even known whether NG(, t) contains Kt,t. The determination of the largest integer s(t), such that NG(, t) contains Kt,s(t) for all large enough prime powers is an important open question with far-reaching consequences, and the best known bounds, t − 1 ≤ s(t) ≤ (t − 1)!, are very far apart. In this paper we settle the first open case and establish s(4) = 6. Along the way we also count subgraphs of NG(, t) isomorphic to H, for any fixed 3-degenerate graph H, and find that projective norm graphs are quasirandom with respect to these parameters. These results go beyond the consequences of the Expander Mixing Lemma and also imply extensions of the work of Alon and Shikhelman on generalized Turán numbers. Finally, we also give an elementary proof of the K4,s-freeness of NG(, t) for s = 6( it=−04 i) + 1. This was known before for t = 4 only, via a less direct algebro-geometric argument. © The Author(s), 2026. Published by Cambridge University Press.}, year = {2026}, eissn = {2050-5094}, pages = {1-42} } @article{MTMT:37545652, title = {Cluster-Based Q-Learning Relational Game (C-QLRG): A Practical Relaxation for Asymmetric Online Social Networks}, url = {https://m2.mtmt.hu/api/publication/37545652}, author = {Vu, Duc Nghia and Demetrovics, János}, doi = {10.3390/ai7060231}, journal-iso = {AI}, journal = {AI}, volume = {7}, unique-id = {37545652}, abstract = {The Q-Learning Relational Game (QLRG) framework provides a theoretically rigorous method for identifying minimal winning coalitions in online social networks (OSNs) under the restrictive assumption of global agent symmetry or uniform matroid structure. Real-world OSNs, however, exhibit significant asymmetry. This paper introduces the Cluster-Based Q-Learning Relational Game (C-QLRG), a practical extension that relaxes the global symmetry requirement by leveraging community structure. We partition the agent set into communities with bounded internal variation and represent the state solely by community membership counts of the seed set. Because the closure operator already captures all eventual influence spread, the problem reduces to a sequential seed selection task where the agent decides, at each step, from which community to add the next seed. We prove that the optimal Q-function of a suitably regularized reach-efficiency objective is Lipschitz continuous and derive a performance bound for the learned policy. The full algorithm is presented, and its complexity is analyzed. Empirical evaluations on a synthetic asymmetric network and Zachary’s Karate Club demonstrate that C-QLRG is highly sensitive to reward parameters, where default settings lead to premature stopping, but parameter tuning combined with a corrected minimality verification recovers high-efficiency coalitions by removing non-contributing agents. With tuned parameters, C-QLRG produces a near-winning coalition of size 11 and 99% reach on the synthetic network, surpassing the greedy baseline’s efficiency (size 12) despite a one-node coverage gap, while identifying the optimal winning coalition of size 1 on the Karate Club dataset, matching all baselines. The framework thus offers a principled trade-off between model fidelity and scalability, with the reward design choice being critical for practical deployment.}, year = {2026}, eissn = {2673-2688}, pages = {231}, orcid-numbers = {Vu, Duc Nghia/0009-0006-2088-5506} } @article{MTMT:37545660, title = {Relational and Weighted Cost-Relational Cooperative Games for Influencer Coalition Optimization in Environmental Sustainability: Algorithms, Complexity, and Cost Efficiency}, url = {https://m2.mtmt.hu/api/publication/37545660}, author = {Vu, Duc Nghia and Demetrovics, János and Nguyen, Hoang Son}, doi = {10.3390/computers15070410}, journal-iso = {COMPUTERS}, journal = {COMPUTERS}, volume = {15}, unique-id = {37545660}, issn = {2073-431X}, abstract = {This paper addresses the critical challenge of identifying cost-effective coalitions of social media influencers to promote environmental sustainability (ES) messages under budget constraints. Traditional influencer marketing often relies on heuristics that ignore relational dependencies and heterogeneous agent costs, leading to redundant coverage and suboptimal resource allocation. To overcome these limitations, we introduce a novel Relational Cooperative Game (RG) framework that formalizes pre-determined dependencies among influencers and followers using closure operators, enabling a portfolio of polynomial-time identification algorithms for Minimal Winning Coalitions (MWCs). We further extend this model to the Weighted Cost-Relational Game (WCRG) to optimize campaigns with heterogeneous influencer costs. We prove that finding a Minimum-Cost Winning Coalition (MCWC) is NP-hard via reduction from weighted set cover and propose two complementary algorithms: (1) a Greedy Cost–Benefit (GCB) algorithm that operates in polynomial time and empirically achieves optimal solutions across all tested instances; a logarithmic approximation guarantee is established for the restricted single-antecedent model; and (2) an Integer Linear Programming (ILP) formulation enhanced with Strongly Connected Component (SCC) preprocessing to handle cyclic dependencies and yield exact optimal solutions for moderate instances. Extensive empirical validation, ranging from a representative six-agent cyclic scenario to large-scale synthetic networks (up to 300 agents), confirms the framework’s robustness and scalability. Results demonstrate that GCB consistently achieves optimal solutions (approximation ratio = 1.000×) with subsecond runtime (<0.2 s) and minimal memory overhead (<50 MB), while ILP-SCC leverages graph condensation for rapid exact solving. Compared to size-based baselines, WCRG achieves up to 95.2% cost savings by systematically leveraging cost-efficient micro-influencers, empirically validating that minimizing coalition size does not guarantee cost efficiency. These findings establish WCRG as a scalable, budget-aware optimization toolkit for maximizing the impact of sustainability campaigns through relational coalition design.}, year = {2026}, eissn = {2073-431X}, pages = {410}, orcid-numbers = {Vu, Duc Nghia/0009-0006-2088-5506; Nguyen, Hoang Son/0000-0003-0468-8327} } @article{MTMT:35578762, title = {Connectivity Preserving Graph Sequences for Routing Arborescence Construction}, url = {https://m2.mtmt.hu/api/publication/35578762}, author = {Tapolcai, János and Babarczi, Péter and Brányi, Balázs and Ho, Pin-Han and Rónyai, Lajos}, doi = {10.1109/JSAC.2025.3528812}, journal-iso = {IEEE J SEL AREA COMM}, journal = {IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS}, volume = {43}, unique-id = {35578762}, issn = {0733-8716}, year = {2025}, eissn = {1558-0008}, pages = {484-494}, orcid-numbers = {Babarczi, Péter/0000-0003-1644-2172} } @inproceedings{MTMT:36428787, title = {A Generic Framework for Cross-Chain Atomic Swaps of Digital Tokens}, url = {https://m2.mtmt.hu/api/publication/36428787}, author = {Tapolcai, János and Ladóczki, Bence and Rónyai, Lajos}, booktitle = {2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS)}, doi = {10.1109/ICDCS63083.2025.00011}, unique-id = {36428787}, abstract = {Decentralisation is one of the most important structural principles of blockchains and it should be present in all aspects of these systems. There is a growing scientific effort to develop protocols that enable the exchange of digital assets between two heterogeneous blockchains without a third-party arbitrator. We investigate the scenario where two parties wish to exchange digital tokens and run a swap protocol without the intervention of a third party. This is a complex and cooperative process for which - in a trust-less environment - atomicity and fairness must be ensured. While smart contracts provide a convenient way to achieve this, we want to ensure that the two parties leave no traceable data on the respective chains. The challenge here is that the two digital assets can reside on different chains with different signature schemes. Tackling these issues, we present a protocol description for the exchange of two arbitrary cryptocurrencies. A generic standard for atomic swap implementations in terms of the required cryptographic primitives is given. Additionally, we derive a protocol for the necessary interactions between two arbitrary chains using these primitives. To demonstrate applicability, we illustrate how this protocol can be instantiated with Schnorr and BLS signatures. © 2025 Elsevier B.V., All rights reserved.}, keywords = {Atoms; CHAINS; Third parties; Information Systems; Interoperability; Cryptography; decentralisation; Atomic; Atomic; blockchain; blockchain; Generic frameworks; Electronic money; SWAP; BLS; BLS; Digital assets; Block-chain; schnorr; swaps; Digital tokens; Schnorr}, year = {2025}, pages = {12-22} } @misc{MTMT:36476574, title = {Shortlisted Problems with Solutions. 66th International Mathematical Olympiad, Sunshine Coast QLD, Australia, 10\th--20\th July 2025}, url = {https://m2.mtmt.hu/api/publication/36476574}, author = {Agisilaou, Adrian and Atkins, Ross and Elvey Price, Andrew and Gong, Sherry and Guo, Ivan and He, Grace and Dongryul, Kim and Kós, Géza and Lim, Jeck and Lorenzo García, Elisa and Machino, Yuka and Maret, Arnaud and Mathews, Daniel and McNamara, Peter and Anant, Mudgal and Offer, Alan and Ragavan, Seyoon and Ren, Michael and Tuffley, Christopher and Wang, Bin and Wanless, Ian and Wong, Rachel and Wong, Sampson and Yijun, Yao and Yip, Fredy}, unique-id = {36476574}, year = {2025}, pages = {1-97}, orcid-numbers = {Kós, Géza/0000-0002-2221-4558} } @article{MTMT:36847089, title = {Approximate Relational Games For Green Influencer Marketing Optimization}, url = {https://m2.mtmt.hu/api/publication/36847089}, author = {Vu, Nghia D. and Demetrovics, János and Nguyen, Giang L. and Vu, Thi D. and Nguyen, Son H. and Nguyen, Kuop G.}, doi = {10.1109/ACCESS.2025.3605398}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {13}, unique-id = {36847089}, year = {2025}, eissn = {2169-3536}, pages = {158967-158983}, orcid-numbers = {Vu, Nghia D./0009-0006-2088-5506; Nguyen, Giang L./0000-0001-6184-1469; Nguyen, Kuop G./0009-0000-3770-574X} } @article{MTMT:33645181, title = {The automorphism group of projective norm graphs}, url = {https://m2.mtmt.hu/api/publication/33645181}, author = {Bayer, T and Mészáros, T and Rónyai, Lajos and Szabó, T}, doi = {10.1007/s00200-022-00590-3}, journal-iso = {APPL ALGEBR ENG COMM}, journal = {APPLICABLE ALGEBRA IN ENGINEERING COMMUNICATION AND COMPUTING}, volume = {35}, unique-id = {33645181}, issn = {0938-1279}, abstract = {The projective norm graphs are central objects to extremal combinatorics. They appear in a variety of contexts, most importantly they provide tight constructions for the Tur & aacute;n number of complete bipartite graphs K-t,K-s with s > (t - 1)! . In this note we deepen their understanding further by determining their automorphism group.}, keywords = {LOWER BOUNDS; Finite fields; Ramsey numbers; Subgraphs; Computer Science, Interdisciplinary Applications; Computer Science, Theory & Methods; Turan problems; Norm graphs; Norm equations}, year = {2024}, eissn = {1432-0622}, pages = {875-886} }