{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/quacs-variational-quantum-algorithm-for","title":"QuACS: Variational Quantum Algorithm for Coalition Structure Generation in Induced Subgraph Games","arxiv_id":"2304.07218","date":"2023-04-14","proceeding":null,"authors":["Supreeth Mysore Venkatesh","Antonio Macaluso","Matthias Klusch"],"abstract":"Coalition Structure Generation (CSG) is an NP-Hard problem in which agents are partitioned into mutually exclusive groups to maximize their social welfare. In this work, we propose QuACS, a novel hybrid quantum classical algorithm for Coalition Structure Generation in Induced Subgraph Games (ISGs). Starting from a coalition structure where all the agents belong to a single coalition, QuACS recursively identifies the optimal partition into two disjoint subsets. This problem is reformulated as a QUBO and then solved using QAOA. Given an $n$-agent ISG, we show that the proposed algorithm outperforms existing approximate classical solvers with a runtime of $\\mathcal{O}(n^2)$ and an expected approximation ratio of $92\\%$. Furthermore, it requires a significantly lower number of qubits and allows experiments on medium-sized problems compared to existing quantum solutions. To show the effectiveness of QuACS we perform experiments on standard benchmark datasets using quantum simulation.","url_abs":"https://arxiv.org/abs/2304.07218v1","url_pdf":"https://arxiv.org/pdf/2304.07218v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"quacs-variational-quantum-algorithm-for","repo_url":"https://github.com/supreethmv/QuACS","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}