ODSS: Efficient Hybridization for Optimal Coalition Structure Generation
Narayan Changder, Samir Aknine, Sarvapali D. Ramchurn, Animesh Dutta
摘要
Coalition Structure Generation (CSG) is an NP-complete problem that remains difficult to solve on account of its complexity. In this paper, we propose an efficient hybrid algorithm for optimal coalition structure generation called ODSS. ODSS is a hybrid version of two previously established algorithms IDP (Rahwan and Jennings 2008) and IP (Rahwan et al. 2009). ODSS minimizes the overlapping between IDP and IP by dividing the whole search space of CSG into two disjoint sets of subspaces and proposes a novel subspace shrinking technique to reduce the size of the subspace searched by IP with the help of IDP. When compared to the state-of-the-art against a wide variety of value distributions, ODSS is shown to perform better by up to 54.15% on benchmark inputs.
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we show that many operations in ODP-IP involve redundant searches by IDP and IP. Hence, both IDP and IP perform many duplicated operations.
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we define a new technique to reduce the size of the subspace searched by IP with the help of IDP.
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- A Multiagent Path Search Algorithm for Large-Scale Coalition Structure GenerationRedha Taguelmimt, Samir Aknine, Djamila Boukredera, Narayan Changder 等AAAI 2025 · 被引用 1 次
- BRIDGE: Bi-level Reinforcement Learning for Dynamic Group Structure in Coalition Formation GamesShuqing Shi, Nam Phuong Tran, Hao Liang, Debmalya Mandal 等ICLR 2026
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