合作超加性对策中模糊联盟的形成

M. He, Xudong Luo, N. Jennings, M. Wooldridge
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引用次数: 3

摘要

研究了合作超加性对策中自利益主体的模糊联盟形成问题。特别是,我们考虑这样一种情况,即给定许多任务,服务提供者代理从环境中可用的伙伴中寻找合作伙伴。这些潜在的合作伙伴可以将他们的资源投入到多个联盟中,这样做的目的是在他们参与的联盟中最大化预期Shapley值的总和。具体来说,我们开发了一种新的基于拍卖的模糊联盟形成算法,该算法使每个代理能够选择其最喜欢的联盟,然后通过同时进行的多条目英语拍卖找到它将实际参与的联盟。当拍卖结束时,每次拍卖中的活动出价代表将共同执行任务的代理集。然后,我们通过经验评估表明,我们的算法优于两个基准(仅允许清晰联盟和贪婪方法来模糊联盟),相对于联盟结构的总价值高达61.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forming Fuzzy Coalitions in Cooperative Superadditive Games
This paper studies fuzzy coalition formation for self-interested agents in cooperative superadditive games. In particular, we consider the situation, where, given a number of tasks, service provider agents seek partners from those available in the environment. These potential partners can commit their resources to multiple coalitions and, in so doing, aim to maximise the sum of the expected Shapley value in the coalitions in which they participate. Specifically, we develop a novel auction-based fuzzy coalition formation algorithm that enables each agent to choose its most preferred coalitions and then to find the coalitions it will actually participate in through simultaneous multiple entry English auctions. When the auction closes, the active bids in each auction represent the set of agents that will perform the task jointly. We then show, by empirical evaluation, that our algorithm outperforms two benchmarks (that allow only crisp coalitions and a greedy approach to fuzzy coalitions) by up to 61.3% with respect to the total value of the coalition structure.
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