社会网络中无嫉妒资源分配的参数化复杂性

E. Eiben, R. Ganian, Thekla Hamm, S. Ordyniak
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引用次数: 12

摘要

我们考虑以无嫉妒(并且在适用的情况下,按比例)方式在代理之间分配资源的经典问题。最近,通过引入社会网络的概念对基本模型进行了丰富,该概念允许捕获代理可能没有关于所有资源分配的完整信息的情况。我们通过考虑捕获网络结构属性和智能体与物品之间相似性的自然参数,开始了这些资源分配问题的参数化复杂性的研究。特别是,我们表明,只要社会网络具有有限的树宽或有限的团宽,即使是所考虑的问题的非常一般的片段也可以处理。我们用匹配的下界来补充我们的结果,这表明我们的算法不能得到实质性的改进。
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Parameterized Complexity of Envy-Free Resource Allocation in Social Networks
We consider the classical problem of allocating resources among agents in an envy-free (and, where applicable, proportional) way. Recently, the basic model was enriched by introducing the concept of a social network which allows to capture situations where agents might not have full information about the allocation of all resources. We initiate the study of the parameterized complexity of these resource allocation problems by considering natural parameters which capture structural properties of the network and similarities between agents and items. In particular, we show that even very general fragments of the considered problems become tractable as long as the social network has bounded treewidth or bounded clique-width. We complement our results with matching lower bounds which show that our algorithms cannot be substantially improved.
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