Fair division is typically framed from a centralized perspective. However, in practice resource allocation often occurs via decentralized networks. We study a decentralized variant of fair division inspired by altruistic dynamics observed in behavioral economics and other practical settings. We develop an approach for decentralized fair division and compare it with a centralized approach with respect to fairness and social welfare guarantees. Our decentralized model can be seen as a relaxation of previous models of sequential exchange, in light of impossibility results concerning the inability of those models to achieve desirable outcomes. We find that the two models of resource allocation offer contrasting fairness and social welfare guarantees, and map out how these guarantees depend on valuations and other model parameters. We further show conditions under which a mix of the two approaches outperforms either approach in isolation. Despite the simplicity of our decentralized model, we show that under appropriate conditions it can ensure high-quality allocative decisions in an efficient fashion.

翻译：公平分配问题通常从中心化视角进行探讨。然而在实践中，资源分配往往通过去中心化网络实现。本研究受行为经济学及其他实践场景中观察到的利他动态启发，提出一种去中心化公平分配模型。我们构建了去中心化公平分配方法，并从公平性与社会福利保障两个维度与中心化方法进行对比。鉴于既有序列交换模型无法达成理想分配结果的不可行性结论，本研究的去中心化模型可视为对先前模型的松弛化改进。研究发现，两种资源分配模型呈现出截然不同的公平性与社会福利保障特性，并系统揭示了这些保障机制如何受估值函数及其他模型参数的影响。我们进一步论证了混合两种方法在特定条件下能够超越单一方法的性能边界。尽管所提出的去中心化模型结构简洁，我们证明在适当条件下该模型能以高效方式确保高质量的分配决策。