Efficient network navigation with partial information

Xiaoran Yan, O. Sporns, Andrea Avena-Koenigsberger
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引用次数: 1

Abstract

We propose a information theoretical framework to capture transition and information costs of network navigation models. Based on the minimum description length principle and the Markov decision process, we demonstrate that efficient global navigation can be achieved with only partial information. Additionally, we derived a scalable algorithm for optimal solutions under certain conditions. The proposed algorithm can be interpreted as a dynamical process on network, making it a useful tool for analysing and understanding navigation strategies on real world networks.
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具有部分信息的高效网络导航
我们提出了一个信息理论框架来捕捉网络导航模型的转移和信息成本。基于最小描述长度原理和马尔可夫决策过程,证明了仅使用部分信息就可以实现高效的全局导航。此外,我们还推导了在一定条件下求最优解的可扩展算法。该算法可以被解释为网络上的动态过程,使其成为分析和理解现实世界网络上导航策略的有用工具。
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