Please use this identifier to cite or link to this item:
https://repositorio.ufba.br/handle/ri/13787
metadata.dc.type: | Artigo de Periódico |
Title: | Learning paths in complex networks |
Other Titles: | EPL |
Authors: | Cajueiro, Daniel Oliveira Andrade, Roberto Fernandes Silva |
metadata.dc.creator: | Cajueiro, Daniel Oliveira Andrade, Roberto Fernandes Silva |
Abstract: | This letter addresses the issue of learning shortest paths in complex networks, which is of utmost importance in real-life navigation. The approach has been partially motivated by recent progress in characterizing navigation problems in networks, having as extreme situations the completely ignorant (random) walker and the rich directed walker, which can pay for information that will guide to the target node along the shortest path. A learning framework based on a first-visit Monte Carlo algorithm is implemented, together with four independent measures that characterize the learning process. The methodology is applied to a number of network classes, as well as to networks constructed from actual data. The results indicate that the navigation difficulty and learning velocity are strongly related to the network topology. |
URI: | http://repositorio.ufba.br/ri/handle/ri/13787 |
Issue Date: | 2009 |
Appears in Collections: | Artigo Publicado em Periódico (FIS) |
Files in This Item:
File | Description | Size | Format | |
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0295-5075_87_5_58004.pdf | 512 kB | Adobe PDF | View/Open |
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