Emergent Mind

Random Walks Performed by Topologically-Specific Agents on Complex Networks

(2312.00859)
Published Dec 1, 2023 in physics.soc-ph and cs.GR

Abstract

Random walks by single-node agents have been systematically conducted on various types of complex networks in order to investigate how their topologies can affect the dynamics of the agents. However, by fitting any network node, these agents do not engage in topological interactions with the network. In the present work, we describe random walks on complex networks performed by agents that are actually small graphs. These agents can only occupy admissible portions of the network onto which they fit topologically, hence their name being taken as topologically-specific agents. These agents are also allowed to move to adjacent subgraphs in the network, which have each node adjacent to the original respective node of the agent. Two types of random walks are considered here: uniformly random and influenced by an external field. The performance of the random walks performed by three types of topologically-specific agents is studied respectively to the obtained coverage considering three types of complex networks (geometrical, Erd\H{o}s-R\'enyi, and Barab\'asi-Albert). The number of nodes displaced at each random walk step is also obtained and analyzed. Several interesting results are reported and discussed, including the fact that, despite its intrinsic node degree heterogeneity, Barab\'asi-Albert networks tend to allow relatively smooth and effective coverage by all the considered topologically-specific agents. Erd\H{o}s-R\'enyi networks were also found to yield large dispersions of node coverage. In addition, the triangle agent was found to allow more effective random walks respectively to any of the three considered networks.

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