Adaptive Local Information Transfer in Random Boolean Networks
نویسندگان
چکیده
منابع مشابه
Measuring Mutual Information in Random Boolean Networks
During the last few years an area of active research in the field of complex systems is that of their information storing and processing abilities. Common opinion has it that the most interesting beaviour of these systems is found “at the edge of chaos”, which would seem to suggest that complex systems may have inherently non-trivial information proccesing abilities in the vicinity of sharp pha...
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Random Boolean networks (RBNs) are frequently employed for modelling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive RBN (HARBN) as a system consisting of distinct adaptive RBNs – subnetworks – connected by a set of permanent interlinks. Information measures and internal subnetworks topology of HARBN coevolve an...
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The amount of mutual information contained in the time series of two elements gives a measure of how well their activities are coordinated. In a large, complex network of interacting elements, such as a genetic regulatory network within a cell, the average of the mutual information over all pairs, , is a global measure of how well the system can coordinate its internal dynamics. We study thi...
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Attractors represent the long-term behaviors of Random Boolean Networks. We study how the amount of information propagated between the nodes when on an attractor, as quantified by the average pairwise mutual information (I(A)), relates to the robustness of the attractor to perturbations (R(A)). We find that the dynamical regime of the network affects the relationship between I(A) and R(A). In t...
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ژورنال
عنوان ژورنال: Artificial Life
سال: 2017
ISSN: 1064-5462,1530-9185
DOI: 10.1162/artl_a_00224