Adaptive Coevolutionary Networks -- A Review Export

@misc{citeulike:1719011, abstract = {Adaptive networks appear in many biological applications. They combine topological evolution of the network with dynamics in the network nodes. Recently, the dynamics of adaptive networks has been investigated in a number of parallel studies from different fields, ranging from genomics to game theory. Here we review these recent developments and show that they can be viewed from a unique angle. We demonstrate that all these studies are characterized by common themes, most prominently: complex dynamics and robust topological self-organization based on simple local rules.}, archivePrefix = {arXiv}, author = {Gross, Thilo and Blasius, Bernd}, citeulike-article-id = {1719011}, citeulike-linkout-0 = {http://arxiv.org/abs/0709.1858}, citeulike-linkout-1 = {http://arxiv.org/pdf/0709.1858}, comment = {Summary: Adaptive networks (I am loath to stretch the term ``coevolutionary'' to this) are ones in which the `evolution of the topology is invariable linked to the state of the network and vice versa. Examples given include: food webs, social networks (topology may change as conflicting views spread), socio-economic / game theory models on networks, epidemiological (SIS) models (agents break contact with infected people), ateriogenesis (angiogenesis). The paper consider several models with different (but related) rewiring rules that seem to self-organise towards the same types of topology. It also considers some adaptive networks in which nodes specialise towards typical roles / relationships. Interesting quote: ``While adaptive networks can add realism to previously studied games like the prisoner's dilemma, they also give rise to a new class of games. In these games, the players do not try to maximize an abstract payoff, but struggle to achieve an advantageous position on the network. For example, in a social network a position of high centrality is certainly desirable. The struggle for such a position is studied in models by Rosval and Sneppen.''}, day = {12}, eprint = {0709.1858}, keywords = {adaptation, coevolution, network}, month = {Sep}, posted-at = {2007-10-17 07:34:39}, priority = {0}, title = {Adaptive Coevolutionary Networks \&\#45;\&\#45; A Review}, url = {http://arxiv.org/abs/0709.1858}, year = {2007} }

TY - ELEC ID - citeulike:1719011 L3 - citeulike-article-id:1719011 N2 - Adaptive networks appear in many biological applications. They combine topological evolution of the network with dynamics in the network nodes. Recently, the dynamics of adaptive networks has been investigated in a number of parallel studies from different fields, ranging from genomics to game theory. Here we review these recent developments and show that they can be viewed from a unique angle. We demonstrate that all these studies are characterized by common themes, most prominently: complex dynamics and robust topological self-organization based on simple local rules. TI - Adaptive Coevolutionary Networks -- A Review KW - adaptation KW - coevolution KW - network N1 - Summary: Adaptive networks (I am loath to stretch the term ``coevolutionary'' to this) are ones in which the `evolution of the topology is invariable linked to the state of the network and vice versa. Examples given include: food webs, social networks (topology may change as conflicting views spread), socio-economic / game theory models on networks, epidemiological (SIS) models (agents break contact with infected people), ateriogenesis (angiogenesis). The paper consider several models with different (but related) rewiring rules that seem to self-organise towards the same types of topology. It also considers some adaptive networks in which nodes specialise towards typical roles / relationships. Interesting quote: ``While adaptive networks can add realism to previously studied games like the prisoner's dilemma, they also give rise to a new class of games. In these games, the players do not try to maximize an abstract payoff, but struggle to achieve an advantageous position on the network. For example, in a social network a position of high centrality is certainly desirable. The struggle for such a position is studied in models by Rosval and Sneppen.'' AU - Gross, Thilo AU - Blasius, Bernd PY - 2007/Sep/12/ UR - http://arxiv.org/abs/0709.1858 ER -