Wed, 20 Aug 2008 22:04:35 BST CiteULike: VRadenovic's feedback http://www.citeulike.org/user/VRadenovic/tag/feedback CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/VRadenovic/article/2725307 <i>International Journal of Tags, Vol. 1, No. 1. (2008)</i> Vanja's Tag Holder Article T Holder International Journal of Tags, Vol. 1, No. 1. (2008) 2008-04-28T01:00:27-00:00 2008 International Journal of Tags 1 1 adaptability agency agent_based_model agility altruism ants artificial_intelligence artificial_life autocatalysis autopoiesis bayesian_network biology bounded_rationality c2 causality cellular_automata chaos coevolution cognition competition complex_system consciousness cooperation design_patterns economics ecosystem emergence entropy epidemiology evolution evolvability feedback flexibility game_theory gene_regulatory_networks genetic_algorithm genetics hierarchy highly_optimized_tolerance immune_system information_theory lamarckian leadership learning linguistics logistics memetics metrics military mission_command modelling multi_agent_system multi_level_selection multiscale multitasking network network_centric_warfare neural_networks neutral_evolution nonlinear novelty optimisation organisation organisation_management origin_of_life patterns phenotype philosophy phylogenetics pleiotropy quantum_mechanics religion replication resilience responsiveness robustness scale_free security selection self_assembly self_organisation self_organised_criticality sex simulation small_world social_network sociology software_engineering specialisation structure swarming symbiosis synergy system systems_engineering systems_theory terrorism trade tragedy_of_the_commons trust http://www.citeulike.org/user/VRadenovic/article/1870603 <i>(31 Jul 2005)</i><br /><br />We investigate a simple generative model for network formation. The model is designed to describe the growth of networks of kinship, trading, corporate alliances, or autocatalytic chemical reactions, where feedback is an essential element of network growth. The underlying graphs in these situations grow via a competition between cycle formation and node addition. After choosing a given node, a search is made for another node at a suitable distance. If such a node is found, a link is added connecting this to the original node, and increasing the number of cycles in the graph; if such a node cannot be found, a new node is added, which is linked to the original node. We simulate this algorithm and find that we cannot reject the hypothesis that the empirical degree distribution is a q-exponential function, which has been used to model long-range processes in nonequilibrium statistical mechanics. A generative model for feedback networks Douglas White Natasa Kejzar Constantino Tsallis Doyne Farmer Scott White (31 Jul 2005) 2007-11-06T00:01:34-00:00 2005 feedback network