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Network Biology, 2016, 6(2): 47-54
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Article

Bit by bit control of nonlinear ecological and biological networks using Evolutionary Network Control

Alessandro Ferrarini
Department of Evolutionary and Functional Biology, University of Parma, Via G. Saragat 4, I-43100 Parma, Italy

Received 25 January 2016;Accepted 6 March 2016;Published online 1 June 2016
IAEES

Abstract
Evolutionary Network Control (ENC) has been first introduced in 2013 to effectively subdue network-like systems. ENC opposes the idea, very common in the scientific literature, that controllability of networks should be based on the identification of the set of driver nodes that can guide the system's dynamics, in other words on the choice of a subset of nodes that should be selected to be permanently controlled. ENC has proven to be effective in the global control (i.e. the focus is on mastery of the final state of network dynamics) of linear and nonlinear networks, and in the local (i.e. the focus is on the step-by-step ascendancy of network dynamics) control of linear networks. In this work, ENC is applied to the local control of nonlinear networks. Using the Lotka-Volterra model as a case study, I show here that ENC is capable of locally driving nonlinear networks as well, so that also intermediate steps (not only the final state) are under our strict control. ENC can be readily applied to any kind of ecological, biological, economic and network-like system.

Keywords Evolutionary Network Control;genetic algorithms;intermediate control function;local dynamics;Lotka-Volterra model;network systems;nonlinear networks;predator-prey model.

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