Title :
The artificial epigenetic network
Author :
Turner, Alexander P. ; Lones, Michael A. ; Fuente, Luis A. ; Stepney, Susan ; Caves, Leo S. D. ; Tyrrell, A.
Author_Institution :
Dept. of Electron., Univ. of York, York, UK
Abstract :
In this paper we describe an Artificial Gene Regulatory Network (AGRN), whose form and function are inspired by biological epigenetics. This new architecture, termed an Artificial Epigenetic Network (AEN), is applied to the coupled inverted pendulum task, a control task that has complex non-linear dynamics. The AENs show significant benefits over previous AGRNs. Firstly, when applied to the coupled inverted pendulum task, they show a significant performance increase. In addition, the AENs self-partition, applying different genes to control different dynamics within the task, which is more analogous to gene regulation in nature. These networks also make it possible to gain user control over the dynamics of the network via the modification of the epigenetic layer.
Keywords :
genetic algorithms; nonlinear control systems; nonlinear dynamical systems; pendulums; AEN; AGRN; artificial epigenetic network; artificial gene regulatory network; biological epigenetics; complex nonlinear dynamics; coupled inverted pendulum task; gene regulation; network dynamics; user control; Biological information theory; Conferences; DNA; Educational institutions; Gene expression; Organisms;
Conference_Titel :
Evolvable Systems (ICES), 2013 IEEE International Conference on
Conference_Location :
Singapore
DOI :
10.1109/ICES.2013.6613284