EPSRC Network on Evolvability in Biology & Software Systems

Evolvability, Genetics & Development in Natural and Constructed Systems: Abstracts of the EPSRC Evolvability Network Symposium

Tewin Bury Farm Hotel, Hertfordshire, England, UK
26-28 August 2003


University of Hertfordshire Computer Science Technical Report 389
C. L. Nehaniv, P. J. Bentley & S. Kumar (Editors)

Evolving GRNs as Real-Time Behavioural Control Systems

Evolving GRNs as Real-Time Behavioural Control Systems

TOM QUICK, CHRYSTOPHER L. NEHANIV AND KERSTIN DAUTENHAHN

Department of Computer Science
University College London
Gower Street, London WC1E 6BT, UK

T.Quick@cs.ucl.ac.uk

Adaptive Systems Research Group
University of Hertfordshire
Hatfield Herts AL10 9AB
United Kingdom

C.L.Nehaniv@herts.ac.uk, K.Dautenhahn@herts.ac.uk


In contrast with GRN models that use genotype to phenotype mappings inspired by the process of biological development as a technique for pattern formation (Eggenberger, Kumar) or the production of artifical agent body plans and neural network controllers (Dellaert and Beer, Bongard), we present a model that focuses on the evolution of heritable regulatory mechanisms in populations of artificial organisms as a technique for producing emergent behaviour via continual coupling to an environment. Rather than using GRNs to produce control systems the run-time operation of which GRNs play no part in, in our model GRNs are the primary drivers of behavioural dynamics throughout artificial organisms' lifetimes.