Cellular automata and immunity amplified stochastic diffusion search

Abstract

Nature has often provided the inspiration needed for new computational paradigms and metaphors [1,16]. However natural systems do not exist in isolation and so it is only natural that hybrid approaches be explored. The article examines the interplay between three biologically inspired techniques derived from a plethora of natural phenomena. Cellular automata with their origins in crystalline lattice formation are coupled with the immune system derived clonal selection principle in order to regulate the convergence of the stochastic diffusion search algorithm. Stochastic diffusion search is itself biologically inspired in that it is an inherently multi-agent oriented search algorithm derived from the non-stigmergic tandem calling / running recruitment behaviour of ant species such as Temnothorax albipennis. The paper presents an invesitigation into the role cellular automata of differing complexity classes can play in order to establish a balancing mechanism between exploitation and exploration in the emergent behaviour of the system... © 2010 Springer-Verlag Berlin Heidelberg.