Real life: Cellular automaton for investigating competition between pleiotrophy and redundancy

Abstract

Redundancy is where multiple agents perform one task. On the other hand, pleiotropy is the inverse of redundancy- that is, where one agent multitasks. In real systems it is usual to find a mixture of both pleiotropic and redundant agents. In engineered systems we may see this in communication networks, computer systems, smart structures, nano-self-assembled systems etc. In biological systems, we can also observe the interplay of pleiotropy and redundancy from neural networks through to DNA coding. The open question is how to design a given complex system with the correct trade-off between redundancy and pleiotropy, in order to confer maximum robustness for lowest cost. Here we propose an evolutionary computational approach for exploring this trade-off in a toy model cellular automation, dubbed Real Life.