Measuring Phenotypic Structural Complexity of Artificial Cellular Organisms

摘要: Artificial multi-cellular organisms develop from a single zygote to different structures and shapes, some simple, complex. Such phenotypic structural complexity is the result of morphogenesis, where cells grow differentiate according information encoded in genome. In this paper we investigate artificial cellular at level, order understand if genome could be used predict emergent complexity. Our measure based on theory Kolmogorov approximations. We relate Lambda parameter, with its ability detect behavioral regimes, calculated It shown that easily computable Lempel-Ziv approximation has good discriminate complexity, thus providing measurement can related parameter for estimation developed organism’s The experimental model herein 1D, 2D 3D Cellular Automata.