robust massive parallel information processing environments in biology and medicine: case study

The current frontiers in the description and simulation of advanced physical and biological phenomena observed within all scientific disciplines are pointing toward the importance of the development of robust mathematical descriptions that are error resilient. complexity research is lacking deeper knowledge of the design methodology of processes that are capable to recreate the robustness, which is going to be studied on massive-parallel computations (mpcs) implemented by cellular automata (ca). a simple, two-state cellular automaton having an extremely simple updating rule, which was created by john h. conway called the ’game of life’ (gol) is applied to simulate and logic gate using emergents. this is followed by simulations of a robust, generalized gol, which works with nine states instead of two, that is called r-gol (open-source). extra states enable higher intercellular communication. the logic gate is simulated by the gol. it is destroyed by injection of random faulty evaluations with even the smallest probability. the simulations of the r-gol are initiated with random values. several types of emergent structures, which are robust to injection of random errors, are observed for different setups of the r-gol rule. the gol is not robust. the r-gol is capable to create and maintain oscillating, emergent structures that are robust under constant injection of random, faulty evaluations with up to 1% of errors. the r-gol express long-range synchronization, which is together with robustness facilitated by designed intercellular communication.