Description of Emergent Phenomena That Are Observed within Physical, Bio-Chemical, and Biological Complex Systems Using Cellular Automata as Means of Massively-Parallel Computations

The position paper serves scientists from all scientific disciplines to get a quick, concise, and easy-to-understand primer that describes the basic principles of design and applications of massively-parallel computations and models. The thesis of the position paper is, “What is the estimated direction of development of massively-parallel computing techniques utilizing emergents as observed in all scientific disciplines?” The birth of massively-parallel computations (MPCs) in the 1940s is closely related to the development of both early computers and simulations of nuclear processes that are operating within matter. It would be demonstrated that MPCs are becoming front and center in many research areas after a long delay that was forced by the previous inaccessibility of MPC computers. Another impetus to the development of MPCs came in the form of generalization of mathematical descriptions of observed natural phenomena using differential equations. More specifically, discretization schemes of differential equations got implemented in MPC simulations. Those achievements opened doors to the development of advanced descriptions of natural phenomena. Currently, there exist a number of MPC techniques that are gaining an increasing influence on the description of self-organization, emergence, replication, self-replication, and error-resilience within living and nonliving systems. A promising class of cellular automata, which is capable of describing a wide range of processes observed within natural phenomena, is called emergent information processing (EIP). The EIP approach is opening doorstowards future descriptions of many observed biological phenomena that are notoriously resisting mathematical and computational descriptions. Fixed and ad hoc networks, which are observed in living and non-living systems, could be interpreted using EIP methodology; this offers an opportunity for computational studies of emergent processes operating within them. Demonstrated approaches represent a toolkit that could be applied in all areas of research that are dealing with living systems. The usefulness of the EIP approach is demonstrated on a special case of emergent synchronization simulation, which could be applied in the design of artificial, biocompatible pacemaker implants and computers utilizing emergent computations.