engleski

Cybernetic Models of Biotic Systems: Understanding Emerging Biocomplexity

Terrestrial evolutionary processes produced structurally and functionally increasingly complex biotic systems. Increases in complexity promoted development of a coordination-and-control apparatus. Emergence of neural apparatus facilitated development of physiological feedback mechanisms resulting in biotic systems becoming proactive agents rather than passive subjects to environmental change. Contemporary research in molecular and population genetics relates physiological processes to population dynamics and provides insight into emerging properties of complex evolving systems. Cybernetics investigates communication and control within systems. Applied to astrobiology, controllable cybernetic models simulate biotic systems and provide insight into their dynamics emerging from increasingly complex functional organization and interactions with the environment. Our research group developed a biocybernetic model designed to simulate evolutionary and population dynamics of highly complex anthropological systems. This research tool simulates population dynamics of agents within a complex biosocial environment. It provides a suitable means for understanding complexity of emergent phenomena such as interaction between genetic kinship, environmental disposition, available resources and population dynamics. Congruity of 82% between control and simulation data sets was achieved by the model. Ongoing research focuses on the model's use as predictive tool for investigations of evolutionary and population dynamics of complex biotic systems based on data describing their population size, environmental conditions, estimated reproduction rates and/or physiological and biosocial organization. The model's ability to simulate various levels of systemic complexity makes it a suitable research tool applicable to a wide range of evolutionary scenarios that are in focus of current research in astrobiology - from evolution of biocomplexity to emergence of intelligence.

cybernetic models; biotic systems; biocomplexity

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