Efficiency of Energy Exchange Strategies in Model Bacteriabot Populations

Micro/nanorobotics is becoming part of the future of medicine. One of the most efficient approaches to the construction of small medical robots is to base them on unicellular organisms. This approach inherently allows for obtaining complex capabilities, such as motility or environmental resistance. Single-celled organisms usually live in groups and are known to interact in many ways (matter, energy, and information), paving the way for potentially beneficial emergent effects. One such naturally expected effect is an increase in the sustainability of a population as a result of a more even redistribution of energy within the population. Our in silico experiments show that under harsh conditions, such as resource scarcity and a rapidly changing environment, altruistic energy exchange (supplying energy to weaker agents) can indeed markedly increase the sustainability of model bacteriabot groups, potentially increasing the efficiency of treatment. Although our work is limited exclusively to the development and use of a phenomenological computer model, we consider our results to be an important argument in favor of practical efforts aimed at implementing altruistic energy exchange strategies in real swarms of single-cell medical robots.