Decentralization

Our Generative Cooperative Network is a systems biology technique that integrates separate scientific findings rather than looking solely at siloed or reductionist studies. This whole is built in a decentralized market, with biological entities like cells viewed as adaptive and dynamic, with their own agendas that combine to create self-reinforcing states of maintenance and aging. These states are the Nash equilibrium of their separate agendas, and they are the result of a mix of cooperation and competition among these co-adapting agents. This is consistent with the belief that regeneration for longevity necessitates understanding of the behavior of agential materials.

Using the data absorption technique, adaptive and nonadaptive models are automatically combined into a multiresolutional simulation. Neural networks, which we use as adaptive models, and Bayesian networks, which we use as non adaptive models, are two important types of these models. In the GCN decentralized simulated market, both types of models are combined. We will provide software support for the incorporation of models contributed by data scientists and research scientists, such as Bayesian networks, generative neural networks, and simulation models, into our composite multiresolutional models of the human body. Scientists will be compensated in tokens if their models are useful in solving longevity-related problems as part of GCN ensembles.