Toward a theory of evolution as multilevel learning.

ABSTRACT: We apply the theory of learning to physically renormalizable systems in an attempt to outline a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution that appear to be necessary and sufficient to render a universe observable and show that they entail the major features of biological evolution, including replication and natural selection. It is shown that these cornerstone phenomena of biology emerge from the fundamental features of learning dynamics such as the existence of a loss function, which is minimized during learning. We then sketch the theory of evolution using the mathematical framework of neural networks, which provides for detailed analysis of evolutionary phenomena. To demonstrate the potent

SUBMITTER: Vanchurin V 

PROVIDER: S-EPMC8833143 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature