Formal genome model of a general artificial intelligence agent based on multi-agent neurocognitive architectures

The relevance of the research is determined by the need to develop and programmatically implement artificial general intelligence agents capable of self-learning based on adaptation to the conditions of solving problems of the universal spectrum based on the ontoepiphilosociogenetic learning process. The research is aimed at developing a formalization of a general artificial intelligence agent suitable for creating its simulation model. A formalization of an intelligent agent is constructed based on two-level multi-agent neurocognitive architectures using an automatic description and multi-agent functions. A formal description of the genomes of neuron agents as part of a multi-agent neurocognitive architecture and the genotype of an intelligent agent has been developed. The resulting formalization can be used to create software for general artificial intelligence systems.