Geodesic
Formal genome model of a general artificial intelligence agent based
News of the Kabardin-Balkar scientific center of RAS, no. 5 (2023), pp. 11-24.

Voir la notice de l'article provenant de la source Math-Net.Ru

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.
Keywords: general artificial intelligence, multi-agent systems, neurocognitive architectures, abstract deterministic automata, multi-generational optimization, genetic algorithms, multi-agent functions. 
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M. I. Anchekov; A. Z. Apshev; K. Ch. Bzhikhatlov; S. A. Kankulov; Z. V. Nagoev; O. V. Nagoeva; I. A. Pshenokova; A. A. Khamov; A. Z. Enes. Formal genome model of a general artificial intelligence agent based. News of the Kabardin-Balkar scientific center of RAS, no. 5 (2023), pp. 11-24. http://geodesic.mathdoc.fr/item/IZKAB_2023_5_a0/

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