Collaborative breeding system based on a consortium of heterogeneous intelligent agents

The architecture of a human-machine intelligent system has been developed based on a consortium of intelligent software and cyber-physical agents that perform simulation modeling, decision making and synthesis of cooperative control of selection and seed production processes. Understanding the meaningful content and collective decision-making in the production and agrotechnical cycles of breeding and seed production in systems based on such a computing architecture will be ensured by the work of cooperative intelligent software agents of general artificial intelligence based on multi-agent neurocognitive architectures. The developed computational model of a distributed consortium of heterogeneous intelligent agents can be used to create intelligent expert and collaborative information and control systems that provide a significant increase in the efficiency of breeding and seed production based on the use of self-learning decentralized multi-agent neurocognitive systems for controlling the processes of precise selection and seed production.