Developing Digital Twin of Plant Based on Emergent Intelligence Concept, Ontology and Multi-agent Technology

The article advances methodology of designing smart digital twins of plants (SDTP) as a multi-level complex adaptive system, integrating the capabilities of cyber-physical and ontology-customizable multi-agent systems for planning and simulation of plants' growth stages, synchronized with stages of real crops. New multi-agent model and method of creating a SDTP are proposed, based on the use of the "emergent intelligence" concept which combine the advantages of centralized and self-organized resource management in a form of self-guided organization. The multi-level, multi-agent resource-service network model of the plant is developed, as well as a method of compensations, that ensures the quasioptimality of plant plans. Ontologically configurable classes of agents and protocols of their interaction are presented. The newmodel and method are implemented in an ontology-customizable multi-agent system for resource scheduling and control of crops. Results of first experiments for wheat and broccoli are discussed and plans for future developments are given.