Ontology of human-machine collaboration patterns for decision support

In the process of human-machine collaboration, recurring problems often arise, prompting the use of collaboration patterns that offer ready-made solution schemes for similar recurring issues. The aim of the research is to develop models that facilitate the organization of human-machine collaboration while supporting decision-making based on collaboration patterns. The paper employs methods of conceptual, ontological, and scenario modeling. Based on the descriptions of collaboration patterns found in various problem areas, conceptual models were constructed representing five types of patterns: organizational patterns, cognitive patterns, information interaction patterns, process patterns, and joint engineering patterns. An ontological model of a collaboration pattern and an ontology of human-machine collaboration patterns were developed, integrating various types of such patterns. The developed models represent a new result that unifies existing approaches to the description of collaboration patterns. A scenario variant is proposed, demonstrating the possibility of using the developed ontology to support decision-making. The developed models for organizing human-machine teams and their activities can enhance the quality of decisions by using solution patterns for similar problems and ensuring effective cooperation between humans and machines.