Cognitive peering infrastructure for the organization teamwork on projects based on agile methodology

Purpose of research. The goal of the work is to develop and justify a cognitive peer-to-peer infrastructure that will improve the conditions for collective work on projects based on agile methodology. Cognitive architecture is defined as a structure that ensures the implementation of anthropomorphic and neuromorphic functions in natural or artificial systems. The proposed approach is based on organizing the interaction of the collective intelligence of members of an agile team and artificial intelligence, represented by trained artificial neural networks. When forming an agile team, it is proposed to take into account the structure of the cognitive sphere in the structure of the mental processes of a human cognitive agent. Methods. Domain knowledge is determined based on the collective intelligence of the agile team members and the training of artificial neural networks. It is assumed that artificial neural networks are available to all members of an agile team and implement the functions of collective artificial intelligence, provided that their training uses the professionalism and experience of a person in a natural social environment. Mental operations such as analysis, partitioning (modularization), comparison, abstraction, synthesis, generalization, classification, concretization, known from general psychology courses, are interpreted not only as a result of human activity, but also as the functionality of a program. Some elements of the cognitive sphere processes “memory” and “speech” are realized in a similar way. Results. The system is implemented on the basis of a peer-to-peer computer network that provides communications between all artificial and natural participants in the cognitive process during the design process. A conceptual model of a cognitive collective intelligence cell is proposed, combining elements of the actual collective intelligence of agile agents with the collective artificial intelligence of agents based on neural networks. In an expert assessment of the quality of individual design stages, it was proposed to use tagging based on the emotional-volitional and motivational mental processes of individuals. Conclusion. Cognitive information processing is based on the idea of modeling human thinking processes in computer systems. In the system under consideration, this includes natural language processing, written speech recognition, associated with understanding information through software imitation of human intelligence. The accepted concept involves the implementation of collective intelligence not only artificially, but also by organizing convenient interaction between participants in an intellectual chat. Artificial intelligence, also collective, is implemented using initially trained and further trained neural networks.