Intelligent Models and Architectures for Global Learning-Oriented Cooperation

This paper presents the design of intelligent models and architectures for global learning-oriented cooperation. The research work brings our current investigations towards the definition of a general development methodology for global intelligent systems. We use a basic top-down approach to analyze global cooperation, adding more natural intelligence into our models. Then we design, integrate and adapt software architectures to be able to extract the computational requirements of our systems at an appropriate level of abstraction. Our architectural designs serve to dynamically generate cooperative knowledge and behaviour using hybrid registries and intelligent engines. The registries store knowledge and behaviour descriptions. The functional engines control knowledge delivery processes and behaviour executions involving single and composite actions. All these elements are evaluated using a designing case study in current Sustainable Development Goals for education. This last part of the paper also discusses how our intelligent models and architectures can be further developed adding implementation details based on recent technologies.