Engineering Decisions for Regenerative Economies
Keywords:
Autonomous Knowledge Networks,Intelligent Decision Engineering,Sustainable Economic Growth,Artificial Intelligence Ecosystems,Knowledge Graph Analytics,Autonomous Decision Support Systems,Cognitive Computing,Data-Driven Governance,Digital Transformation,Economic Intelligence Platforms,Multi-Agent Systems,Explainable Artificial Intelligence (XAI),Enterprise Knowledge Management,Sustainable Innovation Networks,Intelligent Economic Forecasting.Abstract
Sustainable economic growth demands fundamental changes in how the global economy operates and evolves. Autonomous Knowledge Networks (AKNs) offer significant potential for driving society toward a smarter, more sustainable economic paradigm by supporting Digital Twins of environments, economies, and societies that enable decentralized, autonomous decision-making through engineered intelligence. Yet a comprehensive account of the architectural design that enables such autonomous functioning, along with the methods that allow AKNs to operate independently of outside supervision, remains lacking. These two questions are addressed below.
We first introduce the architectural design of an AKN, detailing its overarching framework, layered structure, governance mechanisms, and core components, with particular attention to the data layer, which ensures the grounding and consistency of the knowledge the network generates. We then propose a formalization of the data repositories underpinning this layer, addressing key considerations including data and knowledge sources, the ontologies employed, metadata attached to stored elements, data lineage, associated quality metrics, and caching strategies. We further highlight the importance of monitoring the integrity, completeness, and consistency of source data, and conclude by discussing the functions and protocols needed to ensure the interoperability and scalability of the data layer.
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