Autonomous learning for decision making in complex situations

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The project aims to create a novel research direction – autonomous machine learning for data-driven decision-making – that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively handle tremendous uncertainties in data, learning processes and decision outputs, particularly enabling smart learning in massive domains, massive streams, and massive-agent sequentially changing environments. The project’s outcomes are expected to improve data-driven decision-making in multiple industry sectors.