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Autonomous decision-making is a central challenge to theories and technologies of AI and computational intelligence. It could not be implemented because the inexhaustive, indeterministic, and uncertain bottlenecks in traditional machine inference theories. This paper presents a formal study on mathematical models of decision and decision-making. Generic mathematical models of formal decisions are created for qualitative, quantitative, and serial decision-making. Cognitive algorithms are developed to extend traditional intuitive, empirical, or heuristic decisions to machine-learnt inferences for decision making. Experiments have demonstrated the power of cognitive decision-making algorithms and technologies for autonomous systems and computational intelligence.
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Yingxu Wang (2020) studied this question.
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