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Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective

22 October 2022
Caesar Wu
R. Kotagiri
Rui Zhang
Pascal Bouvry
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Abstract

Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex. It is the art of possibility. We develop a systematic taxonomy of decision-making frames that consists of 6 bases, 18 categorical, and 54 frames. We aim to lay out the computational foundation that is possible to capture a comprehensive landscape view of a strategic problem. Compared with traditional models, it covers irrational, non-rational and rational frames c dealing with certainty, uncertainty, complexity, ambiguity, chaos, and ignorance.

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