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

• URL: http://arxiv.org/abs/2210.12373v1
• Date: Sat, 22 Oct 2022 07:01:10 GMT
• Title: Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective
• Authors: Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry
• Abstract summary: We develop a systematic taxonomy of decision-making frames that consists of 6 bases, 18 categorical, and 54 frames. Compared with traditional models, it covers irrational, non-rational and rational frames c dealing with certainty, uncertainty, complexity, ambiguity, chaos, and ignorance.
• Score: 15.649335092388897
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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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