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

October 22, 2022 Β· Declared Dead Β· πŸ› ACM Computing Surveys

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Authors Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry arXiv ID 2210.12373 Category cs.AI: Artificial Intelligence Citations 24 Venue ACM Computing Surveys Last Checked 4 months ago
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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