Decision under Uncertainty

This work addresses a foundational issue in decision theory and AI, providing a theoretical basis for handling uncertainty, though it appears incremental as it builds on existing axiomatic approaches.

The paper tackles the problem of decision-making under uncertainty by deriving an axiomatic probability function for any form of underlying uncertainty, resulting in a general framework for such decisions.