Magnuswhich

Magnuswhich is a hypothetical framework used to illustrate decision-making under uncertainty. In theoretical discussions, it provides a method for selecting among competing options by balancing multiple criteria and practical feasibility, rather than relying on a single metric.

The framework describes each option with a vector of features and assigns weights to reflect relative importance. A magnuswhich score combines expected desirability with constraint satisfaction, and the chosen option is the one with the highest score subject to feasibility constraints.

Variants include a deterministic form with fixed weights and a probabilistic form that models uncertainty in criteria through distributions. A robust version conducts sensitivity analyses to assess how results change under different weighting schemes.

Applications are mainly in thought experiments, multi-criteria decision analysis, and AI planning simulations used in education and research to compare different decision rules.

Limitations include dependence on the quality of feature definitions and weights, potential bias in weighting, and computational complexity for large option sets. Like other decision rules, magnuswhich cannot guarantee optimal real-world outcomes.

The name combines magnus, Latin for great, with which to emphasize its selection role. This article presents magnuswhich as a fictional construct used for illustrative purposes in discussions of decision theory.