Wald's maximin model

In decision theory and game theory, Wald's maximin model is a non-probabilistic decision-making model according to which decisions are ranked on the basis of their worst-case outcomes – the optimal decision is one with the least worst outcome. It is one of the most important models in robust decision making in general and robust optimization in particular.

It is also known by a variety of other titles, such as Wald's maximin rule, Wald's maximin principle, Wald's maximin paradigm, and Wald's maximin criterion. Often 'minimax' is used instead of 'maximin'.

Wald's generic maximin model is as follows:

where ${\displaystyle D}$ denotes the decision space; ${\displaystyle S(d)}$ denotes the set of states associated with decision ${\displaystyle d}$ and ${\displaystyle f(d,s)}$ denotes the payoff (outcome) associated with decision ${\displaystyle d}$ and state ${\displaystyle s}$.

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