# Minimax Decision Rule

A Minimax Decision Rule is a decision rule that minimize a maximum loss.

**AKA:**Minimax.**Counter-Example(s):**- a Bayes Rule (that minimized an average loss).

**See:**Decision Theory, Loss Function, Zero-Sum, Minimax Estimator, Minimax Value.

## References

### 2015

- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Minimax Retrieved:2015-9-15.
**Minimax**(sometimes MinMax or**MM**^{[1]}) is a decision rule used in decision theory, game theory, statistics and philosophy for*mini*mizing the possible loss for a worst case (*max*imum loss) scenario. Originally formulated for two-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision making in the presence of uncertainty.

- ↑ Provincial Healthcare Index 2013 (Bacchus Barua, Fraser Institute, January 2013 -see page 25-)