# Exponential Weights Algorithms

This is an important family of algorithms in Competitive On-line Prediction. At each trial the weight of each strategy in the benchmark class is multiplied by , where is a constant called the *learning rate* and is the strategy's loss. The master's prediction is obtained as a weighted average (in different senses) of the strategies' predictions.

Algorithms in this class include: