A committee machine is a type of artificial neural network using a divide and conquer strategy in which the responses of multiple neural networks (experts) are combined into a single response.
[1] The combined response of the committee machine is supposed to be superior to those of its constituent experts.
In this class of committee machines, the responses of several predictors (experts) are combined by means of a mechanism that does not involve the input signal, hence the designation static.
In boosting, a weak algorithm is converted into one that achieves arbitrarily high accuracy.
In hierarchical mixture of experts, the individual responses of the individual experts are non-linearly combined by means of several gating networks arranged in a hierarchical fashion.