Approximators

MushroomRL provides a hierarchy of approximator classes for both tabular and function-approximation settings.

The base class Approximator dispatches to an Ensemble of models when n_models > 1 is passed to the constructor. This means any approximator subclass (Table, LinearApproximator, …) can be turned into an ensemble simply by passing n_models:

# single model
q = Table(shape=(10, 4))

# ensemble of 5 tables — returns an Ensemble instance transparently
q = Table(n_models=5, shape=(10, 4))

`Approximator`	Base class for all approximators.
`QApproximator`	Interface for Q-function approximators.
`Table`	Table approximator.
`LinearApproximator`	This class implements a linear approximator.
`CMAC`	This class implements a Cerebellar Model Arithmetic Computer.
`TorchApproximator`	Class to interface a pytorch model to the mushroom Regressor interface.
`RecurrentTorchApproximator`	Class extending the TorchApproximator for the recurrent-network setting.