MLPSyntheticSimulation

class coba.environments.MLPSyntheticSimulation

A synthetic simulation whose reward function belongs to the MLP family.

The MLP architecture has a single hidden layer with sigmoid activation and one output value calculated from a random linear combination of the hidden layer’s output.

Constructors

__init__(n_interactions: int, n_actions: int = 10, n_context_features: int = 10, n_action_features: int = 10, seed: int = 1) → None

Instantiate an MLPSythenticSimulation.

Parameters:

• n_interactions – The number of interactions the simulation should have.

• n_actions – The number of actions each interaction should have.

• n_context_features – The number of features each context should have.

• n_action_features – The number of features each action should have.

• seed – The random number seed used to generate all features, weights and noise in the simulation.

Methods

read() → Iterable[SimulatedInteraction]

A sequence of interactions.

Remarks:

This function should always be “re-iterable”.

Attributes

params