bolero.environment.ContextualObjectiveFunction¶

class bolero.environment.ContextualObjectiveFunction(name='LinearContextualSphere', n_params=1, n_context_dims=1, random_state=None, **kwargs)[source]¶

Artificial contextual benchmark function.

Parameters:	name : string, optional (default: ‘LinearContextualSphere’) Name of the objective function n_params : int, optional (default: 1) Number of dimensions n_context_dims : int, optional (default: 1) Number of context dimensions random_state : RandomState or int, optional (default: None) Random number generator or seed kwargs : optional (default: {}) Additional keyword arguments for objective function

__init__(name='LinearContextualSphere', n_params=1, n_context_dims=1, random_state=None, **kwargs)[source]¶

get_args()¶

Get parameters for this estimator.

Returns:	params : mapping of string to any Parameter names mapped to their values.

get_maximum_feedback(context)[source]¶

Returns the maximum feedback obtainable in given context.

get_num_context_dims()[source]¶

Returns the number of context dimensions.

is_behavior_learning_done()[source]¶

Check if the behavior learning is finished.

Returns:	finished : bool Is the learning of a behavior finished?

request_context(context=None)[source]¶

Request that a specific context is used.

Parameters:	context : array-like, shape (n_context_dims,), optional (default=None) The requested context that shall be used in the next rollout. Defaults to None. In that case, the environment selects the next context.
Returns:	context : array-like, shape (n_context_dims,) The actual context used in the next rollout. This is either the requested context or selected by the environment.