mlpy.learners.LearnerFactory.create¶
-
static
LearnerFactory.
create
(_type, *args, **kwargs)[source]¶ Create an learner of the given type.
A new learner of the given type is created. If progress is among the keywords in kwargs, the factory attempts to recover the learner from the learner state saved to file filename. If the factory fails to load the learners state from file, a new learner is created.
Parameters: _type : str
The learner type. Valid learner types:
- qlearner
Performs q-learning, a reinforcement learning variant. A
QLearner
module is created.- rldtlearner
The learner performs reinforcement learning with decision trees (RLDT), a method introduced by Hester, Quinlan, and Stone which builds a generalized model for the transitions and rewards of the environment. A
RLDTLearner
module is created.- apprenticeshiplearner
The learner performs apprenticeship learning via inverse reinforcement learning, a method introduced by Abbeel and Ng which strives to imitate the demonstrations given by an expert. A
ApprenticeshipLearner
module is create.- incrapprenticeshiplearner
The learner incrementally performs apprenticeship learning via inverse reinforcement learning. Inverse reinforcement learning assumes knowledge of the underlying model. However, this is not always feasible. The incremental apprenticeship learner updates its model after every iteration by executing the current policy. A
IncrApprenticeshipLearner
module is create.
args : tuple, optional
Positional arguments passed to the class of the given type for initialization.
kwargs : dict, optional
Non-positional arguments passed to the class of the given type for initialization.
Returns: ILearner :
A learner instance of the given type.