mlpy.mdp.continuous.casml.CASML

class mlpy.mdp.continuous.casml.CASML(cbtdata, cbvdata=None, ncomponents=1, proba_calc_method=None, actions=None, n_init=1, **kwargs)

Bases: mlpy.mdp.IMDPModel

Continuous Action and State Model Learner (CASML).

Parameters:

cbtdata : CbTData

The transition case base data.

cbvdata : CbVData

The value case base data.

ncomponents : int, optional

Number of states of the hidden Markov model. Default is 1.

proba_calc_method : str, optional

The method used to calculate the probability distribution for the initial states. Default is DefaultProbaCalcMethod.

actions : list or dict, optional

A list of possible discrete actions.

Attributes

cases
experience
mid	The module’s unique identifier.

Methods

fit(obs, actions[, rewards, n_init])	Fit the CaseBase and the HMM.
get_actions([state])	Retrieve the available actions for the given state.
init()	Initialize the MDP model.
load(filename)	Load the state of the module from file.
predict_proba(state, action)	Predict the probability distribution.
retrieve(case_base, state, action[, ...])
sample([state, action])	Sample from the probability distribution.
save(filename)	Save the current state of the module to file.
update(experience)	Update the model with the agent’s experience.