from mushroom_rl.core import Serializable
[docs]class Agent(Serializable):
"""
This class implements the functions to manage the agent (e.g. move the agent
following its policy).
"""
[docs] def __init__(self, mdp_info, policy, features=None):
"""
Constructor.
Args:
mdp_info (MDPInfo): information about the MDP;
policy (Policy): the policy followed by the agent;
features (object, None): features to extract from the state.
"""
self.mdp_info = mdp_info
self.policy = policy
self.phi = features
self.next_action = None
self._add_save_attr(
mdp_info='pickle',
policy='mushroom',
phi='pickle',
next_action='numpy'
)
[docs] def fit(self, dataset):
"""
Fit step.
Args:
dataset (list): the dataset.
"""
raise NotImplementedError('Agent is an abstract class')
[docs] def draw_action(self, state):
"""
Return the action to execute in the given state. It is the action
returned by the policy or the action set by the algorithm (e.g. in the
case of SARSA).
Args:
state (np.ndarray): the state where the agent is.
Returns:
The action to be executed.
"""
if self.phi is not None:
state = self.phi(state)
if self.next_action is None:
return self.policy.draw_action(state)
else:
action = self.next_action
self.next_action = None
return action
[docs] def episode_start(self):
"""
Called by the agent when a new episode starts.
"""
self.policy.reset()
[docs] def stop(self):
"""
Method used to stop an agent. Useful when dealing with real world
environments, simulators, or to cleanup environments internals after
a core learn/evaluate to enforce consistency.
"""
pass