"""NOP (no optimization performed) policy search algorithm."""
from garage.np.algos.rl_algorithm import RLAlgorithm
[docs]class NOP(RLAlgorithm):
"""NOP (no optimization performed) policy search algorithm."""
[docs] def init_opt(self):
"""Initialize the optimization procedure."""
[docs] def optimize_policy(self, paths):
"""Optimize the policy using the samples.
Args:
paths (list[dict]): A list of collected paths.
"""
[docs] def train(self, runner):
"""Obtain samplers and start actual training for each epoch.
Args:
runner (LocalRunner): LocalRunner is passed to give algorithm
the access to runner.step_epochs(), which provides services
such as snapshotting and sampler control.
"""