def __init__(self,
learner,
memory,
simulator,
settings,
dqn_policy=None,
rollout_policy=None):
"""
The learning agent is responsible for communicating and moving
data between the three modules: Learner, Simulator, Memory
Inputs:
- learner: containes the neural network and the optimizer to train it
- memory: expereince replay memory that can be minibatch sampled
- simulator: simulates the environemnt
- settings: hyper parameters for training
- rollout_policy: rollout policy, random by default
"""
self.learner = learner
self.memory = memory
self.simulator = simulator # for populating the experience replay
self.evaluator = deepcopy(simulator) # for evaluation
self.dqn_policy = dqn_policy
if dqn_policy is None:
self.dqn_policy = DQNPolicy(learner)
self.rollout_policy = rollout_policy
if rollout_policy is None:
self.rollout_policy = RandomPolicy(simulator.n_actions)
self.set_params(settings)
self.n_epochs = self.iterations / float(memory.memory_size)
self.iteration = []
self.loss = []
self.q_ave = []
self.eval_iteration = []
self.r_eval = []
self.r_per_episode_eval = []
