def feed_forward_network_agent(self, environment: Environment) -> Agent: return Academy.FeedForwardNetworkAgent( self, environment.observation_space(), environment.action_space(), self._get_env_save_folder(environment))
def random_agent(self, environment: Environment) -> Agent: return Academy.RandomAgent(self, environment.action_space())
def table_method_agent(self, environment: Environment) -> Agent: return Academy.TableMethodAgent(self, environment.observation_space(), environment.action_space(), self._get_env_save_folder(environment))
import gym import gym_ple from agents.dqn import DQNAgent from models.cnn import DuelingCNNModel from environment import Environment import torch env = Environment('FlappyBird-v0') model = DuelingCNNModel(env.action_space()) agent = DQNAgent(environment=env, model=model) agent.play()