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hub / github.com/lazyprogrammer/machine_learning_examples / main

Function main

rl2/mountaincar/pg_theano_random.py:202–225  ·  view source on GitHub ↗
()

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200
201
202def main():
203 env = gym.make('MountainCarContinuous-v0')
204 ft = FeatureTransformer(env, n_components=100)
205 D = ft.dimensions
206 pmodel = PolicyModel(ft, D, [], [])
207 gamma = 0.99
208
209 if 'monitor' in sys.argv:
210 filename = os.path.basename(__file__).split('.')[0]
211 monitor_dir = './' + filename + '_' + str(datetime.now())
212 env = wrappers.Monitor(env, monitor_dir)
213
214
215 totalrewards, pmodel = random_search(env, pmodel, gamma)
216
217 print("max reward:", np.max(totalrewards))
218
219 # play 100 episodes and check the average
220 avg_totalrewards = play_multiple_episodes(env, 100, pmodel, gamma, print_iters=True)
221 print("avg reward over 100 episodes with best models:", avg_totalrewards)
222
223 plt.plot(totalrewards)
224 plt.title("Rewards")
225 plt.show()
226
227
228if __name__ == '__main__':

Callers 1

Calls 4

FeatureTransformerClass · 0.90
PolicyModelClass · 0.70
random_searchFunction · 0.70
play_multiple_episodesFunction · 0.70

Tested by

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