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Optimize replay buffer

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Shangtong Zhang
2017-05-24 19:45:42 -06:00
parent be9c5cdcdb
commit 45a3f00d32
5 changed files with 83 additions and 39 deletions
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main.py
+7 -6
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@@ -66,24 +66,25 @@ def actor_critic_cart_pole():
config['step_limit'] = 300
config['n_workers'] = 8
config['batch_size'] = 5
config['test_interval'] = 500
config['test_interval'] = 50000
config['test_repeats'] = 5
agent = AsyncAgent(**config)
agent.run()
def dqn_pixel_atari(name):
config = dict()
config['task_fn'] = lambda: PixelAtari(name)
config['optimizer_fn'] = lambda params: torch.optim.RMSprop(params, lr=0.00025)
config['network_fn'] = lambda optimizer_fn: ConvNet(4, 6, optimizer_fn)
history_length = 4
config['task_fn'] = lambda: PixelAtari(name, 30)
config['optimizer_fn'] = lambda params: torch.optim.RMSprop(params, lr=0.00025, alpha=0.95, eps=0.01)
config['network_fn'] = lambda optimizer_fn: ConvNet(history_length, 6, optimizer_fn)
config['policy_fn'] = lambda: GreedyPolicy(epsilon=1.0, final_step=1000000, min_epsilon=0.1)
config['replay_fn'] = lambda: Replay(memory_size=200000, batch_size=32)
config['replay_fn'] = lambda: Replay(memory_size=1000000, batch_size=32, dtype=np.uint8)
config['discount'] = 0.99
config['target_network_update_freq'] = 10000
config['step_limit'] = 0
config['explore_steps'] = 50000
config['logger'] = gym.logger
config['history_length'] = 4
config['history_length'] = history_length
agent = DQNAgent(**config)
agent.run()