'LEARNING_RATE': 1e-3,
'REPLAY_BUFFER_SIZE': 1000,
'MIN_REPLAY_BUFFER_SIZE': 100,
'EPSILON_START': 1,
'EPSILON_END': 0.1,
'EPSILON_DECAY_DURATION': 5000,
}
# Allow changing hyperparameters from command-line arguments
args = get_args(default_args=args_dict)
# Create wrapped environment
env = make_env(args.ENV_ID)
# Set Seed
set_seed(env, args.SEED)
# GPU or CPU
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
# Create agent
agent = Agent(env, device, args)
# Train agent for args.NB_FRAMES
agent.train()
# Save agent
agent.save()
# Test agent
agent.test(render=False)
